Micro-grid and standalone schemes are emerging as a viable mixed source of electricity due to interconnected costly central power plants and associated faults as well as brownouts and blackouts in additions to costly fuels. Micro-Grid (MG) is gaining very importance to avoid or decrease these problems. The objective of this paper is to design an optimal sizing and energy management scheme of an isolated MG. The MG is suggested to supply load located in El-shorouk Academy, Egypt between 30.119 latitudes and 31.605 longitudes. The components of the MG are selected and designed for achieving minimum Total Investment Cost (TIC) with CO2 emissions limitations. This is accomplished by a search and optimization MATLAB code used with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) techniques. The use of Diesel Generators (DGs) is minimized by limiting the gaseous CO2 emissions as per targeted allowable amount. A comparison is accomplished for investigating the CO2 emissions constraints effects on the TIC in $/year and annual cost of energy in $/kWh. The obtained results verified and demonstrated that the designed MG configuration scheme is able to feed the energy entailed by the suggested load cost effectively and environmental friendly.
The document discusses environmental/economic scheduling of renewable energy resources in a micro-grid. It proposes a multi-objective framework to minimize the total operation cost and emission from generating units. Lexicographic optimization and a hybrid augmented-weighted epsilon-constraint method are used to solve the multi-objective optimization problem and generate Pareto optimal solutions. The decision making process uses a fuzzy technique. Case studies show the proposed method improves solutions for cost, emission, and execution time compared to other methods.
The document presents a novel approach using grey wolf optimization (GWO) to determine the optimal energy management and sizing of battery storage for grid-connected microgrids. The objective is to minimize operational costs by considering the optimal battery size. GWO is implemented and shown to outperform other algorithms like genetic algorithm, particle swarm optimization, bat algorithm, and improved bat algorithm in terms of solution quality and computational efficiency. Numerical results demonstrate that GWO reduces microgrid operational costs by 33.185% compared to other algorithms through smart utilization of battery energy storage.
Determining the Pareto front of distributed generator and static VAR compens...IJECEIAES
The integration of distributed generators (DGs), which are based on renewable energy sources, energy storage systems, and static VAR compensators (SVCs), requires considering more challenging operational cases due to the variability of DG production contributed by different characteristics for different time sequences. The size, quantity, technology, and location of DG units have major effects on the system to benefit from the integration. All these aspects create a multi-objective scope; therefore, it is considered a multi-objective mixed-integer optimization problem. This paper presents an improved multi-objective salp swarm optimization algorithm (MOSSA) to obtain multiple Pareto efficient solutions for the optimal number, location, and capacity of DGs and the controlling strategy of SVC a radial distribution system. MOSSA is a bio-inspired optimizer based on swarm intelligence techniques and it is used in finding the optimal solution for a global optimization problem. Two sets of objective functions have been formulated minimizing DGs and SVC cost, voltage violation, energy losses, and system emission cost. The usefulness of the proposed MOSSA has been tested with the 33-bus and 141-bus radial distribution systems and the qualitative comparisons against two well-known algorithms, multiple objective evolutionary algorithms based on decomposition (MOEA/D), and multiple objective particle swarm optimization (MOPSO) algorithm.
Performance based Comparison of Wind and Solar Distributed Generators using E...Editor IJLRES
Distributed Generation (DG) technologies have become more and more important in power systems. The objective of the paper is to optimize the distributed energy resource type and size based on uncertainties in the distribution network. The three things are considered in stand point of uncertainties are listed as, (i) Future load growth, (ii) Variation in the solar radiation, (iii) Wind output variation. The challenge in Optimal DG Placement (ODGP) needs to be solved with optimization problem with many objectives and constraints. The ODGP is going to be done here, by using Non-dominated Sorting Genetic Algorithm II (NSGA II). NSGA II is one among the available multi objective optimization algorithms with reduced computational complexity (O=MN2). Because of this prominent feature of NSGA II, it is widely applicable in all the multi objective optimization problems irrespective of disciplines. Hence it is selected to be employed here in order to obtain the reduced cost associated with the DG units. The proposed NSGA II is going to be applied on the IEEE 33-bus and the different performance characteristics were compared for both wind and solar type DG units.
This document proposes a multi-objective framework for short-term scheduling of a microgrid considering cost minimization and emission minimization objectives. It formulates the problem as a mixed integer nonlinear program with constraints including power balance and unit generation limits. The Normal Boundary Intersection method is employed to solve the multi-objective problem and generate a Pareto front of optimal solutions. Simulation results are presented comparing the proposed approach to other methods.
This article describes a multi-objective optimization approach to determine the optimal sizing and placement of distributed generation (DG) units in a distribution system. The objectives are to minimize total real power losses and total DG installation cost. A weighted sum method is used to combine the objectives into a single scalar function. Constraints include power flow equations and limits on voltage, generation capacity, and line flows. The problem is formulated as a non-linear program and solved using sequential quadratic programming. The method provides a set of Pareto optimal solutions, from which a compromise solution can be selected using fuzzy decision making. The approach is demonstrated on a 15-bus test system.
Optimum Location of DG Units Considering Operation ConditionsEditor IJCATR
The optimal sizing and placement of Distributed Generation units (DG) are becoming very attractive to researchers these days. In this paper a two stage approach has been used for allocation and sizing of DGs in distribution system with time varying load model. The strategic placement of DGs can help in reducing energy losses and improving voltage profile. The proposed work discusses time varying loads that can be useful for selecting the location and optimizing DG operation. The method has the potential to be used for integrating the available DGs by identifying the best locations in a power system. The proposed method has been demonstrated on 9-bus test system.
Sampling-Based Model Predictive Control of PV-Integrated Energy Storage Syste...Power System Operation
This paper proposes a novel control solution designed to solve the local and grid-connected
distributed energy resources (DERs) management problem by developing a generalizable framework capable
of controlling DERs based on forecasted values and real-time energy prices. The proposed model uses
sampling-based model predictive control (SBMPC), together with the real-time price of energy and forecasts
of PV and load power, to allocate the dispatch of the available distributed energy resources (DERs) while
minimizing the overall cost. The strategy developed aims to nd the ideal combination of solar, grid, and
energy storage (ES) power with the objective of minimizing the total cost of energy of the entire system.
Both ofine and controller hardware-in-the-loop (CHIL) results are presented for a 7-day test case scenario
and compared with two manual base test cases and four baseline optimization algorithms (Genetic Algo-
rithm (GA), Particle Swarm Optimization (PSO), Quadratic Programming interior-point method (QP-IP),
and Sequential Quadratic Programming (SQP)) designed to solve the optimization problem considering the
current status of the system and also its future states. The proposed model uses a 24-hour prediction horizon
with a 15-minute control horizon. The results demonstrate substantial cost and execution time savings when
compared to the other baseline control algorithms.
The document discusses environmental/economic scheduling of renewable energy resources in a micro-grid. It proposes a multi-objective framework to minimize the total operation cost and emission from generating units. Lexicographic optimization and a hybrid augmented-weighted epsilon-constraint method are used to solve the multi-objective optimization problem and generate Pareto optimal solutions. The decision making process uses a fuzzy technique. Case studies show the proposed method improves solutions for cost, emission, and execution time compared to other methods.
The document presents a novel approach using grey wolf optimization (GWO) to determine the optimal energy management and sizing of battery storage for grid-connected microgrids. The objective is to minimize operational costs by considering the optimal battery size. GWO is implemented and shown to outperform other algorithms like genetic algorithm, particle swarm optimization, bat algorithm, and improved bat algorithm in terms of solution quality and computational efficiency. Numerical results demonstrate that GWO reduces microgrid operational costs by 33.185% compared to other algorithms through smart utilization of battery energy storage.
Determining the Pareto front of distributed generator and static VAR compens...IJECEIAES
The integration of distributed generators (DGs), which are based on renewable energy sources, energy storage systems, and static VAR compensators (SVCs), requires considering more challenging operational cases due to the variability of DG production contributed by different characteristics for different time sequences. The size, quantity, technology, and location of DG units have major effects on the system to benefit from the integration. All these aspects create a multi-objective scope; therefore, it is considered a multi-objective mixed-integer optimization problem. This paper presents an improved multi-objective salp swarm optimization algorithm (MOSSA) to obtain multiple Pareto efficient solutions for the optimal number, location, and capacity of DGs and the controlling strategy of SVC a radial distribution system. MOSSA is a bio-inspired optimizer based on swarm intelligence techniques and it is used in finding the optimal solution for a global optimization problem. Two sets of objective functions have been formulated minimizing DGs and SVC cost, voltage violation, energy losses, and system emission cost. The usefulness of the proposed MOSSA has been tested with the 33-bus and 141-bus radial distribution systems and the qualitative comparisons against two well-known algorithms, multiple objective evolutionary algorithms based on decomposition (MOEA/D), and multiple objective particle swarm optimization (MOPSO) algorithm.
Performance based Comparison of Wind and Solar Distributed Generators using E...Editor IJLRES
Distributed Generation (DG) technologies have become more and more important in power systems. The objective of the paper is to optimize the distributed energy resource type and size based on uncertainties in the distribution network. The three things are considered in stand point of uncertainties are listed as, (i) Future load growth, (ii) Variation in the solar radiation, (iii) Wind output variation. The challenge in Optimal DG Placement (ODGP) needs to be solved with optimization problem with many objectives and constraints. The ODGP is going to be done here, by using Non-dominated Sorting Genetic Algorithm II (NSGA II). NSGA II is one among the available multi objective optimization algorithms with reduced computational complexity (O=MN2). Because of this prominent feature of NSGA II, it is widely applicable in all the multi objective optimization problems irrespective of disciplines. Hence it is selected to be employed here in order to obtain the reduced cost associated with the DG units. The proposed NSGA II is going to be applied on the IEEE 33-bus and the different performance characteristics were compared for both wind and solar type DG units.
This document proposes a multi-objective framework for short-term scheduling of a microgrid considering cost minimization and emission minimization objectives. It formulates the problem as a mixed integer nonlinear program with constraints including power balance and unit generation limits. The Normal Boundary Intersection method is employed to solve the multi-objective problem and generate a Pareto front of optimal solutions. Simulation results are presented comparing the proposed approach to other methods.
This article describes a multi-objective optimization approach to determine the optimal sizing and placement of distributed generation (DG) units in a distribution system. The objectives are to minimize total real power losses and total DG installation cost. A weighted sum method is used to combine the objectives into a single scalar function. Constraints include power flow equations and limits on voltage, generation capacity, and line flows. The problem is formulated as a non-linear program and solved using sequential quadratic programming. The method provides a set of Pareto optimal solutions, from which a compromise solution can be selected using fuzzy decision making. The approach is demonstrated on a 15-bus test system.
Optimum Location of DG Units Considering Operation ConditionsEditor IJCATR
The optimal sizing and placement of Distributed Generation units (DG) are becoming very attractive to researchers these days. In this paper a two stage approach has been used for allocation and sizing of DGs in distribution system with time varying load model. The strategic placement of DGs can help in reducing energy losses and improving voltage profile. The proposed work discusses time varying loads that can be useful for selecting the location and optimizing DG operation. The method has the potential to be used for integrating the available DGs by identifying the best locations in a power system. The proposed method has been demonstrated on 9-bus test system.
Sampling-Based Model Predictive Control of PV-Integrated Energy Storage Syste...Power System Operation
This paper proposes a novel control solution designed to solve the local and grid-connected
distributed energy resources (DERs) management problem by developing a generalizable framework capable
of controlling DERs based on forecasted values and real-time energy prices. The proposed model uses
sampling-based model predictive control (SBMPC), together with the real-time price of energy and forecasts
of PV and load power, to allocate the dispatch of the available distributed energy resources (DERs) while
minimizing the overall cost. The strategy developed aims to nd the ideal combination of solar, grid, and
energy storage (ES) power with the objective of minimizing the total cost of energy of the entire system.
Both ofine and controller hardware-in-the-loop (CHIL) results are presented for a 7-day test case scenario
and compared with two manual base test cases and four baseline optimization algorithms (Genetic Algo-
rithm (GA), Particle Swarm Optimization (PSO), Quadratic Programming interior-point method (QP-IP),
and Sequential Quadratic Programming (SQP)) designed to solve the optimization problem considering the
current status of the system and also its future states. The proposed model uses a 24-hour prediction horizon
with a 15-minute control horizon. The results demonstrate substantial cost and execution time savings when
compared to the other baseline control algorithms.
Energy management system for distribution networks integrating photovoltaic ...IJECEIAES
The concept of the energy management system, developed in this work, is to determine the optimal combination of energy from several generation sources and to schedule their commitment, while optimizing the cost of purchased energy, power losses and voltage drops. In order to achieve these objectives, the non-dominated sorting genetic algorithm II (NSGA-II) was modified and applied to an IEEE 33-bus test network containing 10 photovoltaic power plants and 4 battery energy storage systems placed at optimal points in the network. To evaluate the system performance, the resolution was performed under several test conditions. Optimal Pareto solutions were classified using three decision-making methods, namely analytic hierarchy process (AHP), technique for order preference by similarity to ideal solution (TOPSIS) and entropy-TOPSIS. The simulation results obtained by NSGA-II and classified using entropy-TOPSIS showed a significant and considerable reduction in terms of purchased energy cost, power losses and voltage drops while successfully meeting all constraints. In addition, the diversity of the results proved once again the robustness and effectiveness of the algorithm. A graphical interface was also developed to display all the decisions made by the algorithm, and all other information such as the states of power systems, voltage profiles, alarms, and history.
