In this paper, cuckoo search algorithm (CSA) is suggested for determining optimal operation parameters of the combined wind turbine and hydrothermal system (CWHTS) in order to minimize total fuel cost of all operating thermal power plants while all constraints of plants and system are exactly satisfied. In addition to CSA, Particle swarm optimization (PSO), PSO with constriction factor and inertia weight factor (FCIW-PSO) and social ski-driver (SSD) are also implemented for comparisons. The CWHTS is optimally scheduled over twenty-four one-hour interval and total cost of producing power energy is employed for comparison. Via numerical results and graphical results, it indicates CSA can reach much better results than other ones in terms of lower total cost, higher success rate and faster search process. Consequently, the conclusion is confirmed that CSA is a very efficient method for the problem of determining optimal operation parameters of CWHTS.
Combined heat and power - optimal power flow based on thermodynamic model wit...IJECEIAES
Oil fields produce associated petroleum and wet gas, which can be mixed with commercial natural gas as fuel. Associated petroleum and wet gas are a low cost, low quality fuel, whereas commercial natural gas is the opposite. Two parameters are affected by this mixture: the fuel cost and the power – steam output of gas turbine – heat recovery steam generators. This research develops a Unit Commitment and Optimal Power Flow model based on Mixed Integer Nonlinear Programming to optimize combined heat and power cost by considering the optimal mixture between associated petroleum - wet gas and commercial natural gas. A thermodynamic model is used to represent the performance of gas turbine – heat recovery steam generators when subjected to different fuel mixtures. The results show that the proposed model can optimize cost by determining the most efficient power – steam dispatch and optimal fuel mixture. Furthermore, the optimization model can analyse the trade-off between power system losses, steam demand and associated - wet gas utilization.
Optimal tuning of a wind plant energy production based on improved grey wolf ...journalBEEI
The tuning of optimal controller parameters in wind plant is crucial in order to minimize the effect of wake interaction between turbines. The purpose of this paper is to develop an improved grey wolf optimizer (I-GWO) in order to tune the controller parameters of the turbines so that the total energy production of a wind plant is increased. The updating mechanism of original GWO is modified to improve the efficiency of exploration and exploitation phase while avoiding trapping in local minima solution. A row of ten turbines is considered to evaluate the effectiveness of the I-GWO by maximizing the total energy production. The proposed approach is compared with original GWO and previously published modified GWO. Finally, I-GWO produces the highest total energy production as compared to other methods, as shown in statistical performance analysis.
The Development of an Application Conceived for the Design, Feasibility Study...IJECEIAES
Because of the rise in diesel and butane prices widely used for pumping, added to their negative impact on both Morocco's environment and trade balance, the use of renewable energies should sound obvious, practical and cost effective. This study offers the transformation of a traditional butane pumping system (BPS) and diesel pumping system (DPS), located on a farm nearby the city of Agadir, into an optimized solar pumping system (SPS). The suggested method is based on a techno-economic study according to the “Business-As-usual” scenario. As a first step, we have dimensioned our pumping system and chosen the elements that constitute it. As a second step, we carried out an economic analysis, based on the calculation of all costs, which makes it possible to ensure the viability of the components of our SPS over its life cycle and brought it to a discounted value. The processing of the different data is made possible thanks to the computer application “PVDesign” which we have developed. This application has allowed us to carry out a comparative study of several techniques of pumping systems. The result of the study is that the SPS beats the other systems at various levels, namely economic, environmental and technical.
Photovoltaic (PV) cell from solar energy is one of the most widely adopted renewable energy source and commercially available system that can be used in various applications. More appealing application of PV arrays used in thermoelectric (TE) device was it can convert solar thermal energy from temperature difference into electric energy to act as power generators. In this study, a theoretical model is developed by using conducting steady state energy analysis of a PVT-TE air collector. The matrix inversion method is used to obtain energy balance equation. The effect of various parameters also investigated. The mass flow rate of range 0.01 kg/s to 0.05 kg/s and solar intensity of 400 W/m2, 600 W/m2 and 800 W/m2 was used to obtain outlet temperature, To in the range about 28.9oC to 43.7oC and PV temperature, Tp about 35.3oC to 60oC.
Heuristic Optimization Technique for CHP-Wind Power Dispatchidescitation
This paper applies Differential Evolution (DE) for
solving combined heat and power dispatch (CHP) problem with
wind turbines. The CHP economic dispatch problem consist
of two sub problems, namely, heat dispatch and power dispatch.
The optimal dispatch utilization of multiple CHP units and
wind turbines is a complicated problem due to the complex
constraints such as feasible operating regions created by
mutual dependence of heat and power. The uncertainty of
wind speed and wind power is modeled using the Weibull
probability distribution. Economic dispatch is carried out for
cost optimization with varying wind power. The proposed
method is able to handle all complex constraints very
effectively without any violations. The developed optimization
model is tested and validated on a study system from literature.
This paper presents a Stand-alone Hybrid Renewable Energy System (SHRES) as an alternative to fossil fuel based generators. The Photovoltaic (PV) panels and wind turbines (WT) are designed for the Malaysian low wind speed conditions with battery Energy Storage (BES) to provide electric power to the load. The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. The optimized hybrid system was examined in MATLAB using two case studies to find the optimum number of PV panels, wind turbines system and BES that minimizes the Loss of Power Supply Probability (LPSP) and Cost of Energy (COE). The hybrid power system was connected to the AC bus to investigate the system performance in supplying a rural settlement. Real weather data at the location of interest was utilized in this paper. The results obtained from the two scenarios were used to compare the suitability of the NSGA-II and MOPSO methods. The NSGA-II method is shown to be more accurate whereas the MOPSO method is faster in executing the optimization. Hence, both these methods can be used for techno-economic optimization of SHRES.
Combined heat and power - optimal power flow based on thermodynamic model wit...IJECEIAES
Oil fields produce associated petroleum and wet gas, which can be mixed with commercial natural gas as fuel. Associated petroleum and wet gas are a low cost, low quality fuel, whereas commercial natural gas is the opposite. Two parameters are affected by this mixture: the fuel cost and the power – steam output of gas turbine – heat recovery steam generators. This research develops a Unit Commitment and Optimal Power Flow model based on Mixed Integer Nonlinear Programming to optimize combined heat and power cost by considering the optimal mixture between associated petroleum - wet gas and commercial natural gas. A thermodynamic model is used to represent the performance of gas turbine – heat recovery steam generators when subjected to different fuel mixtures. The results show that the proposed model can optimize cost by determining the most efficient power – steam dispatch and optimal fuel mixture. Furthermore, the optimization model can analyse the trade-off between power system losses, steam demand and associated - wet gas utilization.
Optimal tuning of a wind plant energy production based on improved grey wolf ...journalBEEI
The tuning of optimal controller parameters in wind plant is crucial in order to minimize the effect of wake interaction between turbines. The purpose of this paper is to develop an improved grey wolf optimizer (I-GWO) in order to tune the controller parameters of the turbines so that the total energy production of a wind plant is increased. The updating mechanism of original GWO is modified to improve the efficiency of exploration and exploitation phase while avoiding trapping in local minima solution. A row of ten turbines is considered to evaluate the effectiveness of the I-GWO by maximizing the total energy production. The proposed approach is compared with original GWO and previously published modified GWO. Finally, I-GWO produces the highest total energy production as compared to other methods, as shown in statistical performance analysis.
