International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Economic dispatch by optimization techniquesIJECEIAES
The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic approaches are introduced, the BA and ALOA. A rigorous stochastically developmental computing strategy focused on the action and intellect of ant lions is an ALOA. The ALOA imitates ant lions' hunting process. The introduction of a numerical description of its biological actions for the solution of ED in the power framework. These algorithms are applied to two systems: a small scale three generator system and a large scale six generator. Results show were compared on the metrics of convergence rate, cost, and average run time that the ALOA and BA are suitable for economic dispatch studies which is clear in the comparison set with other algorithms. Both of these algorithms are tested on IEEE-30 bus reliability test system.
Solving combined economic emission dispatch problem in wind integrated power ...nooriasukmaningtyas
A meta-heuristic based optimization method for solving combined economic
emission dispatch (CEED) problem for the power system with thermal and
wind energy generating units is proposed in this paper. Wind energy is
environmentally friendly and abundantly available, but the intermittency and
variability of wind power affects the system operation. Therefore, the system
operator (SO) must aware of wind forecast uncertainty and dispatch the wind
power accordingly. Here, the CEED problem is solved by including the
nonlinear characteristics of thermal generators, and the stochastic behavior of
wind generators. The stochastic nature of wind generators is handled by
using probability distribution analysis. The purpose of this CEED problem is
to optimize fuel cost and emission levels simultaneously. The proposed
problem is changed into a single objective optimization problem by using
weighted sum approach. The proposed problem is solved by using particle
swarm optimization (PSO) algorithm. The feasibility of proposed
methodology is demonstrated on six generator power system, and the
obtained results using the PSO approach are compared with results obtained
from genetic algorithm (GA) and enhanced genetic algorithms (EGA).
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Economic Dispatch using Quantum Evolutionary Algorithm in Electrical Power S...IJECEIAES
Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Quantum behaved artificial bee colony based conventional controller for opti...IJECEIAES
Since a multi area system (MAS) is characterized by momentary overshoot, undershoot and intolerable settling time so, neutral copper conductors are replaced by multilayer zigzag graphene nano ribbon (MLGNR) interconnects that are tremendously advantageous to copper interconnects for the future transmission line conductors necessitated for economic and emission dispatch (EED) of electric supply system giving rise to reduced overshoots and settling time and greenhouse effect as well. The recent work includes combinatorial algorithm involving proportional integral and derivative controller and heuristic swarm optimization; we say it as Hybridparticle swarm optimization (PSO) controller. The modeling of two multi area systems meant for EED is carried out by controlling the conventional proportional integral and derivative (PID) controller regulated and monitored by quantum behaved artificial bee colony (ABC) optimization based PID (QABCOPID) controller in MATLAB/Simulink platform. After the modelling and simulation of QABCOPID controller it is realized that QABCOPID is better as compared to multi span double display (MM), neural network based PID (NNPID), multi objective constriction PSO (MOCPSO) and multi objective PSO (MOPSO). The real power generation fixed by QABCOPID controller is used to estimate the combined cost and emission objectives yielding optimal solution, minimum losses and maximum efficiency of transmission line.
A Review on Various Techniques Used for Economic Load Dispatch in Power Systemijtsrd
Electrical power plays a pivotal role in the modern world to satisfy various needs. It is therefore very important that the electrical power generated is transmitted and distributed efficiently in order to satisfy the power requirement. The Economic Load Dispatch ELD problem is the most significant problem of optimization in forecasting the generation amongst thermal generating units in power system. Pankaj Verma | Manish Prajapati "A Review on Various Techniques Used for Economic Load Dispatch in Power System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49830.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/49830/a-review-on-various-techniques-used-for-economic-load-dispatch-in-power-system/pankaj-verma
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Economic dispatch by optimization techniquesIJECEIAES
The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic approaches are introduced, the BA and ALOA. A rigorous stochastically developmental computing strategy focused on the action and intellect of ant lions is an ALOA. The ALOA imitates ant lions' hunting process. The introduction of a numerical description of its biological actions for the solution of ED in the power framework. These algorithms are applied to two systems: a small scale three generator system and a large scale six generator. Results show were compared on the metrics of convergence rate, cost, and average run time that the ALOA and BA are suitable for economic dispatch studies which is clear in the comparison set with other algorithms. Both of these algorithms are tested on IEEE-30 bus reliability test system.