Energy Management System in Smart Microgrid Using Multi Objective Grey Wolf O...IRJET Journal
This document proposes an energy management system for a smart microgrid using a multi-objective grey wolf optimization algorithm. The goals are to maximize the use of local renewable energy generation, minimize consumer energy costs, and reduce greenhouse gas emissions. It describes energy controllers that would manage energy sharing between providers and customers. The multi-objective grey wolf optimization technique is said to provide faster optimization than other methods. Simulation results reportedly show reductions in both pollution and energy consumption costs with this approach.
Economic dispatch by optimization techniquesIJECEIAES
The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic approaches are introduced, the BA and ALOA. A rigorous stochastically developmental computing strategy focused on the action and intellect of ant lions is an ALOA. The ALOA imitates ant lions' hunting process. The introduction of a numerical description of its biological actions for the solution of ED in the power framework. These algorithms are applied to two systems: a small scale three generator system and a large scale six generator. Results show were compared on the metrics of convergence rate, cost, and average run time that the ALOA and BA are suitable for economic dispatch studies which is clear in the comparison set with other algorithms. Both of these algorithms are tested on IEEE-30 bus reliability test system.
A new approach to the solution of economic dispatch using particle Swarm opt...ijcsa
This document presents a new approach to solving the economic dispatch problem using particle swarm optimization combined with simulated annealing (PSO-SA). The economic dispatch problem aims to minimize the total generation cost while satisfying constraints like power demand and generator limits. Previous solutions had limitations. The authors propose using PSO-SA to find high quality solutions more efficiently. PSO is able to find global optima but can get trapped in local optima. SA helps avoid this through probabilistic jumping. The authors combine PSO and SA techniques to leverage their benefits while overcoming individual limitations. They test the PSO-SA method on three generator systems and find it provides better results than traditional and other computational methods.
IRJET- Comprehensive Analysis on Optimal Allocation and Sizing of Distributed...IRJET Journal
This document summarizes a research paper that investigates the optimal allocation and sizing of distributed generation (DG) units in a distribution system using Particle Swarm Optimization (PSO). The objective is to minimize voltage deviation and total power loss. A 33-bus distribution network is used as a case study. The results show that allocating 3 DG units at buses 18, 14, and 17 with sizes of 1.7154 MW, 0.1908 MW, and 1.6159 MW respectively reduces voltage deviation at all buses and total power loss by 89.83%. The PSO technique effectively finds the optimal DG locations and sizes to improve the voltage profile and minimize losses in the distribution network.
Optimal power flow with distributed energy sources using whale optimization a...IJECEIAES
Renewable energy generation is increasingly attractive since it is non-polluting and viable. Recently, the technical and economic performance of power system networks has been enhanced by integrating renewable energy sources (RES). This work focuses on the size of solar and wind production by replacing the thermal generation to decrease cost and losses on a big electrical power system. The Weibull and Lognormal probability density functions are used to calculate the deliverable power of wind and solar energy, to be integrated into the power system. Due to the uncertain and intermittent conditions of these sources, their integration complicates the optimal power flow problem. This paper proposes an optimal power flow (OPF) using the whale optimization algorithm (WOA), to solve for the stochastic wind and solar power integrated power system. In this paper, the ideal capacity of RES along with thermal generators has been determined by considering total generation cost as an objective function. The proposed methodology is tested on the IEEE-30 system to ensure its usefulness. Obtained results show the effectiveness of WOA when compared with other algorithms like non-dominated sorting genetic algorithm (NSGA-II), grey wolf optimization (GWO) and particle swarm optimization-GWO (PSOGWO).
This document summarizes a research paper that proposes a new approach for solving the economic dispatch problem in power systems using a hybrid particle swarm optimization and simulated annealing algorithm. The paper introduces economic dispatch and describes previous solution methods. It then presents the new hybrid algorithm, which combines the global search capabilities of particle swarm optimization with the probabilistic jumping of simulated annealing to find high-quality solutions faster. The paper applies the method to test cases and finds it performs better than traditional and other computational techniques at determining low-cost generation schedules that satisfy operational constraints.
The document proposes a new approach for solving the economic dispatch problem in power systems using a hybrid particle swarm optimization and simulated annealing algorithm. It begins with introductions to economic dispatch and optimization techniques like particle swarm optimization and simulated annealing. It then describes the economic dispatch problem formulation, including the objective of minimizing generation cost while satisfying constraints. The document proposes a novel hybrid algorithm that combines the salient features of particle swarm optimization and simulated annealing to generate high-quality solutions efficiently. It presents the particle swarm optimization, simulated annealing and hybrid algorithms in detail. The effectiveness of the proposed approach is demonstrated through case studies on different power systems.
Study and Analysis of Nonlinear Constrained Components A Study of Plug-in Hyb...ijtsrd
Today transportation is one of the rapidly evolving technologies in the world. With the stringent mandatory emission regulations and high fuel prices, researchers and manufacturers are ever increasingly pushed to the frontiers of research in pursuit of alternative propulsion systems. Electrically propelled vehicles are one of the most promising solutions among all the other alternatives, as far as reliability, availability, feasibility and safety issues are concerned. However, the shortcomings of a fully electric vehicle in fulfilling all performance requirements make the electrification of the conventional engine powered vehicles in the form of a plug-in hybrid electric vehicle PHEV the most feasible propulsion systems. Sadia Andaleeb "Study and Analysis of Nonlinear Constrained Components (A Study of Plug-in Hybrid Electric Vehicle)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd20308.pdf
Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/20308/study-and-analysis-of-nonlinear-constrained-components-a-study-of-plug-in-hybrid-electric-vehicle/sadia-andaleeb
ENERGY MANAGEMENT SYSTEM IN MICROGRID: A REVIEWIRJET Journal
This document provides a review of energy management systems in microgrids. It discusses how energy management systems can help integrate renewable energy resources and reduce greenhouse gas emissions from fossil fuel power generation. The review classifies different approaches to energy management, including control strategies for emissions reduction, energy storage optimization techniques, and methods for reducing energy costs. It also examines demand response management strategies to encourage local power consumption from renewable sources. The document concludes by stating this review provides direction for future research in microgrid energy management.
Evolutionary algorithm solution for economic dispatch problemsIJECEIAES
A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints, these include the practical operation constraints of the generators (such as the forbidden working areas, nonlinear limits, and generation limits) that makes the calculation of the global optimal solutions of ED a difficult task. The proposed approach in this study was evaluated in the IEEE 30-Bus test-bed, the evaluation showed that the proposed FA-based approach performed optimally in comparison with the performance of the other existing optimizers, such as the traditional FA and particle swarm optimization. The results show the high performance of the modified firefly algorithm compared to the other methods.
IRJET- Comparison of GA and PSO Optimization Techniques to Optimal Planning o...IRJET Journal
This document presents a comparison of genetic algorithm (GA) and particle swarm optimization (PSO) techniques for optimally placing electric vehicle charging stations in a local distribution system. It describes using GA and PSO in MATLAB simulations to determine charging station locations that minimize real and reactive power losses. The results found that PSO requires fewer iterations and less time to achieve optimal solutions compared to GA, though GA may find solutions with slightly lower losses. Overall, both techniques provide effective methods for optimizing charging station placement to support electric vehicles.
Optimal Operation of Wind-thermal generation using differential evolutionIOSR Journals
This document presents an optimal operation model for a wind-thermal power generation system using differential evolution (DE). DE is an evolutionary algorithm inspired by biological evolution that can solve complex constrained optimization problems. The paper formulates the economic dispatch problem to minimize total generation cost of the wind and thermal plants subject to various constraints like power balance, generator limits, ramp rates, and valve point loading effects. Five different DE mutation strategies are analyzed for solving the wind-thermal economic dispatch problem on a test system with 10 thermal units. The results show that the best mutation strategy and control parameter values (mutation rate and crossover rate) depend on the problem and can significantly impact the solution quality and consistency obtained by the DE algorithm.
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...IJERA Editor
This Paper is an attempt to develop the expansion-planning algorithm using meta heuristics algorithms. Expansion Planning is always needed as the power demand is increasing every now and then. Thus for a better expansion planning the meta heuristic methods are needed. The cost efficient Expansion planning is desired in the proposed work. Recently distributed generation is widely researched to implement in future energy needs as it is pollution free and capability of installing it in rural places. In this paper, optimal distributed generation expansion planning with Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) for identifying the location, size and type of distributed generator for future demand is predicted with lowest cost as the constraints. Here the objective function is to minimize the total cost including installation and operating cost of the renewable DGs. MATLAB based `simulation using M-file program is used for the implementation and Indian distribution system is used for testing the results.
The document summarizes research on optimizing the design parameters of an asynchronous machine using genetic algorithms. It presents the objective as minimizing losses to improve efficiency. A genetic algorithm approach is used to optimize five induction motor equivalent circuit parameters as design variables while satisfying constraints like nominal slip and temperature rise. The algorithm evaluates losses as the objective function and converges to an optimal solution with improved efficiency and performance characteristics like higher starting torque compared to the initial design.
A hybrid non-dominated sorting genetic algorithm for a multi-objective deman...IJECEIAES
One of the most significant challenges facing optimization models for the demand-side management (DSM) is obtaining feasible solutions in a shorter time. In this paper, the DSM is formulated in a smart building as a linear constrained multi-objective optimization model to schedule both electrical and thermal loads over one day. Two objectives are considered, energy cost and discomfort caused by allowing flexibility of loads within an acceptable comfort range. To solve this problem, an integrative matheuristic is proposed by combining a multi-objective evolutionary algorithm as a master level with an exact solver as a slave level. To cope with the non-triviality of feasible solutions representation and NP-hardness of our optimization model, in this approach discrete decision variables are encoded as partial chromosomes and the continuous decision variables are determined optimally by an exact solver. This matheuristic is relevant for dealing with the constraints of our optimization model. To validate the performance of our approach, a number of simulations are performed and compared with the goal programming under various scenarios of cold and hot weather conditions. It turns out that our approach outperforms the goal programming with respect to some comparison metrics including the hypervolume difference, epsilon indicator, number of the Pareto solutions found, and computational time metrics.
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Security Constraint Unit Commitment Considering Line and Unit Contingencies-p...IJAPEJOURNAL
This summary provides the key details about the document in 3 sentences:
The document presents a new approach for security constrained unit commitment that considers both generator and transmission line contingencies using an incidence matrix methodology. It formulates the security constrained unit commitment problem and proposes modeling the optimal power flow using an incidence matrix to overcome challenges of admittance matrix based methods. The methodology allows easier modeling of multiple contingencies without changes to the network topology.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Renewable energy based dynamic tariff system for domestic load managementnooriasukmaningtyas
To deal with the present power-scenario, this paper proposes a model of an advanced energy management system, which tries to achieve peak clipping, peak to average ratio reduction and cost reduction based on effective utilization of distributed generations. This helps to manage conventional loads based on flexible tariff system. The main contribution of this work is the development of three-part dynamic tariff system on the basis of time of utilizing power, available renewable energy sources (RES) and consumers’ load profile. This incorporates consumers’ choice to suitably select for either consuming power from conventional energy sources and/or renewable energy sources during peak or off-peak hours. To validate the efficiency of the proposed model we have comparatively evaluated the model performance with existing optimization techniques using genetic algorithm and particle swarm optimization. A new optimization technique, hybrid greedy particle swarm optimization has been proposed which is based on the two aforementioned techniques. It is found that the proposed model is superior with the improved tariff scheme when subjected to load management and consumers’ financial benefit. This work leads to maintain a healthy relationship between the utility sectors and the consumers, thereby making the existing grid more reliable, robust, flexible yet cost effective.
Brownfield Sites as Catalysts for Sustainable Urban Regenerationand the Deman...IEREK Press
Almost two decades today, the topic of brownfields has extensively been researched in urban sociology, urban planning, and human geography, and numerous Western-Centric studies have linked the redevelopment of the abandoned, contaminated, vacant or derelict sites to sustainable urban regeneration and achieving smart cities and sustainability goals in general. Yet, until this day, the concept has received little academic and practical attention in Middle Eastern contexts. Western contexts on the other hand including Europe, UK and USA continue to offer unique perspectives on approaching brownfields in ways that reduce the alarming spatial cluttering and address socio-spatial disparities and spatial segregation in addition to achieving economic and environmental goals, and similar to the global scene, brownfield sites make a large portion of the post-industrial city of Amman, the capital of Jordan. However, with the lack of a systematic definition for the urban phenomenon objectives, methods to identifying potential brownfield sites and evaluating the prioritisation of their redevelopment that takes into consideration context particularities, and with the absence of participative approaches that include the local community in the decision-making regarding these spaces, city planners fail to include the increasingly growing number of brownfield site that proliferate their cities in the urban planning practice. Through the examination of literature discussions on objectives, approaches, classification systems, methodologies, assessment and evaluation tools for the support of design and prioritising decisions for brownfield regeneration indifferent contexts, and through looking at the numerous potential alternatives for brownfield sites regeneration these contexts highlight, this paper bids to emphasise the importance of developing context specific, localised tools tailored for the Middle Eastern case. Building on the above, this paper identifies five potential brownfield typologies in the context of Amman; (1)residual planning outcomes; (2) discontinued mines and quarries; (3) unfinished mega-projects; (4) contaminated and hazardous sites, and; (5) miscellaneous abandoned sites and buildings, and ends on the note that looking at the increasing demand to meeting smart growth and sustainability needs, these urban landscapes may function as catalysts for achieving comprehensive sustainable urban regeneration.