The Development of an Application Conceived for the Design, Feasibility Study...IJECEIAES
Because of the rise in diesel and butane prices widely used for pumping, added to their negative impact on both Morocco's environment and trade balance, the use of renewable energies should sound obvious, practical and cost effective. This study offers the transformation of a traditional butane pumping system (BPS) and diesel pumping system (DPS), located on a farm nearby the city of Agadir, into an optimized solar pumping system (SPS). The suggested method is based on a techno-economic study according to the “Business-As-usual” scenario. As a first step, we have dimensioned our pumping system and chosen the elements that constitute it. As a second step, we carried out an economic analysis, based on the calculation of all costs, which makes it possible to ensure the viability of the components of our SPS over its life cycle and brought it to a discounted value. The processing of the different data is made possible thanks to the computer application “PVDesign” which we have developed. This application has allowed us to carry out a comparative study of several techniques of pumping systems. The result of the study is that the SPS beats the other systems at various levels, namely economic, environmental and technical.
Photovoltaic (PV) cell from solar energy is one of the most widely adopted renewable energy source and commercially available system that can be used in various applications. More appealing application of PV arrays used in thermoelectric (TE) device was it can convert solar thermal energy from temperature difference into electric energy to act as power generators. In this study, a theoretical model is developed by using conducting steady state energy analysis of a PVT-TE air collector. The matrix inversion method is used to obtain energy balance equation. The effect of various parameters also investigated. The mass flow rate of range 0.01 kg/s to 0.05 kg/s and solar intensity of 400 W/m2, 600 W/m2 and 800 W/m2 was used to obtain outlet temperature, To in the range about 28.9oC to 43.7oC and PV temperature, Tp about 35.3oC to 60oC.
Heuristic Optimization Technique for CHP-Wind Power Dispatchidescitation
This paper applies Differential Evolution (DE) for
solving combined heat and power dispatch (CHP) problem with
wind turbines. The CHP economic dispatch problem consist
of two sub problems, namely, heat dispatch and power dispatch.
The optimal dispatch utilization of multiple CHP units and
wind turbines is a complicated problem due to the complex
constraints such as feasible operating regions created by
mutual dependence of heat and power. The uncertainty of
wind speed and wind power is modeled using the Weibull
probability distribution. Economic dispatch is carried out for
cost optimization with varying wind power. The proposed
method is able to handle all complex constraints very
effectively without any violations. The developed optimization
model is tested and validated on a study system from literature.
This paper presents a Stand-alone Hybrid Renewable Energy System (SHRES) as an alternative to fossil fuel based generators. The Photovoltaic (PV) panels and wind turbines (WT) are designed for the Malaysian low wind speed conditions with battery Energy Storage (BES) to provide electric power to the load. The appropriate sizing of each component was accomplished using Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) techniques. The optimized hybrid system was examined in MATLAB using two case studies to find the optimum number of PV panels, wind turbines system and BES that minimizes the Loss of Power Supply Probability (LPSP) and Cost of Energy (COE). The hybrid power system was connected to the AC bus to investigate the system performance in supplying a rural settlement. Real weather data at the location of interest was utilized in this paper. The results obtained from the two scenarios were used to compare the suitability of the NSGA-II and MOPSO methods. The NSGA-II method is shown to be more accurate whereas the MOPSO method is faster in executing the optimization. Hence, both these methods can be used for techno-economic optimization of SHRES.
Optimal generation for wind-thermal power plant systems with multiple fuel so...IJECEIAES
In this paper, the combined wind and thermal power plant systems are operated optimally to reduce the total fossil fuel cost (TFFC) of all thermal power plants and supply enough power energy to loads. The objective of reducing TFFC is implemented by using antlion algorithm (ALA), particle swarm optimization (PSO) and Cuckoo search algorithm (CSA). The best method is then determined based on the obtained TFFC from the three methods as dealing with two study cases. Two systems with eleven units including one wind power plant (WPP) and ten thermal power plants are optimally operated. The two systems have the same characteristic of MFSs but the valve loading effects (VLEs) on thermal power plants are only considered in the second system. The comparisons of TFFC from the two systems indicate that CSA is more powerful than ALA and PSO. Furthermore, CSA is also superior to the two methods in terms of faster search process. Consequently, CSA is a powerful method for the problem of optimal generation for wind-thermal power plant systems with consideration of MFSs from thermal power plants.
Coordination of blade pitch controller and battery energy storage using firef...TELKOMNIKA JOURNAL
Utilization of renewable energy sources (RESs) to generate electricity is increasing significantly in recent years due to global warming situation all over the world. Among RESs type, wind energy is becoming more favorable due to its sustainability and environmentally friendly characteristics. Although wind power system provides a promising solution to prevent global warming, they also contribute to the instability of the power system, especially in frequency stability due to uncertainty characteristic of the sources (wind speed). Hence, coordinated controller between blade pitch controller and battery energy storage (BES) system to enhance the frequency performance of wind power system is proposed in this work. Firefly algorithm (FA) is used as optimization method for achieving better coordination. From the investigated test systems, the frequency performance of wind power system can be increased by applying the proposed method. It is noticeable that by applying coordinated controller between blade pitch angle controller and battery energy storage using firefly algorithm the overshoot of the frequency can be reduced up to -0.2141 pu and accelerate the settling time up to 40.14 second.
Free Download Link (Copy URL):
https://sites.google.com/view/varunpratapsingh/teaching-engagements
Unit-I
Part-1 Introduction
Power and energy, sources of energy, review of thermodynamic cycles related to power plants,
fuels and combustion, calculations.
Part-2 Variable Load Problem
Industrial production and power generation compared ideal and realized load curves, terms, and factors. Effect of variable load on power plan operation, methods of meeting the variable load problem.
Part-3 Power plant economics and selection Effect of plant type on costs, rates, fixed elements, energy elements, customer elements, and investor’s profit; depreciation and replacement, theory of rates. Economics of plant selection, other considerations in plant selection.
Impact of compressed air energy storage system into diesel power plant with w...IJECEIAES
The wind energy plays an important role in power system because of its renewable, clean and free energy. However, the penetration of wind power (WP) into the power grid system (PGS) requires an efficient energy storage systems (ESS). compressed air energy storage (CAES) system is one of the most ESS technologies which can alleviate the intermittent nature of the renewable energy sources (RES). Nyala city power plant in Sudan has been chosen as a case study because the power supply by the existing power plant is expensive due to high costs for fuel transport and the reliability of power supply is low due to uncertain fuel provision. This paper presents a formulation of security-constrained unit commitment (SCUC) of diesel power plant (DPP) with the integration of CAES and PW. The optimization problem is modeled and coded in MATLAB which solved with solver GORUBI 8.0. The results show that the proposed model is suitable for integration of renewable energy sources (RES) into PGS with ESS and helpful in power system operation management.