Solving combined economic emission dispatch problem in wind integrated power ...nooriasukmaningtyas
A meta-heuristic based optimization method for solving combined economic
emission dispatch (CEED) problem for the power system with thermal and
wind energy generating units is proposed in this paper. Wind energy is
environmentally friendly and abundantly available, but the intermittency and
variability of wind power affects the system operation. Therefore, the system
operator (SO) must aware of wind forecast uncertainty and dispatch the wind
power accordingly. Here, the CEED problem is solved by including the
nonlinear characteristics of thermal generators, and the stochastic behavior of
wind generators. The stochastic nature of wind generators is handled by
using probability distribution analysis. The purpose of this CEED problem is
to optimize fuel cost and emission levels simultaneously. The proposed
problem is changed into a single objective optimization problem by using
weighted sum approach. The proposed problem is solved by using particle
swarm optimization (PSO) algorithm. The feasibility of proposed
methodology is demonstrated on six generator power system, and the
obtained results using the PSO approach are compared with results obtained
from genetic algorithm (GA) and enhanced genetic algorithms (EGA).
Optimal power flow based congestion management using enhanced genetic algorithmsIJECEIAES
Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.
Economic Dispatch using Quantum Evolutionary Algorithm in Electrical Power S...IJECEIAES
Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Quantum behaved artificial bee colony based conventional controller for opti...IJECEIAES
Since a multi area system (MAS) is characterized by momentary overshoot, undershoot and intolerable settling time so, neutral copper conductors are replaced by multilayer zigzag graphene nano ribbon (MLGNR) interconnects that are tremendously advantageous to copper interconnects for the future transmission line conductors necessitated for economic and emission dispatch (EED) of electric supply system giving rise to reduced overshoots and settling time and greenhouse effect as well. The recent work includes combinatorial algorithm involving proportional integral and derivative controller and heuristic swarm optimization; we say it as Hybridparticle swarm optimization (PSO) controller. The modeling of two multi area systems meant for EED is carried out by controlling the conventional proportional integral and derivative (PID) controller regulated and monitored by quantum behaved artificial bee colony (ABC) optimization based PID (QABCOPID) controller in MATLAB/Simulink platform. After the modelling and simulation of QABCOPID controller it is realized that QABCOPID is better as compared to multi span double display (MM), neural network based PID (NNPID), multi objective constriction PSO (MOCPSO) and multi objective PSO (MOPSO). The real power generation fixed by QABCOPID controller is used to estimate the combined cost and emission objectives yielding optimal solution, minimum losses and maximum efficiency of transmission line.
A Review on Various Techniques Used for Economic Load Dispatch in Power Systemijtsrd
Electrical power plays a pivotal role in the modern world to satisfy various needs. It is therefore very important that the electrical power generated is transmitted and distributed efficiently in order to satisfy the power requirement. The Economic Load Dispatch ELD problem is the most significant problem of optimization in forecasting the generation amongst thermal generating units in power system. Pankaj Verma | Manish Prajapati "A Review on Various Techniques Used for Economic Load Dispatch in Power System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49830.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/49830/a-review-on-various-techniques-used-for-economic-load-dispatch-in-power-system/pankaj-verma
Evolutionary algorithm solution for economic dispatch problemsIJECEIAES
A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints, these include the practical operation constraints of the generators (such as the forbidden working areas, nonlinear limits, and generation limits) that makes the calculation of the global optimal solutions of ED a difficult task. The proposed approach in this study was evaluated in the IEEE 30-Bus test-bed, the evaluation showed that the proposed FA-based approach performed optimally in comparison with the performance of the other existing optimizers, such as the traditional FA and particle swarm optimization. The results show the high performance of the modified firefly algorithm compared to the other methods.