Natural Urban Heritage and Preservation Policies: the Case of Kyoto’s Waterways.IEREK Press
The value of natural heritage within urban areas is nowadays gaining recognition, but there are still no clear reference frameworks to confront the complexities of their management. In this discussion, the challenges of the association of historical preservation and urban nature are explored through the analysis of the management of Kyoto’s waterways. The conflicts caused by the rapid modernization of Japan at the end of 19thcentury find in Kyoto a remarkable expression in the tensions between renovation and conservation, providing a fertile frame for discussion. Relevant achievements and shortcomings of Kyoto ́s experience are here analyzed, considering how the preservation of historic landscapes affected the protection of urban rivers, the relationship between sustainability and heritage, and the new environmentally aware approaches to river improvement.
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The concept of the energy management system, developed in this work, is to determine the optimal combination of energy from several generation sources and to schedule their commitment, while optimizing the cost of purchased energy, power losses and voltage drops. In order to achieve these objectives, the non-dominated sorting genetic algorithm II (NSGA-II) was modified and applied to an IEEE 33-bus test network containing 10 photovoltaic power plants and 4 battery energy storage systems placed at optimal points in the network. To evaluate the system performance, the resolution was performed under several test conditions. Optimal Pareto solutions were classified using three decision-making methods, namely analytic hierarchy process (AHP), technique for order preference by similarity to ideal solution (TOPSIS) and entropy-TOPSIS. The simulation results obtained by NSGA-II and classified using entropy-TOPSIS showed a significant and considerable reduction in terms of purchased energy cost, power losses and voltage drops while successfully meeting all constraints. In addition, the diversity of the results proved once again the robustness and effectiveness of the algorithm. A graphical interface was also developed to display all the decisions made by the algorithm, and all other information such as the states of power systems, voltage profiles, alarms, and history.
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This document proposes an energy management system for a smart microgrid using a multi-objective grey wolf optimization algorithm. The goals are to maximize the use of local renewable energy generation, minimize consumer energy costs, and reduce greenhouse gas emissions. It describes energy controllers that would manage energy sharing between providers and customers. The multi-objective grey wolf optimization technique is said to provide faster optimization than other methods. Simulation results reportedly show reductions in both pollution and energy consumption costs with this approach.
Economic dispatch by optimization techniquesIJECEIAES
The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic approaches are introduced, the BA and ALOA. A rigorous stochastically developmental computing strategy focused on the action and intellect of ant lions is an ALOA. The ALOA imitates ant lions' hunting process. The introduction of a numerical description of its biological actions for the solution of ED in the power framework. These algorithms are applied to two systems: a small scale three generator system and a large scale six generator. Results show were compared on the metrics of convergence rate, cost, and average run time that the ALOA and BA are suitable for economic dispatch studies which is clear in the comparison set with other algorithms. Both of these algorithms are tested on IEEE-30 bus reliability test system.
A new approach to the solution of economic dispatch using particle Swarm opt...ijcsa
This document presents a new approach to solving the economic dispatch problem using particle swarm optimization combined with simulated annealing (PSO-SA). The economic dispatch problem aims to minimize the total generation cost while satisfying constraints like power demand and generator limits. Previous solutions had limitations. The authors propose using PSO-SA to find high quality solutions more efficiently. PSO is able to find global optima but can get trapped in local optima. SA helps avoid this through probabilistic jumping. The authors combine PSO and SA techniques to leverage their benefits while overcoming individual limitations. They test the PSO-SA method on three generator systems and find it provides better results than traditional and other computational methods.
IRJET- Comprehensive Analysis on Optimal Allocation and Sizing of Distributed...IRJET Journal
This document summarizes a research paper that investigates the optimal allocation and sizing of distributed generation (DG) units in a distribution system using Particle Swarm Optimization (PSO). The objective is to minimize voltage deviation and total power loss. A 33-bus distribution network is used as a case study. The results show that allocating 3 DG units at buses 18, 14, and 17 with sizes of 1.7154 MW, 0.1908 MW, and 1.6159 MW respectively reduces voltage deviation at all buses and total power loss by 89.83%. The PSO technique effectively finds the optimal DG locations and sizes to improve the voltage profile and minimize losses in the distribution network.
Optimal power flow with distributed energy sources using whale optimization a...IJECEIAES
Renewable energy generation is increasingly attractive since it is non-polluting and viable. Recently, the technical and economic performance of power system networks has been enhanced by integrating renewable energy sources (RES). This work focuses on the size of solar and wind production by replacing the thermal generation to decrease cost and losses on a big electrical power system. The Weibull and Lognormal probability density functions are used to calculate the deliverable power of wind and solar energy, to be integrated into the power system. Due to the uncertain and intermittent conditions of these sources, their integration complicates the optimal power flow problem. This paper proposes an optimal power flow (OPF) using the whale optimization algorithm (WOA), to solve for the stochastic wind and solar power integrated power system. In this paper, the ideal capacity of RES along with thermal generators has been determined by considering total generation cost as an objective function. The proposed methodology is tested on the IEEE-30 system to ensure its usefulness. Obtained results show the effectiveness of WOA when compared with other algorithms like non-dominated sorting genetic algorithm (NSGA-II), grey wolf optimization (GWO) and particle swarm optimization-GWO (PSOGWO).
This document summarizes a research paper that proposes a new approach for solving the economic dispatch problem in power systems using a hybrid particle swarm optimization and simulated annealing algorithm. The paper introduces economic dispatch and describes previous solution methods. It then presents the new hybrid algorithm, which combines the global search capabilities of particle swarm optimization with the probabilistic jumping of simulated annealing to find high-quality solutions faster. The paper applies the method to test cases and finds it performs better than traditional and other computational techniques at determining low-cost generation schedules that satisfy operational constraints.
The document proposes a new approach for solving the economic dispatch problem in power systems using a hybrid particle swarm optimization and simulated annealing algorithm. It begins with introductions to economic dispatch and optimization techniques like particle swarm optimization and simulated annealing. It then describes the economic dispatch problem formulation, including the objective of minimizing generation cost while satisfying constraints. The document proposes a novel hybrid algorithm that combines the salient features of particle swarm optimization and simulated annealing to generate high-quality solutions efficiently. It presents the particle swarm optimization, simulated annealing and hybrid algorithms in detail. The effectiveness of the proposed approach is demonstrated through case studies on different power systems.
Study and Analysis of Nonlinear Constrained Components A Study of Plug-in Hyb...ijtsrd
Today transportation is one of the rapidly evolving technologies in the world. With the stringent mandatory emission regulations and high fuel prices, researchers and manufacturers are ever increasingly pushed to the frontiers of research in pursuit of alternative propulsion systems. Electrically propelled vehicles are one of the most promising solutions among all the other alternatives, as far as reliability, availability, feasibility and safety issues are concerned. However, the shortcomings of a fully electric vehicle in fulfilling all performance requirements make the electrification of the conventional engine powered vehicles in the form of a plug-in hybrid electric vehicle PHEV the most feasible propulsion systems. Sadia Andaleeb "Study and Analysis of Nonlinear Constrained Components (A Study of Plug-in Hybrid Electric Vehicle)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd20308.pdf
Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/20308/study-and-analysis-of-nonlinear-constrained-components-a-study-of-plug-in-hybrid-electric-vehicle/sadia-andaleeb
ENERGY MANAGEMENT SYSTEM IN MICROGRID: A REVIEWIRJET Journal
This document provides a review of energy management systems in microgrids. It discusses how energy management systems can help integrate renewable energy resources and reduce greenhouse gas emissions from fossil fuel power generation. The review classifies different approaches to energy management, including control strategies for emissions reduction, energy storage optimization techniques, and methods for reducing energy costs. It also examines demand response management strategies to encourage local power consumption from renewable sources. The document concludes by stating this review provides direction for future research in microgrid energy management.
Evolutionary algorithm solution for economic dispatch problemsIJECEIAES
A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints, these include the practical operation constraints of the generators (such as the forbidden working areas, nonlinear limits, and generation limits) that makes the calculation of the global optimal solutions of ED a difficult task. The proposed approach in this study was evaluated in the IEEE 30-Bus test-bed, the evaluation showed that the proposed FA-based approach performed optimally in comparison with the performance of the other existing optimizers, such as the traditional FA and particle swarm optimization. The results show the high performance of the modified firefly algorithm compared to the other methods.
IRJET- Comparison of GA and PSO Optimization Techniques to Optimal Planning o...IRJET Journal
This document presents a comparison of genetic algorithm (GA) and particle swarm optimization (PSO) techniques for optimally placing electric vehicle charging stations in a local distribution system. It describes using GA and PSO in MATLAB simulations to determine charging station locations that minimize real and reactive power losses. The results found that PSO requires fewer iterations and less time to achieve optimal solutions compared to GA, though GA may find solutions with slightly lower losses. Overall, both techniques provide effective methods for optimizing charging station placement to support electric vehicles.
Optimal Operation of Wind-thermal generation using differential evolutionIOSR Journals
This document presents an optimal operation model for a wind-thermal power generation system using differential evolution (DE). DE is an evolutionary algorithm inspired by biological evolution that can solve complex constrained optimization problems. The paper formulates the economic dispatch problem to minimize total generation cost of the wind and thermal plants subject to various constraints like power balance, generator limits, ramp rates, and valve point loading effects. Five different DE mutation strategies are analyzed for solving the wind-thermal economic dispatch problem on a test system with 10 thermal units. The results show that the best mutation strategy and control parameter values (mutation rate and crossover rate) depend on the problem and can significantly impact the solution quality and consistency obtained by the DE algorithm.
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...IJERA Editor
This Paper is an attempt to develop the expansion-planning algorithm using meta heuristics algorithms. Expansion Planning is always needed as the power demand is increasing every now and then. Thus for a better expansion planning the meta heuristic methods are needed. The cost efficient Expansion planning is desired in the proposed work. Recently distributed generation is widely researched to implement in future energy needs as it is pollution free and capability of installing it in rural places. In this paper, optimal distributed generation expansion planning with Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) for identifying the location, size and type of distributed generator for future demand is predicted with lowest cost as the constraints. Here the objective function is to minimize the total cost including installation and operating cost of the renewable DGs. MATLAB based `simulation using M-file program is used for the implementation and Indian distribution system is used for testing the results.
The document summarizes research on optimizing the design parameters of an asynchronous machine using genetic algorithms. It presents the objective as minimizing losses to improve efficiency. A genetic algorithm approach is used to optimize five induction motor equivalent circuit parameters as design variables while satisfying constraints like nominal slip and temperature rise. The algorithm evaluates losses as the objective function and converges to an optimal solution with improved efficiency and performance characteristics like higher starting torque compared to the initial design.
A hybrid non-dominated sorting genetic algorithm for a multi-objective deman...IJECEIAES
One of the most significant challenges facing optimization models for the demand-side management (DSM) is obtaining feasible solutions in a shorter time. In this paper, the DSM is formulated in a smart building as a linear constrained multi-objective optimization model to schedule both electrical and thermal loads over one day. Two objectives are considered, energy cost and discomfort caused by allowing flexibility of loads within an acceptable comfort range. To solve this problem, an integrative matheuristic is proposed by combining a multi-objective evolutionary algorithm as a master level with an exact solver as a slave level. To cope with the non-triviality of feasible solutions representation and NP-hardness of our optimization model, in this approach discrete decision variables are encoded as partial chromosomes and the continuous decision variables are determined optimally by an exact solver. This matheuristic is relevant for dealing with the constraints of our optimization model. To validate the performance of our approach, a number of simulations are performed and compared with the goal programming under various scenarios of cold and hot weather conditions. It turns out that our approach outperforms the goal programming with respect to some comparison metrics including the hypervolume difference, epsilon indicator, number of the Pareto solutions found, and computational time metrics.
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Security Constraint Unit Commitment Considering Line and Unit Contingencies-p...IJAPEJOURNAL
This summary provides the key details about the document in 3 sentences:
The document presents a new approach for security constrained unit commitment that considers both generator and transmission line contingencies using an incidence matrix methodology. It formulates the security constrained unit commitment problem and proposes modeling the optimal power flow using an incidence matrix to overcome challenges of admittance matrix based methods. The methodology allows easier modeling of multiple contingencies without changes to the network topology.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Renewable energy based dynamic tariff system for domestic load managementnooriasukmaningtyas
To deal with the present power-scenario, this paper proposes a model of an advanced energy management system, which tries to achieve peak clipping, peak to average ratio reduction and cost reduction based on effective utilization of distributed generations. This helps to manage conventional loads based on flexible tariff system. The main contribution of this work is the development of three-part dynamic tariff system on the basis of time of utilizing power, available renewable energy sources (RES) and consumers’ load profile. This incorporates consumers’ choice to suitably select for either consuming power from conventional energy sources and/or renewable energy sources during peak or off-peak hours. To validate the efficiency of the proposed model we have comparatively evaluated the model performance with existing optimization techniques using genetic algorithm and particle swarm optimization. A new optimization technique, hybrid greedy particle swarm optimization has been proposed which is based on the two aforementioned techniques. It is found that the proposed model is superior with the improved tariff scheme when subjected to load management and consumers’ financial benefit. This work leads to maintain a healthy relationship between the utility sectors and the consumers, thereby making the existing grid more reliable, robust, flexible yet cost effective.