Optimal Configuration of Wind Farms in Radial Distribution System Using Parti...journalBEEI
Recently, a wide range of wind farm based distributed generations (DGs) are being integrated into distribution systems to fulfill energy demands and to reduce the burden on transmission corridors. The non-optimal configuration of DGs could severely affect the distribution system operations and control. Hence, the aim of this paper is to analyze the wind data in order to build a mathematical model for power output and pinpoint the optimal location. The overall objective is minimization of power loss reduction in distribution system. The five years of wind data was taken from 24o 44’ 29” North, 67o 35’ 9” East coordinates in Pakistan. The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. The result reveals that the proposed method helps in improving renewable energy near to load centers, reduce power losses and improve voltage profile of the system. Moreover, the validity and performance of the proposed model were also compared with other optimization algorithms.
Exergy analysis and igcc plant technology to improve the efficiency and to re...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
optimization of the managed electrical energy within a hybrid renewable energ...INFOGAIN PUBLICATION
Hybrid energy applications based on renewable energy sources are becoming more and more desirable every day. They have increased the economic attractiveness of renewable electric energy generation. Because of the sudden fluctuations of the load requirements, the main attribute of such Hybrid Systems is to be able to generate energy at any time by optimally using each source. In this article, we have proposed a combination between a sizing study and a control one for the aim of solving the complex optimization problem of finding the optimal combination of size and storage to make the best use of the renewable power generations and to become more independent of rising electricity costs. Additionally, an improvement in the induced optimization algorithm is introduced in this paper so as to compute the optimal size and the operation control of the system with the aim of minimizing as much as possible the cost while responding to the load energy requirements taking into account the environmental factors.
Multi-objective based economic environmental dispatch with stochastic solar-w...IJECEIAES
This paper presents an evolutionary based technique for solving the multi-objective based economic environmental dispatch by considering the stochastic behavior of renewable energy resources (RERs). The power system considered in this paper consists of wind and solar photovoltaic (PV) generators along with conventional thermal energy generators. The RERs are environmentally friendlier, but their intermittent nature affects the system operation. Therefore, the system operator should be aware of these operating conditions and schedule the power output from these resources accordingly. In this paper, the proposed EED problem is solved by considering the nonlinear characteristics of thermal generators, such as ramp rate, valve point loading (VPL), and prohibited operating zones (POZs) effects. The stochastic nature of RERs is handled by the probability distribution analysis. The aim of proposed optimization problem is to minimize operating cost and emission levels by satisfying various operational constraints. In this paper, the single objective optimization problems are solved by using particle swarm optimization (PSO) algorithm, and the multi-objective optimization problem is solved by using the multi-objective PSO algorithm. The feasibility of proposed approach is demonstrated on six generator power system.
Evaluation of the Energy Performance of the Amougdoul Wind Farm, Morocco IJECEIAES
This paper is concerned with the assessment of the the performance of the Amougdoul wind farm. We have determined the Weibull parameters; namely the scale parameter, c (m/s) and shape parameter, k. After that, we have estimated energy output by a wind turbine using two techniques: the useful power calculation method and the method based on the modeling of the power curve, which is respectively 134.5 kW and 194.19 KW corresponding to 27% and 39% of the available wind energy, which confirm that the conversion efficiency does not exceed 40%.
In this study, optimal economic load dispatch problem (OELD) is resolved by
a novel improved algorithm. The proposed modified moth swarm algorithm
(MMSA), is developed by proposing two modifications on the classical moth
swarm algorithm (MSA). The first modification applies an effective formula
to replace an ineffective formula of the mutation technique. The second
modification is to cancel the crossover technique. For proving the efficient
improvements of the proposed method, different systems with discontinuous
objective functions as well as complicated constraints are used. Experiment
results on the investigated cases show that the proposed method can get less
cost and achieve stable search ability than MSA. As compared to other
previous methods, MMSA can archive equal or better results. From this view,
it can give a conclusion that MMSA method can be valued as a useful method
for OELD problem.
Energy and exergy analysis for biomass co firing coal fuel based thermal powe...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Novel technique for maximizing the thermal efficiency of a hybrid pveSAT Journals
Abstract In this paper a comparison between numerical model and experimental work results for a fixed Photovoltaic/ Thermal (PV/T) hybrid system is presented. The simulation in this work is based on a numerical model in solving the equations and determining the Photovoltaic (PV) cells thermal characteristics using both MATLAB and COMSOL Multiphysics. COMSOL is simulating the electromagnetic waves produced by the Sun through solving Maxwell's equations in three dimensions using Finite Elements Methods (FEM) and the sun irradiance is assumed to be Gaussian distribution across the twelve mourning hours. Beside that an experimental work is presented depending on the results conjured from the theoretical experience used in Comsol Multiphysics. A Pulse Width Modulator (PWM) is used to control the solenoid valve operation. In addition to the above a thermal analysis for the fixed PV modules and the piping water is presented where the output water temperatures, rate of heat transfer, overall heat transfer coefficient and thermal efficiency are calculated. As a result, a significant enhancement in the total thermal efficiency is observed with acceptable increase in the output water temperature. Keywords: Cooling systems; DAQ; Hybrid; COMSOL MULTIPHYSICS; MATLAB; Solid work; Lab view.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Stochastic renewable energy resources integrated multi-objective optimal powe...TELKOMNIKA JOURNAL
The modern state of electrical system consists the conventional generating units along with the sources of renewable energy. The proposed article recommends a method for the solution of single and multi-objective optimal power flow, integrating wind and solar output energy with traditional coal-based generating stations. In the first part of the article, the two wind power plants and one solar PV power plants are incorporated with the thermal power plants. The optimal power flow problem of single and conflicting multi-objectives are taken with this scenario. The second part of the paper, solar power plant is replaced with another wind power plant with the conventional coal-based power plants. The techno-economic analysis are done with this state of electrical system. In proposed work, lognormal and weibull probability distribution functions are also utilized for predicting solar and wind outputs, respectively. A non-dominated multi-objective moth flame optimization technique is used for the optimization issue. The fuzzy decision-making approach is applied for extracting the best compromise solution. The results are validated though adapted IEEE-30 bus test system, which is incorporated with wind and solar generating plants.
Improved particle swarm optimization algorithms for economic load dispatch co...IJECEIAES
Economic load dispatch problem under the competitive electric market (ELDCEM) is becoming a hot problem that receives a big interest from researchers. A lot of measures are proposed to deal with the problem. In this paper, three versions of PSO method such as conventional particle swarm optimization (PSO), PSO with inertia weight (IWPSO) and PSO with constriction factor (CFPSO) are applied for handling ELDCEM problem. The core duty of the PSO methods is to determine the most optimal power output of generators to obtain total profit as much as possible for generation companies without violation of constraints. These methods are tested on three and ten-unit systems considering payment model for power delivered and different constraints. Results obtained from the PSO methods are compared with each other to evaluate the effectiveness and robustness. As results, IWPSO method is superior to other methods. Besides, comparing the PSO methods with other reported methods also gives a conclusion that IWPSO method is a very strong tool for solving ELDCEM problem because it can obtain the highest profit, fast converge speed and simulation time.