Hybrid Particle Swarm Optimization for Solving Multi-Area Economic Dispatch P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC) and RCGA.
Normally, the character of the wind energy as a renewable energy sources has uncertainty in generation. To resolve the Optimal Power Flow (OPF) drawback, this paper proposed a replacement Hybrid Multi Objective Artificial Physical Optimization (HMOAPO) algorithmic rule, which does not require any management parameters compared to different meta-heuristic algorithms within the literature. Artificial Physical Optimization (APO), a moderately new population-based intelligence algorithm, shows fine performance on improvement issues. Moreover, this paper presents hybrid variety of Animal Migration Optimization (AMO) algorithmic rule to express the convergence characteristic of APO. The OPF drawback is taken into account with six totally different check cases, the effectiveness of the proposed HMOAPO technique is tested on IEEE 30-bus, IEEE 118-bus and IEEE 300-bus check system. The obtained results from the HMOAPO algorithm is compared with the other improvement techniques within the literature. The obtained comparison results indicate that proposed technique is effective to succeed in best resolution for the OPF drawback.
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.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
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.
Economic Load Dispatch for Multi-Generator Systems with Units Having Nonlinea...IJAPEJOURNAL
Economic Load Dispatch aims at distributing the load demand between various generation stations in a system such that the total cost of generation is minimum. This is of vital importance since it not only reduces the operation cost of the generation utility but also helps in conserving fast dwindling energy resources. Modern day power systems are large interconnected systems with a large number of generator units each having its own cost curve. Ideally the cost function of a unit is a quadratic function of the power generated by the unit and the cost curve obtained is a smooth parabola. But in practice cost curves deviate from the idealised one due the several reasons such as valve point effect, multi fuel operation, existence of forbidden zones etc. and as such may not be continuous or analytic. Also for a large interconnected system it becomes essential to consider the effect of transmission losses. Conventional numerical method based approaches work well with systems without losses but for large systems with losses obtaining convergence becomes difficult as the number of iterations required as well as the computational time are very high. These methods fail entirely if non ideal cost curves are considered. Hence soft computing based methods become essential. Here Gravity Search Algorithm(GSA) has been used to for finding economic load scheduling in a multi generator system, given a certain load demand, and taking into consideration the effects of practical constraints on the idealised load curve. The algorithms for finding the economic scheduling has been written in Matlab and has provided satisfactory results based on the given tolerance values. Also the traditional and soft computing based approaches have been compared to demonstrate the advantages of one over the other.
Estimation efficiency of rewound induction motors in situ using a numerical m...journalBEEI
This paper presents an effective technique for determining the impact of rewinding practices on the motor efficiency and characterizing the efficiency reduction when electrical motors are rewound several times. This technique focuses on a new approach and a statistical study to find a numerical model for the estimation efficiency of rewound induction motors in the field. The experimental results from 101 induction motor tests are analyzed. A numerical model is determined and compared with different methods: separate losses method, modified current method and simple current method. An error analysis is conducted to examine the level of uncertainty by testing three asynchronous motors at 110 kW, 160 kW, and 300 kW. The results show that this approach can predict and estimate the efficiency reduction in rewound motors without expensive tests and can help the energy manager make effective cost decisions in replacing the rewound motors with more efficient ones by using an assessment of overconsumption and maintenance costs. Another advantage of this model is that it can be used to improve the software tools and can also be a very strong indicator to audit the repair quality.
A probabilistic multi-objective approach for FACTS devices allocation with di...IJECEIAES
This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller.