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Brownfield Sites as Catalysts for Sustainable Urban Regenerationand the Deman...IEREK Press
Almost two decades today, the topic of brownfields has extensively been researched in urban sociology, urban planning, and human geography, and numerous Western-Centric studies have linked the redevelopment of the abandoned, contaminated, vacant or derelict sites to sustainable urban regeneration and achieving smart cities and sustainability goals in general. Yet, until this day, the concept has received little academic and practical attention in Middle Eastern contexts. Western contexts on the other hand including Europe, UK and USA continue to offer unique perspectives on approaching brownfields in ways that reduce the alarming spatial cluttering and address socio-spatial disparities and spatial segregation in addition to achieving economic and environmental goals, and similar to the global scene, brownfield sites make a large portion of the post-industrial city of Amman, the capital of Jordan. However, with the lack of a systematic definition for the urban phenomenon objectives, methods to identifying potential brownfield sites and evaluating the prioritisation of their redevelopment that takes into consideration context particularities, and with the absence of participative approaches that include the local community in the decision-making regarding these spaces, city planners fail to include the increasingly growing number of brownfield site that proliferate their cities in the urban planning practice. Through the examination of literature discussions on objectives, approaches, classification systems, methodologies, assessment and evaluation tools for the support of design and prioritising decisions for brownfield regeneration indifferent contexts, and through looking at the numerous potential alternatives for brownfield sites regeneration these contexts highlight, this paper bids to emphasise the importance of developing context specific, localised tools tailored for the Middle Eastern case. Building on the above, this paper identifies five potential brownfield typologies in the context of Amman; (1)residual planning outcomes; (2) discontinued mines and quarries; (3) unfinished mega-projects; (4) contaminated and hazardous sites, and; (5) miscellaneous abandoned sites and buildings, and ends on the note that looking at the increasing demand to meeting smart growth and sustainability needs, these urban landscapes may function as catalysts for achieving comprehensive sustainable urban regeneration.
Natural Urban Heritage and Preservation Policies: the Case of Kyoto’s Waterways.IEREK Press
The value of natural heritage within urban areas is nowadays gaining recognition, but there are still no clear reference frameworks to confront the complexities of their management. In this discussion, the challenges of the association of historical preservation and urban nature are explored through the analysis of the management of Kyoto’s waterways. The conflicts caused by the rapid modernization of Japan at the end of 19thcentury find in Kyoto a remarkable expression in the tensions between renovation and conservation, providing a fertile frame for discussion. Relevant achievements and shortcomings of Kyoto ́s experience are here analyzed, considering how the preservation of historic landscapes affected the protection of urban rivers, the relationship between sustainability and heritage, and the new environmentally aware approaches to river improvement.
Urban Public Space Axis Rector of Green Infrastructure in the Current City of...IEREK Press
The current city calls for the reconsideration of a close relationship between gray infrastructure and public spaces, understanding the infrastructure as a set of items, equipment, or services required for the functioning of a country, a City. Ambato, Ecuador, is a current intermediate city, has less than 1% of the urban surface with use of public green spaces, which represents a figure below the 9m2/ hab., recommended by OMS. The aim of this paper was to identify urban public spaces that switches of green infrastructure in the city today, applying a methodology of qualitative studies. With an exploratory descriptive level analysis, in three stages, stage of theoretical foundation product of a review of the existing literature, which is the theoretical support of the relationship gray infrastructure public spaces equal to green infrastructure. Subsequent to this case study, discussed with criteria aimed at green infrastructure and in the public spaces of the study area. Finally, after processing and analysis of the results, we provide conclusions for urban public space as a definition of the green infrastructure of the current city of Latin America; in the latter, the focus is to support this article.
Revitalization Strategy for Historic Core of AhmedabadIEREK Press
In India, dense historic urban settlements were developed with the intention of provision of spaces for adequate engagement of the people. Public squares and streets became important places of interaction. ‘Historic core,’ especially had public spaces meant for various socioeconomic groups. Ahmedabad city is a blend of a harmonious past and a vivacious present. Number of historical and architecturally important buildings were built during Muslim and Moghul rules. One of the first built structures within the walled city is the Bhadra fort, a citadel founded by sultan Ahmed Shah in 1411 with a huge public square in front, developed for purpose of procession and gathering. This Bhadra precinct went through various layers of transformation in different eras and now have become vulnerable due to congestion and encroachment. Though, a need for intervention was felt to bring back the lost vitality of the Bhadra precinct, it was realized that a comprehensive approach would be the necessity. Conservation and sensitive development approach was taken to tackle this problem through pedestrianization of the Bhadra precinct, rerouting of traffic and restoration of Bhadra fort. Larger level traffic and parking issues were also considered be-yond the site. Alternative use of Bhadra fort as tourist information center was considered. Urban design guidelines were proposed for harmonious development in the surrounding area. This proposal was considered for funding under Jawaharlal Nehru National Urban Renewal Mission(JnNURM)and was implemented. Many issues were faced during implementation of Bhadra project due to contextualization of informal commercial, religious and other cultural activities. Political, social and administrative factors also played immense role in implementation of proposal. Now since Ahmedabad has achieved the status of World Heritage City through UNESCO certification further implementation of this project will be relatively easy due to envisaged strong political and administrative support.
Unlocking the Potentials of Urban Architecture in Enhancing theQuality of Urb...IEREK Press
Currently more than half of world population are living in cities, while world is witnessing a rapid urbanization process particularly in cities of the developing and emerging countries, where urban poverty areas (UPA) with low quality of urban life (QUL) and lack of the usual urban spaces are the most significant urban phenomena that characterized those cities. In such an urban context there is a need for an efficient tool that contributes positively to the enhancement of the QUL, meanwhile to provide the best use of the rare vacant lands. This study argues that urban architecture as a design field offers a distinctive approach to a special type of buildings made for an urban setting, thus it can enhance the QUL in UPA through community projects. The study is based on an analytical study of selected cases of community projects in UPA that represents examples of how urban architecture through its potentials has a positive impact on its urban context, notably through community projects that strongly linked to real community needs. The results showed that urban architecture as a design approach for community projects have multiple roles that boost the socio-economic daily life, as well it supports various environmental issues towards better QUL.
The Sinkhole Occurrence Risk Mitigation in Urban Areas for the Historic Salt ...IEREK Press
The present research focuses on the definition of a novel methodology for sinkhole risk assessment above shallow salt mines. The research were carried out on the area above the Wieliczka salt mine, a World Heritage site. The study of vertical stresses on the basis of a theoretical state of rock mass deformation in the area of test chambers was performed. Furthermore, the risk of chamber collapse due to ventricular stress exceeding the limit specified in the zone were calculated based on the arch pressure theory. The final stage of the research consists of spatial analysis that leading to the identification of chambers potentially influenced by other risk factors. The research shown in the article strongly suggests that combined spatial analysis with geotechnical analysis may lead to reliable sinkhole risk assessment methodology.
In Search of a Tool to Support Planning Inside Large Cities: the SustaIn-LED ...IEREK Press
The aim of the present study is to investigate the linkages between local economic development, innovation, and environmental sustainability inside urban areas. Can innovation affect the improvement of the quality of life inside urban areas? This research question comes from the consideration that usually innovation and growth in general are considered sources of conflict in affecting the livability of large cities. The objective of the paper is to design a model — the “SustaIn-Led” - to connect levels of environmental sustainability, quality of life, and economic development inside metropolitan areas, taking into account also innovation processes, activated by the innovation policies and by the knowledge economy. The study takes in consideration the 53 largest United States metropolitan areas with a population over 1 million, with a time series from the years 2000 through 2015.This has been done because of a two-fold reason: (1) the US among high-income countries is the one with the highest number of universities, patents, and citations; (2) several studies have shown that innovation occurs in large cities. The first part of the present study has carried out the identification of the variables to represent and significantly explain the phenomena – local economic development, innovation, and environmental sustainability – linked to the design of the SustaIn-LED model. Environmental sustainability in urban areas in this paper is represented by means of the Air Quality Index (AQI),while the number of workers synthetically quantifies local economic development. Correlation and multiple regression analyses are conducted in order to examine the relationship between the three main indicators. The multiple regressions for the year 2015 produced a low p-value, indicating that the predictors are significant in the regression analysis. Similar results of p-value are shown in all the years from 2000 to 2013. For 2015, the results showed that part of the variance in the measure of total workers of the metropolitan areas could be predicted by measures of innovation and air quality. Higher R2values have been registered for the years from 2000 through2013.The development of the SustaIn-LED model could be utilized in urban regeneration processes to help in the design of new urban planning policies inside large cities by means of a better comprehension of environmental and economic implications caused by the implementation of innovation policies.
Estimation of Coating Materials Contribution to the TVOCsEmissions of Wood Fl...IEREK Press
Based on the increasing concern about the exposure to volatile organic compounds (VOCs) from indoor finishing materials, industrial companies are called to meet the growing demand for more sustainable products. Recently, most designers and consumers have more environmental considerations while selecting the finishing materials. These considerations are related to the VOCs content of the finishing material itself regardless of its coating layers. Nowadays, interior wood coatings are commonly applied to large surfaces (ceilings, walls, floors) and many types of furnishing, leading to a high loading factor (surface-to-volume ratio). These coatings might contribute significantly to the VOCs emissions due to repeatedly and periodically use during maintenance, remodeling, and renovation of interior spaces. The aim of this study is to estimate the wood coating materials contribution to the TVOCs emissions of wood product in the indoor environment to shed light on the importance of comprehensive analysis of wood material with all treatment coatings. So, a small interior space with controlled temperature, relative humidity, and air exchange rate was simulated using IA-Quest program to investigate the influence of three wood coating materials; stain, wax, and varnish which were applied to an area of natural hardwood Oak floor. The TVOCs emission data resulted from the different coated wood floor was compared with VOCs emissions caused by the natural wood floor to find out the coating material contribution in TVOCs emissions of a wood flooring material
Sustainable Park Landscaping as an Approach for theDevelopment of the Built E...IEREK Press
Implementing sustainable principles when landscaping parks is vital for the development of the built environment, and should take into account environmental, social, economic, and cultural aspects, in order to eliminate conflict between developmental requirements, and the need to preserve cultural and natural resources. This paper reviews the guidelines that should be considered for current and future sustainable parks in regions with a moderate climate, in order to ensure that they incorporate ecotourism, cost effective operation and maintenance, a clean environment, the promotion of renewable energy, and resource preservation. A number of parks, located in moderate climate zones, are studied in terms of aspects such as their location, topography, operation, and landscaping characteristics, to demonstrate the prevailing normative values that can be applied to sustainable park design. Prince Meshari Park, in Al-Baha city, Saudi Arabia, is employed as a case study for applying all of the guidelines proposed in this investigation, and to highlight some of their merits and limitations in terms of the current situation of the park.
Load Shifting Assessment of Residential Heat Pump System in JapanIEREK Press
With the economic growth and increasing requirement of indoor thermal comfort, the load of building sector presents a greater variability. This paper aims at analyzing the energy consumption characteristics and influencing factors of the residential heat pump system. Firstly, we selected residential households as investigated objective in Kitakyushu, Japan, and compared the energy saving performances of heat supply systems between heat pump and natural gas boiler. The results were based on real measured residential load during winter period, and calculated the cost saving performance of residential heat pump system compared with traditional natural gas boiler. We also did a survey of residential occupation behavior for the 12 selected residential customers. The result indicated that there was low relationship between power consumption and occupation hours, and the number of family members had a significant impact on the power consumption. The results indicate that residential heat pump system presented promising energy saving and cost reduction potential
A Model Proposed for the Prediction of Future Sustainable Residence Specifica...IEREK Press
In Egypt, people are unable to determine the qualities of appropriate residence that achieves quality and occupant satisfaction, and contributes to sustainability of residential conglomerations. In general, developing countries lack housing information which can be used to enhance quality of residence. Also, the methods of assessing and identifying the appropriate criteria for future residence quality remain traditional ones that cannot address the multiple, conflicting, overlapping aspects to reach a good decision. This calls for using the Analytical Network Process (ANP), an effective tool for specifying the relative importance of all factors impacting a specific issue for making an appropriate residential decision. In addition, this method provides results for the decision element impacts network within the decision structure; thus contributing to more understanding of the mechanisms and requirements of residence selection. The proposed decision structure comprises a two-level network: main clusters, main elements, and sub-elements included in the demographic characteristics group, the residence criteria group, the demand parameters group, the supply parameters group, the residence specifications group, and the alternatives group which representing, in total, the decision and specifying the percentage needed for each housing level. Results of the model showed complete capacity in smoothly addressing complexities and overlapping in the decision structure. The decision structure showed that 52% chose luxury residence, 28% chose middle-class residence, and 19.5% chose the economic residence. Mechanisms of decision making were analyzed; particularly in terms of relationship to demographic characteristics and residence specifications. Also, the importance and impact of demand / supply parameters in reaching decision were analyzed
Development of an Open-Source Water Consumption Meter for HousingIEREK Press
This article reports on the project "Design and development of water and gas P.L. measurement devices in the housing: an approach to sustainable consumption in Mexico", prepared at the Metropolitan Autonomous University in the Department of the Environment, whose objective was to develop a device to measure water consumption in the housing, which allows users to know their spending and can make decisions in favor of efficiency through the reduction of water use in household activities. The meter is made up of open source, programmable or reconfigurable software, which receives the signal from a water flow sensor and a casing designed to contain the hardware and facilitate the user's installation. Both the hardware and the casing can be purchased, downloaded, manufactured and assembled at home (Do It Yourself). As specific results were obtained: hardware programming and housing design and as a final result: the assembly of the functional prototype with which measurements of water consumption were made in a housing in Mexico. With this work we conclude that through the development of new accessible and common measurement technologies for the users of a house, it will be possible to promote efficiency in the use of natural resources in cities, increasing availability and promoting a more sustainable urban development.