Optimal generation for wind-thermal power plant systems with multiple fuel so...IJECEIAES
In this paper, the combined wind and thermal power plant systems are operated optimally to reduce the total fossil fuel cost (TFFC) of all thermal power plants and supply enough power energy to loads. The objective of reducing TFFC is implemented by using antlion algorithm (ALA), particle swarm optimization (PSO) and Cuckoo search algorithm (CSA). The best method is then determined based on the obtained TFFC from the three methods as dealing with two study cases. Two systems with eleven units including one wind power plant (WPP) and ten thermal power plants are optimally operated. The two systems have the same characteristic of MFSs but the valve loading effects (VLEs) on thermal power plants are only considered in the second system. The comparisons of TFFC from the two systems indicate that CSA is more powerful than ALA and PSO. Furthermore, CSA is also superior to the two methods in terms of faster search process. Consequently, CSA is a powerful method for the problem of optimal generation for wind-thermal power plant systems with consideration of MFSs from thermal power plants.
Coordination of blade pitch controller and battery energy storage using firef...TELKOMNIKA JOURNAL
Utilization of renewable energy sources (RESs) to generate electricity is increasing significantly in recent years due to global warming situation all over the world. Among RESs type, wind energy is becoming more favorable due to its sustainability and environmentally friendly characteristics. Although wind power system provides a promising solution to prevent global warming, they also contribute to the instability of the power system, especially in frequency stability due to uncertainty characteristic of the sources (wind speed). Hence, coordinated controller between blade pitch controller and battery energy storage (BES) system to enhance the frequency performance of wind power system is proposed in this work. Firefly algorithm (FA) is used as optimization method for achieving better coordination. From the investigated test systems, the frequency performance of wind power system can be increased by applying the proposed method. It is noticeable that by applying coordinated controller between blade pitch angle controller and battery energy storage using firefly algorithm the overshoot of the frequency can be reduced up to -0.2141 pu and accelerate the settling time up to 40.14 second.
Free Download Link (Copy URL):
https://sites.google.com/view/varunpratapsingh/teaching-engagements
Unit-I
Part-1 Introduction
Power and energy, sources of energy, review of thermodynamic cycles related to power plants,
fuels and combustion, calculations.
Part-2 Variable Load Problem
Industrial production and power generation compared ideal and realized load curves, terms, and factors. Effect of variable load on power plan operation, methods of meeting the variable load problem.
Part-3 Power plant economics and selection Effect of plant type on costs, rates, fixed elements, energy elements, customer elements, and investor’s profit; depreciation and replacement, theory of rates. Economics of plant selection, other considerations in plant selection.
Impact of compressed air energy storage system into diesel power plant with w...IJECEIAES
The wind energy plays an important role in power system because of its renewable, clean and free energy. However, the penetration of wind power (WP) into the power grid system (PGS) requires an efficient energy storage systems (ESS). compressed air energy storage (CAES) system is one of the most ESS technologies which can alleviate the intermittent nature of the renewable energy sources (RES). Nyala city power plant in Sudan has been chosen as a case study because the power supply by the existing power plant is expensive due to high costs for fuel transport and the reliability of power supply is low due to uncertain fuel provision. This paper presents a formulation of security-constrained unit commitment (SCUC) of diesel power plant (DPP) with the integration of CAES and PW. The optimization problem is modeled and coded in MATLAB which solved with solver GORUBI 8.0. The results show that the proposed model is suitable for integration of renewable energy sources (RES) into PGS with ESS and helpful in power system operation management.
Optimal Configuration of Wind Farms in Radial Distribution System Using Parti...journalBEEI
Recently, a wide range of wind farm based distributed generations (DGs) are being integrated into distribution systems to fulfill energy demands and to reduce the burden on transmission corridors. The non-optimal configuration of DGs could severely affect the distribution system operations and control. Hence, the aim of this paper is to analyze the wind data in order to build a mathematical model for power output and pinpoint the optimal location. The overall objective is minimization of power loss reduction in distribution system. The five years of wind data was taken from 24o 44’ 29” North, 67o 35’ 9” East coordinates in Pakistan. The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. The result reveals that the proposed method helps in improving renewable energy near to load centers, reduce power losses and improve voltage profile of the system. Moreover, the validity and performance of the proposed model were also compared with other optimization algorithms.
Exergy analysis and igcc plant technology to improve the efficiency and to re...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
optimization of the managed electrical energy within a hybrid renewable energ...INFOGAIN PUBLICATION
Hybrid energy applications based on renewable energy sources are becoming more and more desirable every day. They have increased the economic attractiveness of renewable electric energy generation. Because of the sudden fluctuations of the load requirements, the main attribute of such Hybrid Systems is to be able to generate energy at any time by optimally using each source. In this article, we have proposed a combination between a sizing study and a control one for the aim of solving the complex optimization problem of finding the optimal combination of size and storage to make the best use of the renewable power generations and to become more independent of rising electricity costs. Additionally, an improvement in the induced optimization algorithm is introduced in this paper so as to compute the optimal size and the operation control of the system with the aim of minimizing as much as possible the cost while responding to the load energy requirements taking into account the environmental factors.
Multi-objective based economic environmental dispatch with stochastic solar-w...IJECEIAES
This paper presents an evolutionary based technique for solving the multi-objective based economic environmental dispatch by considering the stochastic behavior of renewable energy resources (RERs). The power system considered in this paper consists of wind and solar photovoltaic (PV) generators along with conventional thermal energy generators. The RERs are environmentally friendlier, but their intermittent nature affects the system operation. Therefore, the system operator should be aware of these operating conditions and schedule the power output from these resources accordingly. In this paper, the proposed EED problem is solved by considering the nonlinear characteristics of thermal generators, such as ramp rate, valve point loading (VPL), and prohibited operating zones (POZs) effects. The stochastic nature of RERs is handled by the probability distribution analysis. The aim of proposed optimization problem is to minimize operating cost and emission levels by satisfying various operational constraints. In this paper, the single objective optimization problems are solved by using particle swarm optimization (PSO) algorithm, and the multi-objective optimization problem is solved by using the multi-objective PSO algorithm. The feasibility of proposed approach is demonstrated on six generator power system.
Evaluation of the Energy Performance of the Amougdoul Wind Farm, Morocco IJECEIAES
This paper is concerned with the assessment of the the performance of the Amougdoul wind farm. We have determined the Weibull parameters; namely the scale parameter, c (m/s) and shape parameter, k. After that, we have estimated energy output by a wind turbine using two techniques: the useful power calculation method and the method based on the modeling of the power curve, which is respectively 134.5 kW and 194.19 KW corresponding to 27% and 39% of the available wind energy, which confirm that the conversion efficiency does not exceed 40%.
In this study, optimal economic load dispatch problem (OELD) is resolved by
a novel improved algorithm. The proposed modified moth swarm algorithm
(MMSA), is developed by proposing two modifications on the classical moth
swarm algorithm (MSA). The first modification applies an effective formula
to replace an ineffective formula of the mutation technique. The second
modification is to cancel the crossover technique. For proving the efficient
improvements of the proposed method, different systems with discontinuous
objective functions as well as complicated constraints are used. Experiment
results on the investigated cases show that the proposed method can get less
cost and achieve stable search ability than MSA. As compared to other
previous methods, MMSA can archive equal or better results. From this view,
it can give a conclusion that MMSA method can be valued as a useful method
for OELD problem.