Compromising between-eld-&-eed-using-gatool-matlabSubhankar Sau
Creating a compromising points between economic load dispatch & emission created from the plant to minimising those effects.
these are created by using MATLAB and GATOOL .
taking Weighted Sum Method,also Pareto optimal curve.
created by: SUBHANKAR SAU
Optimal Economic Load Dispatch of the Nigerian Thermal Power Stations Using P...theijes
This paper deals with the optimization of economic load dispatch (ELD) problem; this is to find the optimal combination of generators in order to minimize the operating costs of the system. This is done by using the particle swarm optimization (PSO) algorithm. PSO is applied to search for the optimal schedule of all the generator units that can supply the required demand at minimum fuel cost while satisfying all system constraints. The PSO algorithm has been implemented using MATLAB optimization toolbox and was applied to solve the ELD problem of the Nigeria thermal power stations. The results were compared with published results obtained via micro-GA, conventional-GA and differential evolution (DE) techniques.
Coordinated Placement and Setting of FACTS in Electrical Network based on Kal...IJECEIAES
To aid the decision maker, the optimal placement of FACTS in the electrical network is performed through very specific criteria. In this paper, a useful approach is followed; it is based particularly on the use of KalaiSmorodinsky bargaining solution for choosing the best compromise between the different objectives commonly posed to the network manager such as the cost of production, total transmission losses (Tloss), and voltage stability index (Lindex). In the case of many possible solutions, Voltage Profile Quality is added to select the best one. This approach has offered a balanced solution and has proven its effectiveness in finding the best placement and setting of two types of FACTS namely Static Var Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) in the power system. The test case under investigation is IEEE-14 bus system which has been simulated in MATLAB Environment.
Optimal power flow with distributed energy sources using whale optimization a...IJECEIAES
Renewable energy generation is increasingly attractive since it is non-polluting and viable. Recently, the technical and economic performance of power system networks has been enhanced by integrating renewable energy sources (RES). This work focuses on the size of solar and wind production by replacing the thermal generation to decrease cost and losses on a big electrical power system. The Weibull and Lognormal probability density functions are used to calculate the deliverable power of wind and solar energy, to be integrated into the power system. Due to the uncertain and intermittent conditions of these sources, their integration complicates the optimal power flow problem. This paper proposes an optimal power flow (OPF) using the whale optimization algorithm (WOA), to solve for the stochastic wind and solar power integrated power system. In this paper, the ideal capacity of RES along with thermal generators has been determined by considering total generation cost as an objective function. The proposed methodology is tested on the IEEE-30 system to ensure its usefulness. Obtained results show the effectiveness of WOA when compared with other algorithms like non-dominated sorting genetic algorithm (NSGA-II), grey wolf optimization (GWO) and particle swarm optimization-GWO (PSOGWO).
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...IJERA Editor
This Paper is an attempt to develop the expansion-planning algorithm using meta heuristics algorithms. Expansion Planning is always needed as the power demand is increasing every now and then. Thus for a better expansion planning the meta heuristic methods are needed. The cost efficient Expansion planning is desired in the proposed work. Recently distributed generation is widely researched to implement in future energy needs as it is pollution free and capability of installing it in rural places. In this paper, optimal distributed generation expansion planning with Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) for identifying the location, size and type of distributed generator for future demand is predicted with lowest cost as the constraints. Here the objective function is to minimize the total cost including installation and operating cost of the renewable DGs. MATLAB based `simulation using M-file program is used for the implementation and Indian distribution system is used for testing the results.
Coyote multi-objective optimization algorithm for optimal location and sizing...IJECEIAES
Research on the integration of renewable distributed generators (RDGs) in radial distribution systems (RDS) is increased to satisfy the growing load demand, reducing power losses, enhancing voltage profile, and voltage stability index (VSI) of distribution network. This paper presents the application of a new algorithm called ‘coyote optimization algorithm (COA)’ to obtain the optimal location and size of RDGs in RDS at different power factors. The objectives are minimization of power losses, enhancement of voltage stability index, and reduction total operation cost. A detailed performance analysis is implemented on IEEE 33 bus and IEEE 69 bus to demonstrate the effectiveness of the proposed algorithm. The results are found to be in a very good agreement.