Multi-Scale Assessment of Urban Gardens as Constructed Habitats for Biodivers...IEREK Press
Biodiversity in arid urban environments depends upon habitat formation that balances both bioclimatic and biophysical environment needs. There is the potential for urban gardens to establish symbiotic ecosystem services from microhabitat formation that collectively form an assemblage of ecological patches to connect a diverse range of flora and fauna, and establish community driven nursery and seed collection initiatives. This study of urban garden habitats situated within a new urban district of Jeddah Saudi. The analysis concentrates on the ability of garden spatial formations to construct a heterogeneous spatial morphology of sub-patch within the larger urban landscape patch. Patch and subpatch formations are examined based on the criteria of (I) assemblage of the spatial habitat (characterized by shape and spatial organization); (II) integration of spatial, functional and vegetation plantation patterns; (III) connectivity. Findings reveal that garden layout is structured by the integration and layering of plant types to generate cool understory habitat with seedling establishment, and water conservation. Designed layout of the garden as a spatial pattern is augmented with a range of microclimate mediators to dim solar exposure within the plantation habitat. A strong heterogeneity in plant formations and combinations is seen to dominant the garden formations.
Architectural Education for Sustainable Urban RegenerationIEREK Press
Urban regeneration is one of the important agendas of Turkey as a developing country. Rapid urbanization problems have been causing vital social and economic problems together with physical and spatial ones especially in big cities of Turkey. Thus, national and local governments handled urban regeneration as a practical method for solution of these problems. However, they unfortunately don’t implement urban regeneration according to its real requirements. Instead, this multi-dimensional and complex process is seen as a pull down and built up operation. Considering this situation and being in awareness of the responsibilities of architects throughout urban regeneration process, the authors think that urban regeneration should be discussed in the scope of architectural education. This paper presents the purpose, the process and the products of an undergraduate architectural design studio that was undertaken at Bursa Uludağ University, Faculty of Architecture. The architectural and urban design projects of the students of which aim was to offer a livable and sustainable mixed used living environments are discussed together with their conceptual backgrounds. Putting stress on the differences between theory and practice, the conclusion introduces a critical evaluation of urban regeneration and sustainable housing concepts in Turkey.
Typology and Solar Gain Analysis: Vernacular Courtyard Houses of Tabriz, IranIEREK Press
The study presents the results of typological analysis and simulation modeling analysis of traditional courtyard residential houses in the cold semi-arid climate of Iran. The purpose of the research has been to analyze and evaluate traditional passive environmental strategies and their elements to provide implications for the design of sustainable residential buildings in contemporary time. Five existing traditional courtyard houses in the city of Tabriz, Iran, are used as case-studies to analyze the typology and the solar zoning conditions and to develop simulation models. The Ecotect simulation program is used to calculate the solar gains of the buildings and to analyze the effectiveness of the natural passive systems along with native design strategies in terms of potential solar gains of main and secondary living spaces. However, in the vernacular, not only the awareness of the climatic and topological considerations is important, but also the values, rituals, and beliefs that shape the design of the dwellings need to be considered. The research is based on the hypothesis that vernacular buildings (courtyard houses) of Iran have been environmentally sustainable structures. However, an important challenge of the study has been to avoid the technological bias and to consider the cultural and social aspects and embodiment of the studied houses, as well. The study also addresses the potential short comings that limit the reliability of Iranian vernacular architecture at present in order to arrive at a more holistic understanding of the sustainability of the vernacular architecture in the country.
Lessons Learned from the First Passivhaus Building in QatarIEREK Press
Energy efficient models have become the path to reduce energy consumption and Greenhouse gas emissions in the built environment in many developed countries. According to the Energy Performance of Buildings Directive (EPBD), new buildings constructed within the European Union (EU) countries are expected to be nearly zero energy buildings (nZEBs) by 2020, while new public buildings are expected to adhere to this target by 2018. The Passivhaus approach has been identified by several researchers as a possible roadmap to achieve nZEBs. The meticulous engineering and high standards of the Passivhaus building fabric, in addition to the high comfort levels, are the main reasons behind the success and widespread of the standard. Recently, in 2013 the Passivhaus principles have been applied to an experimental residential project in the hot and arid climate of Qatar. The project is composed of two identical buildings, one built according to the Passivhaus standard and the other according to normal practices in the country. The thermal performance and comfort levels of both buildings were assessed through dynamic simulation and on-site measurements. Results indicated that at least 50% reduction in annual operational energy, water consumption, and CO2 emissions were achieved in the Passivhaus model in comparison to the standard model. This paper aims to highlight the lessons learned through the Passivhaus project; first by exhibiting the Passivhaus criteria that have been met, second by showcasing the outcomes of the project, and third by displaying the barriers and difficulties that have been associated with building according to the standard in Qatar. Finally, recommendations and general guidelines are suggested towards a possible adoption of the Passivhaus standard in Qatar and the Gulf Cooperation Council (GCC) countries
Optimal Sizing and Design of Isolated Micro-Grid systemsIEREK Press
Micro-grid and standalone schemes are emerging as a viable mixed source of electricity due to interconnected costly central power plants and associated faults as well as brownouts and blackouts in additions to costly fuels. Micro-Grid (MG) is gaining very importance to avoid or decrease these problems. The objective of this paper is to design an optimal sizing and energy management scheme of an isolated MG. The MG is suggested to supply load located in El-shorouk Academy, Egypt between 30.119 latitudes and 31.605 longitudes. The components of the MG are selected and designed for achieving minimum Total Investment Cost (TIC) with CO2 emissions limitations. This is accomplished by a search and optimization MATLAB code used with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) techniques. The use of Diesel Generators (DGs) is minimized by limiting the gaseous CO2 emissions as per targeted allowable amount. A comparison is accomplished for investigating the CO2 emissions constraints effects on the TIC in $/year and annual cost of energy in $/kWh. The obtained results verified and demonstrated that the designed MG configuration scheme is able to feed the energy entailed by the suggested load cost effectively and environmental friendly.
Regenerative Mobility: Disruption and Urban EvolutionIEREK Press
Mobility plays an important role in the cities by enabling people to carry out the most varied activities across the territory, as well as to ensure the city fully function. In addition, analogies to the human organism can be made by this urban dynamic, looking for solutions to specific issues. Moreover, this paper has been based by the premise that phenomena and urban elements could be conceptualized, explained and transformed from contemporary and innovative approaches applied in the medical field. For this reason, this paper aims to develop and present a new concept associated with urban mobility, based on the principles of regenerative medicine: the Regenerative Mobility, a concept with disruptive and evolutionary purposes. Furthermore, the structure of this paper is summarized by the introduction which contextualizes the theme, presents and characterizes the techniques used in the research. Additionally, the following chapters explore essential aspects of the city, explaining why it needs a mobility change and new concepts. Therefore, the concept of Regenerative Mobility is presented as a potential of mobility and cities improvement, followed by pragmatic cases, capable of illustrating some of its principles.
Unlocking the Potentials of Urban Architecture in Enhancing the Quality of Ur...IEREK Press
Currently more than half of world population are living in cities, while world is witnessing a rapid urbanization process particularly in cities of the developing and emerging countries, where urban poverty areas (UPA) with low quality of urban life (QUL) and lack of the usual urban spaces are the most significant urban phenomena that characterized those cities. In such an urban context there is a need for an efficient tool that contributes positively to the enhancement of the QUL, meanwhile to provide the best use of the rare vacant lands. This study argues that urban architecture as a design field offers a distinctive approach to a special type of buildings made for an urban setting, thus it can enhance the QUL in UPA through community projects. The study is based on an analytical study of selected cases of community projects in UPA that represents examples of how urban architecture through its potentials has a positive impact on its urban context, notably through community projects that strongly linked to real community needs. The results showed that urban architecture as a design approach for community projects have multiple roles that boost the socio-economic daily life, as well it supports various environmental issues towards better QUL.
Urban Public Space Axis Rector of Green Infrastructure in the Current City of...IEREK Press
The current city calls for the reconsideration of a close relationship between gray infrastructure and public spaces, understanding the infrastructure as a set of items, equipment, or services required for the functioning of a country, a City. Ambato, Ecuador, is a current intermediate city, has less than 1% of the urban surface with use of public green spaces, which represents a figure below the 9m2/ hab., recommended by OMS. The aim of this paper was to identify urban public spaces that switches of green infrastructure in the city today, applying a methodology of qualitative studies. With an exploratory descriptive level analysis, in three stages, stage of theoretical foundation product of a review of the existing literature, which is the theoretical support of the relationship gray infrastructure public spaces equal to green infrastructure. Subsequent to this case study, discussed with criteria aimed at green infrastructure and in the public spaces of the study area. Finally, after processing and analysis of the results, we provide conclusions for urban public space as a definition of the green infrastructure of the current city of Latin America; in the latter, the focus is to support this article.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
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DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
2. Abde-hamed/ Environmental Science and Sustainable Development
pg. 2
TIC Total Investment Cost
WT Total Investment Cost
1. Introduction
Micro Grid is a standalone “a local energy provider which reduces energy expense and gas emissions by using
Distributed Energy Resources (DERs)”. MG is treated to be a promising choice or even an alternative to existing
centralized or traditional grids (Zhang, 2013). MGs apply a diversity of Distributed Generation units. These units
includes photovoltaic (PV) modules, Wind Turbines (WT) and energy storage (ES) such as batteries (Shi, Xie, Chu,
&, Gadh, 2014).
It is noted that very large number of population in the developing regions currently lose grid based electric current
services. MGs represent an important option for reducing the electricity gap in very parts of developing world in the
case of grid extension is unpractical (Zhang, 2013).
Proper selection of DERs and optimal sizing for them, for specific goal or objective, are challenging and very
important tasks in the designing of isolated MGs. This is because the coordination between the MG units with adds
of constraints is complicated (Hassanzadehfard, Tafreshi, & Hakimi, 2011). A nonlinear optimization problem is to
be formulated using the basic problem. This optimization problem can be then solved by a desired suitable
optimising technique.
There are number of optimization techniques which are used for the design of MGs (Paudel, Shrestha, & Adhikari,
2011) such as the graphical construction methods (Borowy & Salameh, 1996), linear programming (Chedid &
Rehman, 1997), iterative approach (Yang & Zhou, 2007), GA (Zhou, Yang, & Fang, 2008), and bacterial foraging
(Noroozian & Vahedi, 2010) and so on. The goal for each designer is to determine the best optimal objective/fitness
function value for a given configuration whichever the optimization method.
Rui Huang et al. In (Huang, Wang, Chu, Gadh, & Song, 2014) studied and proposed an approach to find the optimal
placements and sizes of a MG components. To solve the optimization problem, GA is used and compared with a
mathematical optimization method (nonlinear programming). A comprehensive objective function with practical
constraints which take all the important factors that will affect the reliability of the power grid, into account is
proposed. The analysis on results shows that GA maintains a delicate balance between performance and
complexity. It is concluded that GA performs better not only in accuracy, stability, but also in computation time.
Authors of (Huang, Wang, Chu, Gadh, & Song, 2014) did not take the constraints on dynamical power flow into
consideration when designing the new power system. A more comprehensive optimization problem need to be
studied and solved thoroughly.
In (Tabatabaei & Vahidi, 2013) proposed a model for setting the optimal operation of a MG. Diversity of
distributed generation sources that usually used in MGs are obtained by their proposed optimization problem.
Constraints are taken into considerations, in the proposed optimization problem, to reflect a number of limitations
which is found in a MG systems. Environmental costs have been also considered in the optimization problem. For
minimizing the defined objective/fitness function by considering network and load limitations, a new evolutionary
algorithm known as Bacterial Foraging Optimization Algorithm (BFOA) is applied. Although the used technique is
a new one, it has some disadvantages such as large number of parameters and complexity in design.
In (Mohamed & Koivo, 2007) suggested a generalized formulation for obtaining the optimal operation strategy and
cost minimization scheme for a MG. The MG components from actual manufacturer data are constructed before the
optimization of the MG itself. The suggested objective/fitness function considers the costs of the emissions, and the
operation & maintenance costs. The optimization method is aimed for reducing the cost objective/fitness function of
the system while constraining the objective for meeting the load demand profile and safety of the system. Authors
of (Mohamed & Koivo, 2007) did not put the environmental impacts into consideration which should be considered
to reduce the emissions level. The proposed cost function takes into consideration the costs of the emissions NOx,
SO2, and CO2 as well as the operation and maintenance costs but the the replacement cost is not considered. The
3. Abde-hamed/ Environmental Science and Sustainable Development
pg. 3
optimization aims to minimize the cost function of the system while constraining it to meet the customer demand
and safety of the system without taking the environmental constraints into consideration.
Recently, it is needful to obtain a flexible generalized approach or methodology for any kind of MG design of
higher computational efficiency. In addition, the computational optimization methods which use bio-inspired
technologies have been significantly developed in recent years. They can effectively increase the efficiency of MG
systems by finding the best configuration for optimizing the economic and technical criteria.
This paper presents a design of an optimal sizing and energy management scheme of an isolated MG components.
AMATLAB code is proposed for calculating the energy available from MG generation sources according to
meteorological data of the suggested location. The proposed optimization scheme has the advantages that it is
simple and and can be extended to deal with multi-objective functions besides dealing with more renewable and
storage components for the MG. The components of the MG are selected and designed to supply the suggested load
under the objective of minimum TIC with CO2 emissions limitations. The optimization process is carried out via
GA and PSO techniques. A comparison is accomplished to investigate the CO2 emissions constraints effects on the
TIC in $/year and annual cost of energy in $/kWh. It has been proved that the proposed scheme can robustly and
efficiently obtain the optimal MG configuration which is Eco-friendly and has great economic benefits.