Energy and exergy analysis for biomass co firing coal fuel based thermal powe...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Novel technique for maximizing the thermal efficiency of a hybrid pveSAT Journals
Abstract In this paper a comparison between numerical model and experimental work results for a fixed Photovoltaic/ Thermal (PV/T) hybrid system is presented. The simulation in this work is based on a numerical model in solving the equations and determining the Photovoltaic (PV) cells thermal characteristics using both MATLAB and COMSOL Multiphysics. COMSOL is simulating the electromagnetic waves produced by the Sun through solving Maxwell's equations in three dimensions using Finite Elements Methods (FEM) and the sun irradiance is assumed to be Gaussian distribution across the twelve mourning hours. Beside that an experimental work is presented depending on the results conjured from the theoretical experience used in Comsol Multiphysics. A Pulse Width Modulator (PWM) is used to control the solenoid valve operation. In addition to the above a thermal analysis for the fixed PV modules and the piping water is presented where the output water temperatures, rate of heat transfer, overall heat transfer coefficient and thermal efficiency are calculated. As a result, a significant enhancement in the total thermal efficiency is observed with acceptable increase in the output water temperature. Keywords: Cooling systems; DAQ; Hybrid; COMSOL MULTIPHYSICS; MATLAB; Solid work; Lab view.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Stochastic renewable energy resources integrated multi-objective optimal powe...TELKOMNIKA JOURNAL
The modern state of electrical system consists the conventional generating units along with the sources of renewable energy. The proposed article recommends a method for the solution of single and multi-objective optimal power flow, integrating wind and solar output energy with traditional coal-based generating stations. In the first part of the article, the two wind power plants and one solar PV power plants are incorporated with the thermal power plants. The optimal power flow problem of single and conflicting multi-objectives are taken with this scenario. The second part of the paper, solar power plant is replaced with another wind power plant with the conventional coal-based power plants. The techno-economic analysis are done with this state of electrical system. In proposed work, lognormal and weibull probability distribution functions are also utilized for predicting solar and wind outputs, respectively. A non-dominated multi-objective moth flame optimization technique is used for the optimization issue. The fuzzy decision-making approach is applied for extracting the best compromise solution. The results are validated though adapted IEEE-30 bus test system, which is incorporated with wind and solar generating plants.
Improved particle swarm optimization algorithms for economic load dispatch co...IJECEIAES
Economic load dispatch problem under the competitive electric market (ELDCEM) is becoming a hot problem that receives a big interest from researchers. A lot of measures are proposed to deal with the problem. In this paper, three versions of PSO method such as conventional particle swarm optimization (PSO), PSO with inertia weight (IWPSO) and PSO with constriction factor (CFPSO) are applied for handling ELDCEM problem. The core duty of the PSO methods is to determine the most optimal power output of generators to obtain total profit as much as possible for generation companies without violation of constraints. These methods are tested on three and ten-unit systems considering payment model for power delivered and different constraints. Results obtained from the PSO methods are compared with each other to evaluate the effectiveness and robustness. As results, IWPSO method is superior to other methods. Besides, comparing the PSO methods with other reported methods also gives a conclusion that IWPSO method is a very strong tool for solving ELDCEM problem because it can obtain the highest profit, fast converge speed and simulation time.
Improved backtracking search optimization algorithm for PV/Wind/FC systemTELKOMNIKA JOURNAL
This paper uses a novel optimization method based on the improved backtracking search optimization algorithm (IBSA). The study is conducted for a hybrid stand-alone system composed of photovoltaic panel (PV), wind turbine generator and fuel cell electrolyzer (FC). To demonstrate the effectiveness of the IBSA, four benchmark functions are used. The result shows the better exploration and exploitation of the improved backtracking search optimization algorithm in terms of convergence and speed for system comprinsing PV panel wind, turbine generator and fuel cell. The proposed algorithm is used to optimize the annual total cost (ATC) of the energy produced and feed up the load demand. The economic evaluation of the Hybrid PV/Wind/FC system is done throughout hourly demand and daily wind speed and insulation. The simulation results justify the robustness of the IBSA.
Sizing Optimization of Stand-Alone Wind Power System Using Hybrid Energy Stor...ijsrd.com
In this study, the hydrogen production potential and costs by using wind/electrolysis system were considered. In order to evaluate costs and quantities of produced hydrogen, number of wind-turbines and hub heights are considered as the variable Levelized cost of electricity method was used in order to determine the cost analysis of wind energy and hydrogen production. The results of calculations brought out that the electricity costs of the wind turbines and hydrogen production costs of the electrolyzers are decreased with the increase of turbine hub height. The maximum hydrogen production quantity was obtained 1420KWh/year.
Statistical modeling and optimal energy distribution of cogeneration units b...IJECEIAES
Our main objective is to evaluate the performance of a new method to optimize the energy management of a production system composed of six cogeneration units using artificial intelligence. The optimization criterion is economic and environmental in order to minimize the total fuel cost, as well as the reduction of polluting gas emissions such as COx, NOx and SOx. First, a statistical model has been developed to determine the power that the cogeneration units can provide. Then, an economic model of operation was developed: fuel consumption and pollutant gas emissions as a function of the power produced. Finally, we studied the energy optimization of the system using genetic algorithms (GA), and contribute to the research on improving the efficiency of the studied power system. The GA has a better optimization performance, it can easily choose satisfactory solutions according to the optimization objectives, and compensate for these defects using its own characteristics. These characteristics make GA have outstanding advantages in iterative optimization. The robustness of the proposed algorithm is validated by testing six cogeneration units, and the obtained simulation results of the proposed system prove the value and effectiveness of GA for efficiency improvement as well as operating cost minimization.
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.
Power system operation considering detailed modelling of the natural gas supp...IJECEIAES
The energy transition from fossil-fuel generators to renewable energies represents a paramount challenge. This is mainly due to the uncertainty and unpredictability associated with renewable resources. A greater flexibility is requested for power system operation to fulfill demand requirements considering security and economic restrictions. In particular, the use of gas-fired generators has increased to enhance system flexibility in response to the integration of renewable energy sources. This paper provides a comprehensive formulation for modeling a natural gas supply network to provide gas for thermal generators, considering the use of wind power sources for the operation of the electrical system over a 24-hour period. The results indicate the requirements of gas with different wind power level of integration. The model is evaluated on a network of 20 NG nodes and on a 24-bus IEEE RTS system with various operative settings during a 24-hour period.
Low cost, high performance fuel cell energy conditioning system controlled by...TELKOMNIKA JOURNAL
Fuel cells are an important option for the generation of renewable, efficient and environmentally friendly electricity. Although there are commercial applications in the industrial, residential and automotive sectors, it is not yet a mature technology and requires much research, particularly to reduce its costs to a level competitive with other technologies. This research is currently focused not only on the structure of the cell but also on the additional elements and sub systems required for its implementation as an energy solution. In this article, we propose an electrical energy conditioning scheme for the Formic acid fuel cell (direct formic acid fuel cellor DFAFC). This fuel cell was selected for its high performance, and low cost in low and medium power applications. The proposed system consists of a direct current-direct current (DC-DC) regulator supported by a power converter controlled by a Cortex-M3 ARM processor. This CPU is used to propagate a static neural network trained with the non-linear dynamics of the power converter. The power circuit is modeled and simulated to produce the training parameters. The neural network is trained externally and runs off-line on the processor. The results show not only the regulation capacity of the control scheme but also its response speed to sudden changes in the load.