Evolutionary algorithm solution for economic dispatch problemsIJECEIAES
A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints, these include the practical operation constraints of the generators (such as the forbidden working areas, nonlinear limits, and generation limits) that makes the calculation of the global optimal solutions of ED a difficult task. The proposed approach in this study was evaluated in the IEEE 30-Bus test-bed, the evaluation showed that the proposed FA-based approach performed optimally in comparison with the performance of the other existing optimizers, such as the traditional FA and particle swarm optimization. The results show the high performance of the modified firefly algorithm compared to the other methods.
Hybrid Particle Swarm Optimization for Solving Multi-Area Economic Dispatch P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC) and RCGA.
Normally, the character of the wind energy as a renewable energy sources has uncertainty in generation. To resolve the Optimal Power Flow (OPF) drawback, this paper proposed a replacement Hybrid Multi Objective Artificial Physical Optimization (HMOAPO) algorithmic rule, which does not require any management parameters compared to different meta-heuristic algorithms within the literature. Artificial Physical Optimization (APO), a moderately new population-based intelligence algorithm, shows fine performance on improvement issues. Moreover, this paper presents hybrid variety of Animal Migration Optimization (AMO) algorithmic rule to express the convergence characteristic of APO. The OPF drawback is taken into account with six totally different check cases, the effectiveness of the proposed HMOAPO technique is tested on IEEE 30-bus, IEEE 118-bus and IEEE 300-bus check system. The obtained results from the HMOAPO algorithm is compared with the other improvement techniques within the literature. The obtained comparison results indicate that proposed technique is effective to succeed in best resolution for the OPF drawback.
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.
HYBRID PARTICLE SWARM OPTIMIZATION FOR SOLVING MULTI-AREA ECONOMIC DISPATCH P...ijsc
We consider the Multi-Area Economic Dispatch problem (MAEDP) in deregulated power system
environment for practical multi-area cases with tie line constraints. Our objective is to generate allocation
to the power generators in such a manner that the total fuel cost is minimized while all operating
constraints are satisfied. This problem is NP-hard. In this paper, we propose Hybrid Particle Swarm
Optimization (HGAPSO) to solve MAEDP. The experimental results are reported to show the efficiency of
proposed algorithms compared to Particle Swarm Optimization with Time-Varying Acceleration
Coefficients (PSO-TVAC) and RCGA.
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.
Economic Load Dispatch for Multi-Generator Systems with Units Having Nonlinea...IJAPEJOURNAL
Economic Load Dispatch aims at distributing the load demand between various generation stations in a system such that the total cost of generation is minimum. This is of vital importance since it not only reduces the operation cost of the generation utility but also helps in conserving fast dwindling energy resources. Modern day power systems are large interconnected systems with a large number of generator units each having its own cost curve. Ideally the cost function of a unit is a quadratic function of the power generated by the unit and the cost curve obtained is a smooth parabola. But in practice cost curves deviate from the idealised one due the several reasons such as valve point effect, multi fuel operation, existence of forbidden zones etc. and as such may not be continuous or analytic. Also for a large interconnected system it becomes essential to consider the effect of transmission losses. Conventional numerical method based approaches work well with systems without losses but for large systems with losses obtaining convergence becomes difficult as the number of iterations required as well as the computational time are very high. These methods fail entirely if non ideal cost curves are considered. Hence soft computing based methods become essential. Here Gravity Search Algorithm(GSA) has been used to for finding economic load scheduling in a multi generator system, given a certain load demand, and taking into consideration the effects of practical constraints on the idealised load curve. The algorithms for finding the economic scheduling has been written in Matlab and has provided satisfactory results based on the given tolerance values. Also the traditional and soft computing based approaches have been compared to demonstrate the advantages of one over the other.