Consequently, this research reveals that the MG will operate successfully as an isolated controllable power
generation unit for supporting the utility as well as reduces the dependency on the main grid and increases the
market penetration of the MG system or MG sources. Accordingly, it minimizes the problems associated with
central power plants such as power blackout and limitations of fossil fuels.
The rest of this article is organized as follows: Description and modelling of the components for the MG are
introduced in Section 2. Fitness function and constraints are presented and modeled in Section 3. Section 4
describes proposed optimization procedures and a case study. Section 5 presents simulation results and analysis.
Finally conclusion is discussed in Section 6.
2. Complete system modeling
The proposed isolated MG system includes WTs, PVs, batteries, PV controllers, DG units, and inverters. The
schematic diagram for the suggested MG system is indicated by Fig. 1. The first step for optimization process is to
model the MG components used to supply the load. In the following sections, a modeling description of the
components of the complete system is demonstrated.
Figure 1. Schematic diagram for the proposed hybrid multi source MG system
2.1. WT modeling
WT uses kinetic energy from wind speed to produce mechanical energy and then this produced mechanical energy
is utilized for generating the electrical energy (Govardhan & Roy, 2012). WT electrical energy is calculated for
4. Abde-hamed/ Environmental Science and Sustainable Development
pg. 4
each time based on site weather and height of installation for WTs (Bansal, Kumar, & Gupta, 2013). The speed of
wind, at a specific height, can be obtained from “NASA surface meteorology and solar energy”. Modification of
wind speed to the desired hub height, using the measured speed of wind at the reference height, is significantly
required (Tito, Lie, & Anderson, 2015), (Hassan, El-Saadawi, Kandil, & Saeed, 2016).
The energy output from the WT, at a site wind speed, is obtained using the WT power curve that is denoted by
manufacturer. For a given speed profile, the energy available from wind can be modeled using equation (1)
(Yazdanpanah, 2014):
𝐸𝑊𝑇 = 𝑇ℎ𝑟 ∑ 𝑃
𝑜. 𝑓(𝑣, 𝑘, 𝑐)
𝑣𝑚𝑎𝑥
𝑣𝑚𝑖𝑛
(1)
Where EWT represents the energy output from WT in kWh at a given location, Thr represents the time (hours) used in
the study, Po represents the power output of WT (kW), (vmin, vmax) represents the minimum and maximum speeds of
wind, and f(v, k, c) represents the Weibull function for a given site wind speed (ν) at a designed shaping coefficient
k and scaling coefficient c.
The Energy Pattern Factor (EPF) approach is required and recommended for more precise determination of c and k
coefficients. This is to reduce uncertainties concerning with the output wind energy calculation for Wind Energy
Conversion System (WECS) (Kidmo, Danwe, Doka, & Djongyang, 2015).
2.2. PV modeling
PV modules are systems in which sunlight straight converted into electricity. The energy per year of a PV module,
at a certain location with a known solar Irradiation and temperature, can be modeled using equation (2).
𝐸𝑃𝑉 = 𝑇ℎ𝑟 ∑ 𝑃(𝑇, 𝐺)
𝐺𝑚𝑎𝑥,𝑇𝑚𝑎𝑥
𝐺𝑚𝑖𝑛,𝑇𝑚𝑖𝑛
(2)
Where EPV is the energy production per year of PV module, Thr represents time (hours) through which the sun hits
the PV modules and P(T, G) represents the PV modules output power at a solar irradiation G and temperature T of
hourly average values, which is calculated using equation (3) (Mohamed & Koivo, 2011).
𝑃𝑃𝑉(𝑇, 𝐺) = 𝑃𝑆𝑇𝐶
𝐺𝐼𝑁𝐺
𝐺𝑆𝑇𝐶
(1 + 𝑘(𝑇𝑐 − 𝑇𝑟)) (3)
Where PPV(T,G) represents the PV power at incident irradiance and temperature, PSTC represents the maximum
power for the PV at STC, GING is the fallen irradiation, GSTC represents the irradiation at STC (1000W/m2
), k is the
power temperature coefficient (0.5 %/co
), Tc is the cell temperature, and Tr is the reference temperature.
2.3. DG modeling
The conventional roles for diesel generations have been the condition of peak shaving and stand-by power
(Mohamed el al., 2011). In this paper, DGs are supposed for sharing the wind/PV generations for feeding the load
demand. DGs powers are related to their Fuel Consumption (FC). This means that they are characterized by their
efficiency and fuel consumption. The DGs operate between 80 and 100 percent of their nominal powers for
obtaining higher efficiency use (Hassan, Saadawi, Kandil, & Saeed, 2015). The energy that can be generated by a
DG is determined by using the following equation (4) (Bilal et al., 2012):
𝐸𝐷𝐺(𝑡) = 𝑃𝐷𝐺(𝑡). 𝜂𝐷𝐺. 𝑇ℎ𝑟 (4)
5. Abde-hamed/ Environmental Science and Sustainable Development
pg. 5
Where EDG is the DG energy per year in KWh, PDG is the DG rating power, 𝜂𝐷𝐺 is the DG efficiency, and Thr
represents its hours of operations.
The fuel consumption of a DG depends on both the load and the size of generator. Hourly fuel consumption is given
by equation (5) (Hassan et al., 2016).
𝐹𝐶(𝑡) = 𝑎. 𝑃𝑜(𝑡) + 𝑏. 𝑃
𝑛 (5)
Where, (a & b) represents the coefficients for the fuel consumption curve and ( Po & Pn) are power output and
nominal rating of the DG. In this paper, a is taken to be 0.081451 L/kWh while b is taken to be 0.2461 L/kWh
(Hassan et al., 2016).
The total CO2 emission amount can be determined using the following equation (6) (Hassan et al., 2016):
𝑄𝑐𝑜2 = 𝐹𝐶 . 𝐸𝐹 (6)
Where QCO2 is the total CO2 emission amount in (kg), FC is the fuel consumption in (kWh) and EF represents the
emission factor for the fuel used in kg/kWh. For the diesel fuel considered in this article, the default CO2 emission
factor is 0.705 kg/kWh (Hassan et al., 2016).
Usage of a DG is not in line with prevention of air-pollution and minimization of CO2 emission. A gas micro-
turbine will be more environmentally friendly solution but it is not practical to be used in our location and its cost is
higher besides its complex design. A tax on CO2 levels of emissions in any sector did not yet applied by whether
industrial or energy production in the site of the proposed MG. However, the department of environment stated,
depending on the Environmental Law4 of 1994, that there is a need to force such a tax for emissions per year of that
pollutant and harmful gas. The department of environment enumerated these ratings according to European
standards.
2.4. Battery modeling
Battery is defined as an electro-chemical device that stores the electrical energy from AC or DC units of MG for
later use. Since the output of the renewable sources of the MG is a random behavior, the state of charge (SOC) of
the battery is constantly changing accordingly in MG system. When the total power output from the WTS, PV
modules is greater than the load power, the battery is in the SOC. When the total output power of the WT and PV
modules is less than the load power, the battery is in the discharging state. The SOC of battery bank can be
calculated from the following equation (7) (Wei, 2007):
𝑆𝑂𝐶(𝑡) = 𝑆𝑂𝐶(𝑡 − 1). (1 − 𝜎) + [𝐸𝐺𝑡(𝑡) −
𝐸𝐿(𝑡)
𝜂𝑖𝑛𝑣
] . 𝜂𝑏𝑎𝑡 (7)
Where, SOC(t) and SOC(t-1) are the battery bank state of charge at time t and t-1, σ is monthly self-discharging
rate, EGt(t) is the total energy generated, EL(t) is the load demand, ηinv and ηbat are the efficiency of inverter and
battery.
In this paper, the battery SOC model is designed based on the Ah method. The capacity of battery bank (BReq)
required for a MG system can be calculated using the following equation (8) (Hassan et al., 2016).
𝐵𝑅𝑒 𝑞 =
𝐿𝐴ℎ/𝑑𝑎𝑦. 𝑁𝑐
𝑀𝐷𝐷. 𝐷𝑓
(8)
Where LAh/d is the total Ah consumption of the load per day, MDD is the maximum discharge depth and DF is the
factor of discharging and NC represents the autonomous day’s number.
6. Abde-hamed/ Environmental Science and Sustainable Development
pg. 6
The number of parallel connected batteries (Np) for giving the Ah needed by the MG system is determined using
equation (9), while the number of series connected batteries (Ns) for giving the system voltage VN is determined
using equation (10) (Yazdanpanah, 2014).
𝑁𝑝 =
𝐵𝑅𝑒 𝑞
𝐵𝑐
(9)
𝑁𝑠 =
𝑉𝑁
𝑉𝐵
(10)
Where BReq is the required capacity of the battery bank in Ah, BC is the the selected battery capacity, VN is the MG
system voltage and VB is the battery voltage. The total batteries number NBT is obtained as indicated by equation
(11).
𝑁𝐵𝑇 = 𝑁𝑝. 𝑁𝑠 (11)
2.5. PV controller modeling
The Maximum Power Point Tracker (MPPT) controller is implemented as a PV controller which tracks MPP of the
PV system. This is achieved throughout the day delivering the maximum amount of the available solar energy to the
MG system. MPPT controller comprises a number of PV controllers needed for the MG system. The PV controller
numbers required for a PV system is calculated by using the equations 12, 13, and 14 (Hassan et al., 2016), (Hassan
et al., 2015).
𝑃𝑝𝑣_𝑅𝑡𝑜𝑡 = 𝑁𝑝𝑣. 𝑃𝑝𝑣_𝑅 (12)
𝑃𝑚𝑎𝑥_ 𝑐𝑜𝑛 = 𝑉𝑏. 𝐼𝑐𝑜𝑛 (13)
𝑁𝑐𝑜𝑛 =
𝑃𝑝𝑣_𝑅𝑡𝑜𝑡
𝑃𝑚𝑎𝑥_ 𝑐𝑜𝑛
(14)
Where Icon represents the maximum current which the controller handles from the PV to the battery, Vb is the
voltage of the battery, PPV_R is the PV rated power at STCs, PPV_Rtot is the total power of the PVs at STCs, Pmax_con
represents the maximum power of one controller, and NPV represents the total number of PV modules.
2.6. Inverter modeling
Inverters are generally used as the interface to connect energy between MG components and the load. The selected
power inverter must be capable of handling the maximum power expected by AC loads (Bilal el al., 2012), (Hassan,
El-saadawi, Kandil, & Saeed, 2015).
Inverters are classified into three main different schemes. These types are standalone, grid tied battery less and grid
tied with battery back-up inverters (Hassan el al., 2015). In this paper, the stand alone inverter is used. The number
of inverters needed for a certain load demand can be modeled and enumerated using equation (15) (Solar Energy
International, (2007).
𝑁𝑖𝑛𝑣 =
𝑃
𝑔_𝑚𝑎𝑥
𝑃𝑖𝑛𝑣_𝑚𝑎𝑥
(15)
Where Pinv_max represents the maximum power that the inverter can supply, Pg_max is the maximum power that the
MG system generates, and Ninv represents the inverter numbers.
3. Optimal design of MG configuration
The optimal design of MG configuration that can manage the load makes the best compromise between the MG
system CO2 emissions and the cost of energy to optimize the fitness function in the MG system lifetime.
7. Abde-hamed/ Environmental Science and Sustainable Development
pg. 7
3.1. Objective function
The objective of the proposed approach is the design of optimal MG configuration scheme that can manage the
prescribed load under the suggested objective/fitness function and various constraints. The objective/fitness
function in this paper is to minimize the system TIC through the system lifetime in the standalone mode. The
unknown variables are the number of wind turbines, PV modules, batteries, controller units, inverter units, and
diesel generators. These variables represent the number of equipment needed to supply the load at minimum
investment cost with CO2 constraints. The problem is solved for two scenarios: cost minimization without
emissions constraints and cost minimization with emissions limitations. The mathematical model for the general
objective/fitness function can be formulated as follows (Hassan et al., 2016):
𝑇𝐼𝐶 = ∑ 𝑁𝑊𝑇𝑖
𝑛𝑊𝑇
𝑖=1
. 𝐶𝑊𝑇𝑖 + ∑ 𝑁𝑃𝑉𝑗
𝑛𝑃𝑉
𝑗=1
. 𝐶𝑃𝑉𝑗 + ∑ 𝑁𝐵𝐴𝑇𝑘
𝑛𝐵𝐴𝑇
𝑘=1
. 𝐶𝐵𝐴𝑇𝑘 + ∑ 𝑁𝐷𝐺𝑙
𝑛𝐷𝐺
𝑙=1
. 𝐶𝐷𝐺𝑙
+ ∑ 𝑁𝐶𝑂𝑁𝑚
𝑛𝐶𝑂𝑁
𝑚=1
. 𝐶𝐶𝑂𝑁𝑚 + ∑ 𝑁𝐼𝑁𝑉𝑦
𝑛𝐼𝑁𝑉
𝑦=1
. 𝐶𝐼𝑁𝑉𝑦
(16)
Where NWT, NPV, NDG, NBAT, NCON, and NINV are number for each type to be selected of WTs, PV modules, DGs,
batteries, controllers and inverters. CWT, CPV, CDG, CBAT, CCON, and CINV are the total investment cost for each type of
a WT, a PV, a DG, a battery, a controller, and an inverter.
The TIC of the DG comprises the capital (Ccap), the operating & maintenance per year (CO&M), the fuel (Cf) and the
pollutant CO2 emissions costs (Cem). The TIC for other MG components contains capital (Ccap), installation (Cins),
and operation & maintenance (CO&M) costs. The following equations (17 to 22) demonstrates the mathematical
model used for calculating the TIC for DG, wind turbine, PV module, battery bank, a controller, and inverter,
respectively (Bilal el al., 2012).