Study and Dimensioning of the Tanks Dedicated to a Compressed Air Energy Stor...IJECEIAES
The fundamental idea of storage is to transfer available energy During periods of low demand , using only a fraction of the fuel that would be consumed by the standard production machine (gas turbine, thermal engine, etc.). The main role of energy storage is therefore to introduce an energy degree of freedom to decouple Consumers and the producer by supplying or Delivering the difference between these two powers. In this paper is this paper presents a brief study and dimensioning of compressed air storage tanks to a hybrid system wind-PV. adopts the CAES system as a storage agent. starting with the technical criteria on which the choice of reservoirs is based and the mechanical constraints that must be taken into consideration for dimensioning of the reservoirs
Optimal load management of autonomous power systems in conditions of water sh...IJECEIAES
The issues of optimizing the operation of micro hydropower plants in conditions of water scarcity, performed by additional connection to the grid of an energy storage system and wind power turbine, as well as optimal load management, are considered. It is assumed that the load of the system is a concentrated autonomous power facility that consumes only active power. The paper presents a rigorous mathematical formulation of the problem, the solution of which corresponds to the minimum cost of an energy storage system and a wind turbine, which allows for uninterrupted supply of electricity to power facilities in conditions of water shortage necessary for the operation of micro hydropower plants (under unfavorable hydrological conditions). The problem is formulated as a nonlinear multi-objective optimization problem to apply metaheuristic stochastic algorithms. At the same time, a significant part of the problem is taken out and framed as a subproblem of linear programming which will make it possible to solve it by a deterministic simplex method that guarantees to find the exact global optimum. This approach will significantly increase the efficiency of solving the entire problem by combining metaheuristic algorithms and taking into account expert knowledge about the problem being solved.
Implementation effects of economics and market operations based model for tra...nooriasukmaningtyas
The main objective of this paper is to introduce power system economic operations in traditionally integrated power systems and market operations in deregulated power systems and study its effects. The power system economic operation is mathematically treated as an optimization problem. Also, a function of economic operation is to minimize generation cost, transmission losses, and so on, subject to power system operation constraints. In this paper, we start from generation cost formulations and introduce traditional economic dispatch model, optimal power flow model, and unit commitment model. With the deregulation of the power industry, integrated power system is unbundled to generation, transmission, and distribution. Electricity is traded in the wholesale market. Small customers purchase energy from electricity retailers through the retail market. The electricity market is operated for energytrading while satisfying power system operation requirements. Electricity market is mathematically modelled as an optimization problem that is subject to power system operation constraints and market operation constraints.
Experimental study on transient response of fuel celljournalBEEI
This research work discusses a control strategy to enhance the transient response of the fuel cell and boost the real and reactive power flow from grid connected to fuel cell. The current output of the fuel cell depends on the availability of hydrogen in the fuel cell stack, a battery bank is implemented to supply the transient current and to prevent it from hydrogen saturation. The battery should only supply when there is a transient. During steady state the total power is produced by the fuel cell by regulating its hydrogen input. A prototype of the system will be created to study a control scheme which regulates the current from an input source and a battery which is connected to a dc motor. The control philosophy is based on d-q transformation and subsequently generating a reference signal that is tracked by an IGBT based inverter. The speed of the motor is controlled using pulse with modulation. The dynamic modeling of the standalone fuel cell that is connected to a dc motor is carried out using MATLAB/SIMULINK platform. The simulation results show that the control scheme works well, although the dynamic response of the system can be improved. The testing carried on the prototype proves that the concept works well, but a hydrogen control scheme should be developed to improve the efficiency of the control scheme.
PuShort Term Hydrothermal Scheduling using Evolutionary Programmingblished pa...Satyendra Singh
In this paper, Evolutionary Programming method
is used for short term hydrothermal scheduling which minimize
the total fuel cost while satisfying the constraints. This paper
developed and studies the performance of evolutionary programs
in solving hydrothermal scheduling problem. The effectiveness of
the developed program is tested for the system having one hydro
and one thermal unit for 24 hour load demand. Numerical results
show that highly near-optimal solutions can be obtained by
Evolutionary Programming.
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.
Environmental factors such as air pollution and increase in global warming by using polluting fuels are the most important reasons of using renewable and clean energy that runs in global community. Wind energy is one of the most suitable and widely used kind of renewable energy which had been in consideration so well. This paper introduces an electric power generation
system of wind based on Y-source and improved Y-source inverter to deliver optimal electrical power to the network. This new converter is from impedance source converters family. This presented converter has more degrees of freedom to adjust voltage gain and modulation. Also, by limiting the range of simultaneous control (shooting through) while it maintains the
highest power of maximizer, it can operate in higher modulation range. This causes the reduce of stress in switching and thus it will improve the quality of output. Recommended system had been simulated in MATLAB/Simulink and shown results indicate accurate functionality.
The energy costs of a power plant consist of startup cost and cost of power usage. In contrast to
the existing literature, this study introduces at startup cost based on the duration of thermal power plant
downtime. The approach of startup cost function in this research is done by using startup type. Startup of a
steam power plant depends on its condition. Generally, there are three types of startup the power plant
when the turbine temperature is still very high, i.e. hot start, very hot start and very-very hot start. This
paper uses multistage optimization to solve the problem of hydrothermal scheduling with including the
startup type cost in the objective function. The simulation results showed operating cost savings when the
objective function for optimization also consider the cost based on startup type i.e. when compared with
the optimization result which the objective function does not take the cost of startup type.
Optimal Unit Commitment Based on Economic Dispatch Using Improved Particle Sw...paperpublications3
Abstract: In this paper, an algorithm to solve the optimal unit commitment problem under deregulated environment has been proposed using Particle Swarm Optimization (PSO) intelligent technique accounting economic dispatch constraints. In the present electric power market, where renewable energy power plants have been included in the system, there is a lot of unpredictability in the demand and generation. This paper presents an improved particle swarm optimization algorithm (IPSO) for power system unit commitment with the consideration of various constraints. IPSO is an extension of the standard particle swarm optimization algorithm (PSO) which uses more particles information to control the mutation operation, and is similar to the social society in that a group of leaders could make better decisions. The program was developed in MATLAB and the proposed method implemented on IEEE 14 bus test system.
Similar to Optimal power generation for wind-hydro-thermal system using meta-heuristic algorithms (20)
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
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Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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PHk,min, PHk,max Minimum and maximum power generation of the kth hydro unit
xSol ,
new
xSol The xth current solution and new solution
xFit ,
new
xFit Fitness function the the xth current and new solution
1. INTRODUCTION
Hydrothermal system scheduling (HTSS) problem is a very important problem in optimization
operation of power systems where hydropower plants and thermal plants are accounting for a high rate of all
power sources in exiting power systems [1]. In general, hydropower plants use water in river to drive turbines
and run generators for producing electricity to loads while thermal power plants must employ fossil fuel such
as gas, oil and coal to drive gas turbines or steam turbines for generating electricity. Water can be exhausted
and full in rivers dependent on weather, namely rain and sun in seasons [2]. On the contrary, fossil fuels
cannot be recovered after using. As a result, cost of generating electricity or price of fossil fuels in thermal
power plants is a significant issue but cost of water in hydropower plants is normally ignored. Main issues
regarding hydropower plants are hydraulic constraints such as discharge limit, spillage, flood, and reservoir
limits. So, in hydropower system scheduling problem, the most difficulty issue is to solve the hydraulic
constraints successfully while the main target is to reduce cost of generating electricity in thermal power
plants [3].