Estimation efficiency of rewound induction motors in situ using a numerical m...journalBEEI
This paper presents an effective technique for determining the impact of rewinding practices on the motor efficiency and characterizing the efficiency reduction when electrical motors are rewound several times. This technique focuses on a new approach and a statistical study to find a numerical model for the estimation efficiency of rewound induction motors in the field. The experimental results from 101 induction motor tests are analyzed. A numerical model is determined and compared with different methods: separate losses method, modified current method and simple current method. An error analysis is conducted to examine the level of uncertainty by testing three asynchronous motors at 110 kW, 160 kW, and 300 kW. The results show that this approach can predict and estimate the efficiency reduction in rewound motors without expensive tests and can help the energy manager make effective cost decisions in replacing the rewound motors with more efficient ones by using an assessment of overconsumption and maintenance costs. Another advantage of this model is that it can be used to improve the software tools and can also be a very strong indicator to audit the repair quality.
A probabilistic multi-objective approach for FACTS devices allocation with di...IJECEIAES
This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller.
Compromising between-eld-&-eed-using-gatool-matlabSubhankar Sau
Creating a compromising points between economic load dispatch & emission created from the plant to minimising those effects.
these are created by using MATLAB and GATOOL .
taking Weighted Sum Method,also Pareto optimal curve.
created by: SUBHANKAR SAU
Optimal Economic Load Dispatch of the Nigerian Thermal Power Stations Using P...theijes
This paper deals with the optimization of economic load dispatch (ELD) problem; this is to find the optimal combination of generators in order to minimize the operating costs of the system. This is done by using the particle swarm optimization (PSO) algorithm. PSO is applied to search for the optimal schedule of all the generator units that can supply the required demand at minimum fuel cost while satisfying all system constraints. The PSO algorithm has been implemented using MATLAB optimization toolbox and was applied to solve the ELD problem of the Nigeria thermal power stations. The results were compared with published results obtained via micro-GA, conventional-GA and differential evolution (DE) techniques.
Coordinated Placement and Setting of FACTS in Electrical Network based on Kal...IJECEIAES
To aid the decision maker, the optimal placement of FACTS in the electrical network is performed through very specific criteria. In this paper, a useful approach is followed; it is based particularly on the use of KalaiSmorodinsky bargaining solution for choosing the best compromise between the different objectives commonly posed to the network manager such as the cost of production, total transmission losses (Tloss), and voltage stability index (Lindex). In the case of many possible solutions, Voltage Profile Quality is added to select the best one. This approach has offered a balanced solution and has proven its effectiveness in finding the best placement and setting of two types of FACTS namely Static Var Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) in the power system. The test case under investigation is IEEE-14 bus system which has been simulated in MATLAB Environment.
Optimal power flow with distributed energy sources using whale optimization a...IJECEIAES
Renewable energy generation is increasingly attractive since it is non-polluting and viable. Recently, the technical and economic performance of power system networks has been enhanced by integrating renewable energy sources (RES). This work focuses on the size of solar and wind production by replacing the thermal generation to decrease cost and losses on a big electrical power system. The Weibull and Lognormal probability density functions are used to calculate the deliverable power of wind and solar energy, to be integrated into the power system. Due to the uncertain and intermittent conditions of these sources, their integration complicates the optimal power flow problem. This paper proposes an optimal power flow (OPF) using the whale optimization algorithm (WOA), to solve for the stochastic wind and solar power integrated power system. In this paper, the ideal capacity of RES along with thermal generators has been determined by considering total generation cost as an objective function. The proposed methodology is tested on the IEEE-30 system to ensure its usefulness. Obtained results show the effectiveness of WOA when compared with other algorithms like non-dominated sorting genetic algorithm (NSGA-II), grey wolf optimization (GWO) and particle swarm optimization-GWO (PSOGWO).
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...IJERA Editor
This Paper is an attempt to develop the expansion-planning algorithm using meta heuristics algorithms. Expansion Planning is always needed as the power demand is increasing every now and then. Thus for a better expansion planning the meta heuristic methods are needed. The cost efficient Expansion planning is desired in the proposed work. Recently distributed generation is widely researched to implement in future energy needs as it is pollution free and capability of installing it in rural places. In this paper, optimal distributed generation expansion planning with Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) for identifying the location, size and type of distributed generator for future demand is predicted with lowest cost as the constraints. Here the objective function is to minimize the total cost including installation and operating cost of the renewable DGs. MATLAB based `simulation using M-file program is used for the implementation and Indian distribution system is used for testing the results.