𝐶𝐷𝐺 = (
𝐶𝐶𝑎𝑝𝐺𝐷
4
+ 𝐶𝑓𝐷𝐺
. 𝐻𝐴𝑛𝑛 + 𝐶𝑂&𝑀_𝑊𝑇. 𝐻𝐴𝑛𝑛 + 𝐶𝑒𝑚). 𝑇𝑙𝑖𝑓𝑒_𝑃𝑟 (17)
𝐶𝑊𝑇 = 𝐶𝐶𝑎𝑝_𝑊𝑇 + 𝐶𝐼𝑛𝑠_𝑊𝑇 + 𝑇𝐿𝑖𝑓𝑒𝑡𝑖𝑚𝑒. 𝐶𝑂&𝑀_𝑊𝑇 (18)
𝐶𝑃𝑉 = 𝐶𝐶𝑎𝑝_𝑃𝑉 + 𝐶𝐼𝑛𝑠_𝑃𝑉 + 𝑇𝐿𝑖𝑓𝑒𝑡𝑖𝑚𝑒. 𝐶𝑂&𝑀_𝑃𝑉 (19)
𝐶𝐵𝑎𝑡 = 𝐶𝐶𝑎𝑝_𝐵𝑎𝑡 + 𝐶𝐼𝑛𝑠_𝐵𝑎𝑡 + 𝐶𝑅𝑒 𝑝_𝐵𝑎𝑡. 𝑁𝑅𝑒 𝑝_𝐵𝑎𝑡 (20)
𝐶𝐶𝑜𝑛 = 𝐶𝐶𝑎𝑝_𝐶𝑜𝑛 + 𝐶𝐼𝑛𝑠_𝐶𝑜𝑛 + 𝑇𝐿𝑖𝑓𝑒𝑡𝑖𝑚𝑒. 𝐶𝑂&𝑀_𝐶𝑜𝑛 + 𝐶𝑅𝑒 𝑝_𝐶𝑜𝑛. 𝑁𝑅𝑒 𝑝_𝐶𝑜𝑛 (21)
𝐶𝐼𝑛𝑣 = 𝐶𝐶𝑎𝑝_𝐼𝑛𝑣 + 𝐶𝐼𝑛𝑠_𝐼𝑛𝑣 + 𝑇𝐿𝑖𝑓𝑒𝑡𝑖𝑚𝑒. 𝐶𝑂&𝑀_𝐼𝑛𝑣 + 𝐶𝑅𝑒 𝑝_𝐼𝑛𝑣. 𝑁𝑅𝑒 𝑝_𝐼𝑛𝑣 (22)
Where Hann is the number of hours that the DG can be used in one year (6*365), Tlifetime is the life time for the
project (20 years) and NRep is the number of unit replacements through the lifetime period. In this paper, the lifetime
of both PV modules and WT is supposed to be 20 year, the inverter and controller is life time is supposed to be 10
years, and the batteries life time is assumed to be 5 years (Bilal el al., 2012). The MG units replacement costs (Crep)
are considered to be the same as their capital costs.
3.2. Constraint for energy balance
The total generation of yearly energy (kWh/year) have to exceed or at least equal to the effective energy of the
annual consumption. The effective energy of annual consumption is the energy consumed by the yearly load
demand divided by the efficiency of the overall system (𝜂𝑠𝑦𝑠). The energy balance can be modeled using equation
(23) and the overall system efficiency can be determined as equation (24) indicates (Hassan et al., 2016).
8. Abde-hamed/ Environmental Science and Sustainable Development
pg. 8
∑ 𝑁𝑊𝑇
𝑖
. 𝐸𝑊𝑇 + ∑ 𝑁𝑃𝑉
𝑗
. 𝐸𝑃𝑉 + ∑ 𝑁𝐷𝐺. 𝐸𝐷𝐺 ≥
𝐸𝐿𝑜𝑎𝑑
𝜂𝑠𝑦𝑠
𝑙
(23)
𝜂𝑠𝑦𝑠 = 𝜂𝐷𝐺. 𝜂𝐵𝑎𝑡. 𝜂𝐶𝑜𝑛. 𝜂𝐼𝑛𝑣. 𝜂𝑊 (24)
Where Eload, EWT, EPV, and EDG represent the energy consumption of the load, generated by WTs, PV modules, DGs,
in (kWh/year). ηsys, ηInv, ηCon, ηW, ηBat, and ηDG represent overall MG system, inverter, PV controller, connection
wires, battery, and DG efficiencies. The average efficiency for DG, battery, PV controllers, inverter, and wires, are
shown in Table 1.
Table 1. Efficiencies for components of MG.
MG components Efficiency MG components Efficiency
DG 0.85 Inverter 0.95
battery 0.85 Wires 0.90
PV controller 0.95 – –
3.3. Much bounds and size of design variables constraints
These constraints involve physical limits on the number of MG generation sources according to the available area
of the land of the project. It also contains limits with respect to the sizing of the PV units as well as controllers and
inverters and constraints to the SOC of batteries. These constraints can be modeled as indicated by the following
equations (25 to 30):
0 ≤ 𝑁𝑊𝑇 ≤ 𝑁𝑊𝑇_𝑚𝑎𝑥 (25)
0 ≤ 𝑁𝑃𝑉 ≤ 𝑁𝑃𝑉_𝑚𝑎𝑥 (26)
0 ≤ 𝑁𝐷𝐺 ≤ 𝑁𝐺𝐷_𝑚𝑎𝑥 (27)
∑ 𝑁𝐶𝑜𝑛. 𝑃𝐶𝑜𝑛 ≥ 𝑃𝑃𝑉_𝑚𝑎𝑥
∑
𝑗
(28)
∑ 𝑁𝐼𝑛𝑣. 𝑃𝐼𝑛𝑣 ≥ 𝑃𝑚𝑎𝑥
∑
𝑖
(29)
𝑆𝑂𝐶𝑀𝑖𝑛 ≤ 𝑆𝑂𝐶 ≤ 𝑆𝑂𝐶𝑀𝑎𝑥 (30)
Where NWT-max, NPV-max, and NDG-max represent the maximum number of WTs, PV modules and DG units. PIN, PCON,
Pmax, and PPV-max represent the maximum output power of inverter, PV controller, load, PV module in watts and
SOC is the battery state of charge.
3.4. Diesel operation constraints
DG should have operation time limits for reducing wear and tear. This limitation can be modelled using equation (31).
0 ≤ ∑ 𝑇𝐷𝐺
𝑇=24
𝑇=1
≤ 𝑇𝑚𝑎𝑥 (31)
Where TDG represents the time in hours that the DG operates daily and Tmax is the maximum permissible time that
the DG operates per day.
9. Abde-hamed/ Environmental Science and Sustainable Development
pg. 9
3.5. CO2 emissions constraints
The CO2 emissions amount in kg is an indication parameter for the environmental pollution. It represents the
maximum percentage of the CO2 emission results in fuel combustion. Up till now, there are no maximum
governmental permissible limits or level of CO2 emissions in country where of the MG project is proposed (Hassan
et al., 2016). In this paper, a maximum permissible level of CO2 (kg) is suggested for investigating the impact of
CO2 on the optimal MG system configuration and TIC. This limitation can be supposed according to equation (32).
𝐶𝑂2 ≤ 𝐶𝑂2_𝑚𝑎𝑥 (32)
Where CO2-max represents the maximum permissible limit of the CO2 harmful emissions in (kg).
4. Optimal MG configuration approach and case study
4.1. Optimal method
The MG configuration optimization problem is solved by using the MATLAB optimal search code. The GA and
PSO techniques used by authors in (El-Wakeel, El-Eyoun, Ellissy, & Abdel-hamed, 2015) are implemented with
the proposed modules of MATLAB code. This is achieved to determine the numbers of WTs, PVs, DG units,
batteries, PV controllers, and inverters. This configuration supplies the load described in subsection 4.2.1 and
reduces the TIC per year taking into accounts the pollutant CO2 emission limits. The MATLAB code which is
divided into four module codes as shown in Fig. 2 is designed to represent and execute the proposed approach.
The 1st
module calculates the energy generated per year by any given type of WT based on the designed model
illustrated in section 2.1. A combination of WTs power curve and Weibull is used by this module. The input
information for that module are: the WTs power curves, the resource for wind speeds at both hub and tower height.
The energy generated annually by any given type of a PV array, based on the mathematical model explained in
section 2.2, is calculated by using the 2nd
module. The data entered for the module are: power rating of each WT
type, the site temperature and irradiance levels.
The 3rd
module computes the annual energy generated by any given type of DG based on the mathematical model
explained in section 2.3. The data entered for the module are: the diesel generator rated power, the diesel generator
efficiency, and its operation time.
The 4t h
module is the GA, and PSO technique (El-Wakeel, El-Eyoun, Ellissy, & Abdel-hamed, 2015) used with the
objective/fitness function for the optimization of the proposed configuration. All the previous results from first,
second, and third modules are the inputs to fourth module besides the data for controllers, inverters, and batteries.
This module calculates the optimal number of MG system components supplying and managing the specified load
based on minimum TIC for all components with CO2 emissions constraints considerations.
Solar Cells and Solar
Temperature and
Radiation
Code of
Module 1
Code of Module 4 (AI
Techniques)
Prices, Controllers and
Inverters Data
Wind Turbines Power
Curves and Wind Speed
Data
Diesel Rated Power,
Efficiency and Operation
Time
Code of
Module 2
Code of
Module 3
Annual Solar Energy Annual Wind Energy
Annual Wind Energy
Load Data
Optimal MG
Configuration for
Energy Mangement
Figure 2. Modules of the suggested optimization scheme
10. Abde-hamed/ Environmental Science and Sustainable Development
pg. 10
A detailed computational procedure of fourth module, for optimal MG system configuration, is indicated by Fig. 3.
The input data are 1) The data related to meteorological information of the selected location. This data is obtained
from NASA. 2) The unit prices of the projected MG system components including installation, operation &
maintenance costs, components life time which are acquired from (Hassan el al., 2015). 3) Other inputs are fitness
function, constraints and load data explained previously.
The optimal composition of PVs, WTs, DGs, batteries, controllers, and inverters from different brands are
calculated by using PSO and GA as follows:
- Using GA
The initial population of the chromosomes that represents the number of each component of the MG is randomly
generated. The chromosomes are evaluated according to the selected fitness function described in Subsection 3.1. A
new population based on the fitness of the individuals is selected from the old one. Genetic operators (mutation and
crossover) are applied to members of the population to create new solutions. The process of evaluation and new
population creation is continued until a satisfactory solution based on specific termination criteria has been
satisfied. Usually the maximum number of generations is used as the termination criterion. Experience shows that
mutation should be done with a low probability ranging from 0.1 to 2%, while the crossover rate should be between
60 to 90%. Again, the GA has been run for 20 independent trials with different settings until the solutions are very
close to each other. According to the trials, GA parameters are determined as: maximum number of
iterations/generations =100, population size = 3000, the cross over rate = 0.9 and the mutation rate = 0.001.
- Using PSO
In the PSO algorithm, a population of particles is put into the dimensional search space with randomly chosen
velocities and positions knowing their best values so far (pbest) and the position in the d-dimensional space. The
velocity of each particle is adjusted according to its own flying experience and the other particles’ flying
experience. The fitness function value is calculated for each particle. If the value is better than the current pbest of
the particle, the pbest value is replaced by the current value. If the best value of pbest is better than the current
gbest, the gbest is replaced by the best value and the particle number with the best value is stored. The operation is
continued until the current iteration number reaches the predetermined maximum iteration number. The PSO
algorithm has been run for 20 independent trials with different settings until the solutions are very close to each
other. According to the trials, the PSO parameters are determined as: maximum of iterations/generations=100,
number of particles/agents = 3000, acceleration constant c1= 0.6, c2 = 1.4 and weighting factor = 0.95.
Generation of initial condition
Enter:
Meteorological data, Economical data
for function & constraints, Techniques
parameters
Evaluation of searching points using equation (14)
Stopping criteria reached ˀ
Modification of each searching point using
GA or PSO
Display:
-Optimal solution
-MG configuration
-TIS
-CO emssions
Start
Yes
No
Figure 3. Computational procedure flow chart using PSO or GA
11. Abde-hamed/ Environmental Science and Sustainable Development
pg. 11
4.2. Case study
The case study is a typical isolated MG suggested to supply a load located between (30.119 latitude and 31.605
longitude). It consists of different types of energy generation units such as WTs, PVs, DGs, and battery banks as a
storage system. The optimization scheme is used to find the optimal configuration and energy management of the
MG components that satisfy the objective/fitness function discussed previously in equation (16). Input data includes
the load data, meteorological data of the suggested location, and techno-economical data of the MG system
components.
4.2.1. Load data
It is considered that outdoor and indoor lighting load for educational building located between (30.119o
latitudes
and 31.605o
longitudes) will be met by a MG system. Table 2 shows the daily electrical load requirements, with a
load of 50 kW peak. Using Table 2 and actual load measuring, a load profile is built as indicated by Fig. 4. It shows
the daily load profile for proposed MG system with a maximum value of 50 kW and an average consumption per
day of 516.724 kWh.