Basically, hydrothermal system scheduling problem can be divided into short-term [1-10],
medium-term [11-15] and long-term models [16-20] based on the time period of scheduled optimization.
Short-term HTSS problem is classified into fixed-head model [1-7] and variable head model [8-10], and this
problem was also the most attracted problem among three different time period types. The main difference of
the problems is scheduled time period. Short-term HTSS problem considers one day to one week while
long-term HTSS considers over one year with twelve months or four seasons. The time from one week to one
month or from one month to one season is taken into account in medium-term HTSS problem. The three
problems have the same characteristic that is to consider cost of producing electricity in thermal power plants
as an objective and neglect cost in hydropower plants. In addition, renewable energies like solar energy and
wind energy are not considered in the problem.
In recent years, wind turbines have been considered in conventional power systems with
hydrothermal plants. The optimal generation between these thermal plants and these wind turbines was
successfully solved by using metaheuristic algorithms like bee colony algorithm (BCA) [21] and Wait-See
algorithm (WSA) [22]. Then, the integrated system was expanded by adding hydropower plants and
the optimal generation of the wind-hydro-thermal system were solved by using nondominated sorting genetic
algorithm-III (NSGA-III) [23], multi-objective bee colony optimization algorithm (MOBCOA) [24],
two-stage stochastic method (TSSM) [25] and sine-cosine algorithm (SCA) [26]. In [23], multi objective
functions including fuel cost and power loss are considered in which power generation of wind farms is
considered as a control variable of the combined system. In [24], uncertainty of wind speed was considered
by considering Weibull distribution function. In the study, wind turbines are calculated three cost, direction
cost, reserve cost and penalty cost. In [25-26], cascaded hydropower plants are considered together with
the power generation of thermal power plants and wind turbines. Similar to [24], the two studies also
considered the Weibull function and three costs of wind turbines. In general, almost all studies applied
metaheuristics and mainly focused on the highly successful constraint handling ability of rather than reaching
the best solutions for the problem. In addition, power loss of the system due to the impact of resistance and
reactance of conductors was not considered in these studies. This is also understood because these studies
were first application of methods for solving the new problem.
In this paper, short-term HTSS problem with fixed-head model is expanded by adding wind turbines
and considering operation range of them. On the contrary to other studies, all constraints of hydropower
plants are taken into account including discharge limit, available water and generator limits. Thermal power
plants are not constrained by available fossil fuel quantity but generators. Wind turbines are constrained
by capacity and operation wind speeds. The main purpose is to calculate cost of thermal power plants
and determine the most optimal generation for reducing this cost. For reaching the optimal solutions of
the problem, we apply PSO (PSO) [27], CFIWPSO [28], SSD [29] and CSA [30].
In summary, the contributions of the paper are follows:
- Develop wind-hydrothermal system scheduling problem with short-term model
- Propose the best decision variable selection method
- Investigate performance of PSO, FCIW-PSO, SSD and CSA
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2. FORMULATION OF OPTIMAL SCHEDULING OF WIND-HYDRO-THERMAL SYSTEM
In the section, a wind-hydrothermal system with fixed head model is in detail described by using
figure and formulas. Figure 1 shows a system with one thermal power plant, one hydropower plant and one
wind farm located at load. The objective and constraints as well as assumption of the problem are as follows:
Wind turbine
Load
~
Fuel
~
Hydropower plant
Thermal power plant
Figure 1. A typical wind-hydro-thermal system
2.1. Objective function
Total fuel cost (TFC) for generating electricity from all thermal power plants is considered as
a major part that needs to be minimized as much as possible. The objective is shown as follows:
𝑀𝑖𝑛𝑖𝑚𝑖𝑧𝑒 𝑇𝐹𝐶 = ∑ ∑ (𝑘𝑖 + 𝑚𝑖 𝑃𝑇𝑖,𝑗 + 𝑛𝑖(𝑃𝑇𝑖,𝑗)
2
)
𝑁 𝑖𝑛
𝑗=1
𝑁 𝑡𝑝
𝑖=1
(1)
In (1), we only focus on the reduction of fuel cost from thermal power plants meanwhile the electric
generation cost from hydropower plants and wind power plants is neglected. The assumption of neglecting
the electric cost from hydroelectric plant is taken from the idea that water is a nature source with very low
price whereas all power energy from wind power plants is absolutely used with the same price and the same
cost over one scheduled day.
2.2. The set of constraints
a. Constraints from power system
In power systems, the balance between the generated and consumed power must be guaranteed as
the following model:
∑ 𝑃𝑇𝑖,𝑗
𝑁 𝑡𝑝
𝑖=1
∑ 𝑃𝐻 𝑘,𝑗 + ∑ 𝑃𝑊 𝑤,𝑗
𝑁 𝑤𝑡
𝑤=1
− 𝑃𝐿𝑜𝑎𝑑,𝑗 − 𝑃𝐿𝑜𝑠𝑠,𝑗 = 0
𝑁ℎ𝑝
𝑘=1
(2)
b. Constraint from thermal plants
Power generation of thermal power plants is limited as follows:
𝑃𝑇𝑖,𝑚𝑖𝑛 ≤ 𝑃𝑇𝑖,𝑗 ≤ 𝑃𝑇𝑖,𝑚𝑎𝑥 (3)
c. Constraint from wind turbines
Basically, power generation of a wind turbine is much dependent on wind speed. The range of
generation can be seen by the following equation [25]:
𝑃𝑊𝑤 =
{
0, (𝑊𝑉 < 𝑊𝑉𝑐𝑢𝑡−𝑖𝑛 𝑎𝑛𝑑 𝑊𝑉 > 𝑊𝑉𝑐𝑢𝑡−𝑜𝑢𝑡)
𝑃𝑊 𝑤,𝑟𝑎𝑡𝑒 ×
(𝑊𝑉 − 𝑊𝑉𝑐𝑢𝑡−𝑖𝑛)
(𝑊𝑉𝑟𝑎𝑡𝑒 − 𝑊𝑉𝑐𝑢𝑡−𝑖𝑛)
, (𝑊𝑉𝑐𝑢𝑡−𝑖𝑛 ≤ 𝑊𝑉 ≤ 𝑊𝑉𝑟𝑎𝑡𝑒)
𝑃𝑊 𝑤,𝑟𝑎𝑡𝑒 (𝑊𝑉𝑟𝑎𝑡𝑒 ≤ 𝑊𝑉 ≤ 𝑊𝑉𝑐𝑢𝑡−𝑜𝑢𝑡)
(4)
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So, wind turbines are also constrained by power generation as follows:
𝑃𝑊 𝑤,𝑚𝑖𝑛 ≤ 𝑃𝑊 𝑤,𝑗 ≤ 𝑃𝑊𝑤,𝑚𝑎𝑥 (5)
d. Constraints from hydropower plants:
Limits of water Discharge: Water that is discharged through a turbine must be in a predetermined
range as follows:
𝑄 𝑘,𝑚𝑖𝑛 ≤ 𝑄 𝑘,𝑗 ≤ 𝑄 𝑘,𝑚𝑎𝑥 (6)
where Qk,j is determined as follows:
𝑄 𝑘,𝑗 = 𝑋 𝑘 + 𝑌𝑘 𝑃𝐻 𝑘,𝑗 + 𝑍 𝑘(𝑃𝐻𝑘,𝑗)
2
(7)
In addition, the total water discharge over Nin intervals must be equal to available as the constraint below:
∑ 𝑄 𝑘,𝑗
𝑁 𝑖𝑛
𝑗=1
= 𝑊𝑎𝑣𝑎𝑖,𝑘 (8)
e. Constraint of generators: Hydro generation is constrained by.