Table 2. Daily electrical load requirements
Purpose entrance outdoor Indoor
Rated power (kW) 1.08 14.588 49.968
Operation period (h) 6 11 7
Dailyenergy( kWh/day) 6.48 160.468 349.776
Total daily energy ( kWh/day) 516.724
Figure 4. Considered daily load profile
4.2.2. Meteorological and techno-economical data
The solar radiation and wind speed are obtained from “NASA surface meteorology and solar energy”. The monthly
average insulations and air temperature (°C), for the suggested location, incident on a horizontal surface are
indicated by Table 3 and Table 4 respectively. Whereas, the average values per month of the wind speed at (50 m)
above the earth surface are indicated by Table 5. As explained before in Section 2.1, it is found necessary to adjust
the wind speed to the hub height if the speed is measured at a height different than that of turbine hub height. In this
paper the wind towers are taken with a 20 meters height, so that the measured wind speed values have to be
modified as it is obvious in Table 6. The techno-economic data of the used commercial components in this article
are taken as in (Hassan el al., 2015) (21 types of WTs, 13 types of PVs, 1 types of DGs, 5 types of PV controllers,
5 types of inverters, 20 types of batteries).
0 5 10 15 20
0
10
20
30
40
50
60
Hour
load
consumption
(kW)
12. Abde-hamed/ Environmental Science and Sustainable Development
pg. 12
Table 3. Monthly averaged isolation for the suggested location
Month Jan Feb Mar Apr May Jun Annual average
22-years average solar radiation (kWh/m2/day) 3.23 3.91 5.11 6.28 6.99 7.69
5.35
Month Jul Aug Sep Oct Nov Dec
22-years average solar radiation (kWh/m2/day) 7.33 6.85 5.86 4.48 3.45 3.00
Table 4. Averaged air temperature/month for the suggested location
Month Jan. Feb Mar Apr May Jun Annual average
22-years average air temperature (°C) 13.3 13.6 16.0 20.1 23.4 26.3
21
Month Jul Aug Sep Oct Nov Dec
22-years average air temperature (°C) 28.2 28.2 26.3 22.8 18.9 14.8
Table 5. Averaged wind speed/month at 50 m from the surface for for the suggested location
Month Jan Feb Mar Apr May Jun Annual average
measured wind speed at 50 m height (m/s) 4.74 5.01 4.99 4.78 4.80 4.68
4.75
Month Jul Aug Sep Oct Nov Dec
measured wind speed at 50 m height (m/s) 4.73 4.71 4.78 4.68 4.44 4.71
Table 6. Averaged modified wind speed/month for the suggested location
Month Jan Feb Mar Apr May Jun
Annual
average
Modified speed at 20m height(m/s) 4.1584 4.3953 4.3778 4.1935 4.2111 4.1058
4.1709
Month Jul Aug Sep Oct Nov Dec
modified speed at 20 m height (m/s) 4.1497 4.1321 4.1935 4.1058 3.8952 4.1321
5. Optimization results and analysis
The optimum MG system configuration, that meets the energy required by the previously mentioned load profile
with minimum TIC and emissions limits, is obtained by performing the designed optimization scheme explained in
subsection 4.1. Table 7 indicates the bounds and size of design variables Constraints used in this paper. The
simulation results to obtain minimum TIC without and with various emission limits using GA, and PSO techniques
are explained in the following subsections.
Table 7. Indicates the bounds and size of design variables Constraints
Optimal Search limits NWT NPV NDG NBat NCON NINV TDG (hours)
Minimum (lower Limit) 0 0 0 0 0 0 0
Maximum (upper Limit) 1 40 20 10 50 10 6
13. Abde-hamed/ Environmental Science and Sustainable Development
pg. 13
5.1. Using PSO without CO2 emissions constraint
In this configuration, Table 8 indicates different types and numbers of wind turbines, PV modules, diesel
generators, inverters and controller in the designed MG configuration indicated in Fig. 2 and explained in details
previously in subsection 4.1. Number of different battery types is also used for charging the excessive energy in
case of generation higher than load and to supply the load in case of generation is higher. In this case, per year total
generated energy is of 321650.34 kWh, and per year consumption of energy is 321603.88 kWh. The model
represents a MG system configuration with a TIC value of $47822.59 with emissions of 15146.06 kg of CO2.
Table 8. MG sizing optimization results without emission constraint
MG Commercial type Rated cap. No. Commercial type Rated cap. No.
Wind
SouthWest (Air X) 400W 1 Bornay-Inclin 6000 6000W 1
SW(Whisper 500) 3000W 1 ARE110 2500W 1
AE (Lakota) 800W 1 ARE442 10000W 1
Bergey (BWC 1500) 1500W 1 Kestrel Wind (800) 800W 1
Bergey(BWCExcelR) 8100W 1 KestrelWind(3000) 3000W 1
Bornay (Inclin 600) 600W 1 Solacity (Eoltec) 6000W 1
Bornay (Inclin 1500) 1500W 1 – – –
PV
Sharp ND-250QCS 250W 32 CSI CS6X-285P 285W 39
Hyundai HiS-255MG 255W 36 CanadianSolar250P 250W 33
Lightway 235W 40 CSI CS 6X-295P 295W 40
Trina TSM-PA05 240W 40 CanadianSolar300P 300W 40
SolartechSPM135P 135W 16 CanadianSolr255M 255W 37
CSI CS6P-235PX 235W 21 HyundaiHiS260MG 260W 37
CSI CS6X-280P 280W 40 – – –
DG STEPHIL -SE 3000D 1900W 11 – – –
Battery
MK8L16 370Ah 1 US Battery US2200 225Ah 2
Surrette2Ks33Ps 1765A 8 US Battery US250 250Ah 1
SurretteS1-460 350Ah 1 SurretteS2-460 350Ah 1
Trogan T-105 225Ah 2 SurretteS530-6v 400Ah 2
US Battery US185 195Ah 1 – – –
Controller
SE-XW-MPPT-60 1500W 30 Outback FM60 1500W 12
Outback FM80 2000W 27 Blue Sky SB3048 750W 8
Inverter
SE-XW6048 6000W 4 FX-2024ET 2000W 2
SE-XW4548 4500W 2 SE-XW4024 4000W 4
TIC ($) 47822.5970
CO2 (kg) 15146.06
14. Abde-hamed/ Environmental Science and Sustainable Development
pg. 14
5.2. Using PSO with CO2 emissions constraint
For investigating the CO2 emissions effect on the TIC of the MG system, a predetermined maximum permitted CO2
emissions limits introduced. For CO2 emissions constraints limited to 6884 kg, Table 9 presents the optimization
results using PSO.
Table 9. MG sizing optimization results with emission constraint
MG Commercial type Rated cap. No. Commercial type Rated cap. No.
Wind
SouthWest (Air X) 400W 1 BornayInclin 3000 3000W 1
SW (Whisper 200) 1000W 1 BornayInclin 6000 6000W 1
SW(Whisper 500) 3000W 1 ARE110 2500W
SW(Skystream 3.7) 1800W 1 ARE442 10000W 1
Bergey-BWCExcelR 8100W 1 Kestrel Wind (1000) 1000W 1
Bornay (Inclin 250) 250W 1 Kestrel Wind (3000) 3000W 1
Bornay (Inclin 1500) 1500W 1 Solacity (Eoltec) 6000W 1
PV
Sharp ND-250QCS 250W 40 CSI CS6X-285P 285W 40
HyundaiHiS-255MG 255W 40 CanadianSolar250P 250W 40
Lightway 235W 40 CSI CS 6X-295P 295W 40
Trina TSM-PA05 240W 29 CanadianSolar300P 300W 39
SolartechSPM135P 135W 21 CanadianSolr255M 255W 40
CSI CS6P-235PX 235W 40 HyundaiHiS260MG 260W 40
CSI CS6X-280P 280W 40 – – –
DG STEPHIL-SE 3000D 1900W 5 – – –
Battery
MK8L16 370Ah 2 US Battery US185 195Ah 4
Surrette2Ks33Ps 1765Ah 5 US Battery US2200 225Ah 3
Surrette 4-Cs-17Ps 546Ah 4 US Battery US250 250Ah 3
Surrette6-CS-17Ps 546Ah 2 SurretteS2-460 350Ah 2
Trogan T-105 225Ah 4 SurretteS530-6v 400Ah 5
Controller
SE-XW-MPPT-60 1500W 17 SE-XW-MPPT-80 2000W 15
Outback FM80 2000W 23 Blue Sky SB3048 750W 13
Outback FM60 1500W 14 – – –
Inverter
SE-DR1524E 1500W 3 FX-2024ET 2000W 5
SE-XW6048 6000W 4 SE-XW4024 4000W 4
SE-XW4548 4500W 2 – – –
TIC ($) 48503.4315
CO2 (kg) 6884.5772
15. Abde-hamed/ Environmental Science and Sustainable Development
pg. 15
It can be concluded from Table 9 that by decreasing the maximum allowable CO2 emissions limits, number of DGs
is decreased and consequently the number of PV modules, PV controllers, and WTs are increased. This will
increase the installation cost of the MG system and therefore the TIC value will be increased to 48503.43$ instead
of 47822.59$ without constraints.
5.3. Impact of CO2 emissions constraint with comparison between PSO and GA
In this section, comparison of impacts of CO2 emissions constraint using PSO and GA is made. Table 10 indicates
the CO2 emissions constraints impacts on the MG configurations and also shows a comparison between the results
of GA and PSO techniques. Figs 5 -7 show a comparison between energy generated with and without CO2
emissions constraint.
Table 10. Impact of CO2 emissions constraints.
Item No CO2 constraints
Maximum allowable CO2 emissions
6884.5772 kg
Used Technique PSO GA PSO GA
Energy required by the load 321603.88 321603.88 321603.88 321603.88
Generated energy(kWh/year) 321650.34 321605.22 321776.51 321907.14
Surplus energy (kWh/year) 46.4619 1.3403 172.6333 303.25
Wind energy (kWh/year) 66557.88 46680.87 71602.43 71075.39
PV energy (kWh/year) 216187.10 236019.00 232489.83 233147.50
Diesel gen.Energy(kWh/year) 38905.35 38905.35 17684.25 17684.25
No. of DG 11 11 5 5
TIC ($/year) 47822.59 48553.92 48503.43 48688.70
% increase in TIC base base 1.42366 1.8110
Annual energy cost($/kWh) 0.14870 0.15097 0.15081 0.15139
CO2_emissions(kg/year) 15146.06 15146.06 6884.57 6884.57
%CO2 emissions decrease base base 54.5454 54.5454
Seeking Time (Sec) 55.2 88.5 57.6 90.7
16. Abde-hamed/ Environmental Science and Sustainable Development
pg. 16
Figure 5. Monthly wind energy in a year with and without constraints using PSO
Figure 6. Monthly PV energy in a year with and without constraints using PSO
Figure 7. Monthly DG energy in a year with and without constraints using PSO
17. Abde-hamed/ Environmental Science and Sustainable Development
pg. 17
It can be concluded from Table 10 and Figs 5 -7 that by decreasing the maximum allowable CO2 emissions limits,
the number of diesel generators is decreased. Consequently, the designed scheme tends to select higher number of
PV modules and WTs to overcome the decreasing in energy generated from diesel. This increase in WTs, PV units
and PV controller will increase the TIC (1.4236% in PSO which is approximately zero) due to the increase of the
installation cost of the system, but the CO2 emissions is decreased to the required level (45.4545 %). It is obvious
from Table 9 that the results obtained by the configuration scheme optimized by PSO is better than those obtained
by GA. This is with respect to TIC emissions and annual cost of energy. Fig. 6 shows that the components of MG
share higher power in April to August as the radiations of the selected site is higher at these months.
5.4. MG energy management
While designing and simulating the proposed MG, it was assumed that the MG is isolated and supplies the rated
energy to the load throughout the project lifecycle. From Table 9, it is obvious that MG system configuration with a
TIC of $48503.43 and 54.5454 % decrease in CO2 emissions represents the most economical design with lower
emissions. Thus this configuration is used for MG management and supplying the annual average load described in
subsection 4.2.1.
Fig. 8 shows share of designed individual MG components (wind, PV, and diesel) in supplying the demand
electricity for the load profile, whereas Fig. 9 indicates the monthly sharing of combined components and Fig. 10
shows the charged and discharged energy in batteries over the 12 month of the year.
Figure 8. Load profile sharing using MG components with 6884 kg emissions constraints
Figure 9. Grouped load profile sharing with 6884 kg emissions constraints
18. Abde-hamed/ Environmental Science and Sustainable Development
pg. 18
Figure 10. Surplus energy lost in batteries with 6884 kg emissions constraints
It is evident from Figs 8 -10 that with CO2 emissions limitation, the DGs share the smallest part of the load profile
energy. Also WTs shares poor energy due to the low wind speed profile of the MG site. The components of the MG
share higher energy in April to August as the irradiations and temperature of the selected site are higher at these
months. Results also proved that PV technology is preferable in this location.
6. Conclusion
In this paper, an optimal sizing scheme and energy management of MG components, supplying a load demand, is
constructed and designed. The objective of minimizing the TIC with environmental emissions constraints is
achieved. Limitations are also added to the optimization problem to take into accounts some of additional
considerations found in an isolated MG system. Final results proved that the proposed optimization scheme is
efficient and robust. Also the configuration scheme optimized with the help of PSO is better than those optimized
using GA with respect to TIC, emissions and annual cost of energy. Finally, adding extra limits on CO2 emissions
constraints result in extra emissions reduction of 54.54% and negligible cost increase of 1.43% which emphasizes
that the MG is designed economically with low environmental impacts. The meta-heuristic random search and
optimization techniques are now emerging as a viable planning tools in smart grid optimization and renewable
energy applications.
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