𝑃𝐻 𝑘,𝑚𝑖𝑛 ≤ 𝑃𝐻𝑘,𝑗 ≤ 𝑃𝐻𝑘,𝑚𝑎𝑥 (9)
3. CUCKOO SEARCH ALGORITHM
3.1. New solution generation mechanism
On the contrary to PSO and SSD, CSA performs two mechanisms to produce new solutions.
For each mechanism, the whole population is newly updated. So, total new solutions generated by CSA is
two times that of PSO and SSD. Lévy flights is applied in the first mechanism while mutation operation is
employed in the second one. The two mechanisms are mathematically formulated as follows:
0
new
x x x BestSol Sol Sol Sol L (10)
1 1 2 2xnew
x
x
Sol rd Sol Sol if rd Pro
Sol
Sol otherwise
(11)
where α0 is a positive scaling factor; L (β) is Lévy distribution function [10]; and SolBest is the so-far best
solution among the current population; rd1 and rd2 are random numbers in the range between 0 and 1; Pro is
old solution replacement probability, which is selected within 0 and 1. Sol1 and Sol2 are two randomly
selected solutions.
3.2. Promising solution selection mechanism
This mechanism is applied to performance comparison of quality between the new xth solution and
the old xth solution to retain a better solution and abandon a worse one. So, fitness function must be
calculated for each old and new solution. Then, the following model is applied.
new
x x x
x new
x
Sol if Fit Fit
Sol
Sol Otherwise
(12)
4. RESULTS NUMERICAL RESULTS
In this section, the effectiveness of CSA is compared to that of PSO, CFIW-PSO and SSD on
the system with one thermal power plant, one hydropower plant and one wind power plant. The system is
scheduled over twenty-four one-hour intervals. The hydrothermal systems and loss coefficients are taken
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from Table A1 in page 284 [10] while the wind farm data is taken from wind farm 1 in Table 6 in page
760 [31]. The whole data and loss coefficients are shown in Table A1, Table A2 and Table A3 in Appendix.
The four methods are coded on Matlab program language and a computer with CPU of Intel Core
i7-2.4GHz-RAM 4GB for obtaining 50 successful runs.
In order to run these methods, population size (PS) and the maximum iteration (MI) are set to 20 and
2000 for CSA, 40 and 2000 for PSO, CFIW-PSO and SSD. The results from 50 successful runs are
summarized in Table 1 in addition to saving cost and improvement shown in Figures 2 and 3. In the two
figures, saving cost and the corresponding improvement level of CSA as compared to PSO, CFIW-PSO and
SSD are shown. So, there is no bar to show the result of CSA in the two figures. From the figures, it can
indicate that as compared to other methods CSA can reach very high reduction of minimum cost with
$6029.58, mean cost with $7576.37 and maximum cost with $9305.77 the reduction cost of CSA is
corresponding to the improvement level of 8%, 0.94% and 2.1% over PSO, CFIW-PSO and SSD. Similarly,
the mean cost and the highest cost of CSA are also much less than other methods. The improvement level of
mean cost and the highest cost can be up to 4% and 9.8%.
Table 1. Summary of results
PSO CFIW-PSO SSD CSA
Minimum cost ($) 75789.64 70420.13 71236.93 69760.06
Average cost ($) 77362.83 72718.63 73327.8 69786.46
Maximum cost ($) 79306.06 75847.33 77212.04 70000.29
Standard deviation ($) 729.5481 1438.077 1366.289 41.4461
Success rate (%) 848/50 86/50 107/50 50/50
Figure 2. Saving cost of CSA as compared to PSO, CFIW-PSO and SSD
Figure 3. Improvement of CSA over PSO, CFIW-PSO and SSD
6029,58
7576,37
9305,77
688,102
660,07
2932,17
5847,04
1396,6309
1476,87
3541,34
7211,75
1324,8429
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
Minimum cost
($)
Average cost
($)
Maximum cost
($)
Standard
deviation ($)
SavingCostofCSA($)
PSO
CFIW-PSO
SSD
8,0 9,8 11,7
94,3
0,9 4,0 7,7
97,1
2,1 4,8 9,3
97,0
0,0
20,0
40,0
60,0
80,0
100,0
120,0
Minimum cost (%) Average cost (%) Maximum cost (%) Standard deviation
(%)
Improvemetn(%)
PSO CFIW-PSO SSD
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In addition, the best run, the mean run, the worst run and the cost of 50 runs can be observed from
Figures 4-7. The figures indicate that CSA is always the best method with the fastest speed and all better
runs. Consequently, it leads to a conclusion that CSA is the best method for the first system. Optimal power
generation obtained by CSA is shown in Figure 8.
Figure 4. The best convergence characteristic of
four applied methods
Figure 5. The mean convergence characteristic over
50 successful runs of four applied methods
Figure 6. The worst convergence characteristic of
four applied methods
Figure 7. Fuel cost of 50 successful runs obtained by
four applied methods
Figure 8. Optimal power generation obtained by CSA
5. CONCLUSION
In this paper, four applied methods including CSA, PSO, FCIW-PSO and SSD have been applied
for solving combined wind turbine and hydrothermal systems. The four method have been implemented for
reaching 50 successful runs for comparisons. Numerical results including the best cost, mean cost and
maximum cost in addition to graphical results including convergence characteristics have been analyzed for
evaluating performance of these methods. CSA was superior to three other ones in finding the best solution,
reach very high success rate and faster speed. So, it can be concluded that CSA is a very efficient method for
determining optimal parameters of combined wind turbines and hydrothermal systems.
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APPENDIX
Table A1. Data of thermal power plant
k1 m1 n1 PT1,min (MW) PT1,max (MW)
373.7 9.606 0.001991 0 505
Table A2. Data of hydroelectric plant
X1 Y1 Z1 Wavai,1 PH1,min (MW) PH1,max (MW)
61.53 -0.009079 0.0007749 2559.6 0 300
The loss coefficient matrix of the system
0.000150.00001
0.000010.00005
B
Table A3. Load and wind power over 24 one-hour intervals
j 𝑃𝐿𝑜𝑎𝑑,𝑗 𝑃𝑊1,𝑗 j 𝑃𝐿𝑜𝑎𝑑,𝑗 𝑃𝑊1,𝑗 j 𝑃𝐿𝑜𝑎𝑑,𝑗 𝑃𝑊1,𝑗
1 455 99 9 665 94.8 17 721 105
2 425 108 10 675 86.4 18 740 91.2
3 415 93 11 695 120 19 700 78
4 407 82.8 12 705 99 20 678 82.8
5 400 90 13 580 111.6 21 630 114
6 420 106.8 14 605 109.2 22 585 120
7 487 81.6 15 616 111 23 540 92.4
8 604 93 16 653 81 24 503 96
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