Coyote multi-objective optimization algorithm for optimal location and sizing...IJECEIAES
Research on the integration of renewable distributed generators (RDGs) in radial distribution systems (RDS) is increased to satisfy the growing load demand, reducing power losses, enhancing voltage profile, and voltage stability index (VSI) of distribution network. This paper presents the application of a new algorithm called ‘coyote optimization algorithm (COA)’ to obtain the optimal location and size of RDGs in RDS at different power factors. The objectives are minimization of power losses, enhancement of voltage stability index, and reduction total operation cost. A detailed performance analysis is implemented on IEEE 33 bus and IEEE 69 bus to demonstrate the effectiveness of the proposed algorithm. The results are found to be in a very good agreement.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
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.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
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.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
2. CONTENTS
INTRODUCTION
LITERATURE SURVEY
ALL INDIA POWER GENERATION SCENERIO
POWER GENERATION SCENERIO OF TRIPURA
ECONOMIC LOAD DISPATCH
NECESSITIES
ECONOMIC DISPATCH PROBLEM FORMULATION
DIFFERENT CONSTRAINTS IN ECONOMIC LOAD DISPATCH
SIMULATION RESULT
CONCLUSION
FUTURE SCOPE
REFERENCES
5/13/201
9
2
3. INTRODUCTION
In power generation our main aim is to generate the
required amount of power with minimum cost.
Economic load dispatch means that the generators real
and reactive power is allowed to vary within the
certain limits so as to meet a particular load demand
with minimum fuel cost
This allocation of loads are based on some constraints
5/13/201
9
3
4. LITERATURE SURVEY
SL NO. AUTHOR NAME YEAR SUMMARY
01 Kuntal Bhattacharjee [1] 2014 It presents a Real Coded Chemical Reaction
Algorithm approach to solve the economic
emission load dispatch problem of thermal
generators of power system.
02 Barun Mandal [2] 2014 It presents a new & efficient krill herd
algorithm to solve both convex & non convex
ELD problem of thermal power units
considering valve point loading, multiple fuel
operation, transmission losses & constraints.
03 Sumit Banerjee [3] 2015 It presents a novel teaching learning based
optimization technique to solve economic
load dispatch of the Thermal unit without
considering transmission losses.
04 Rakesh Vasani [4] 2015 It presents Economic load dispatch gives the
best saving in cost for any power generation
plant operation in which the methodology can
5/13/201
9
4
5. LITERATURE SURVEY
SL NO. AUTHOR NAME YEAR SUMMARY
5. Naser Ghorbani [5] 2016 It presents exchange market
algorithm for solving economic
load dispatch problems. Exchange
market algorithm is a new, robust
& strong algorithm to extract the
optimal point for global
optimization.
6. Moumita Pradhan
[6]
2016 It presents a new evolutionary
optimization approach named
grey wolf optimization (GWO),
which is based on the behaviour of
grey wolves, for the optimal
operating strategy of economic
load dispatch (ELD).
5/13/201
9
5
6. LITERATURE SURVEY
SL.N
O.
AUTHOR NAME YEAR SUMMARY
7. Pudi Sekhar [7] 2016 This paper propose a Meta-heuristic algorithm
known as the cuckoo search algorithm for
contingency in order to relieve transmiaaion line
overloading. The power system security
enhancement deals with finding out the secure and
insecure state operating states.
8. P. Girish [8] 2018 This paper affords about the numerous optimization
techniques to solve the financial load dispatch
problems occurring at some stage in the
transmission. In few papers the proposed approach
is compared with the preceding strategies and
reveals a higher system to solve the monetary
dispatch problems.
5/13/201
9
6
7. LITERATURE SURVEY
SL.N
O.
AUTHOR NAME
YEAR
SUMMARY
9. Masoud Javadi [9] 2019 This paper develops a new look ahead dynamic security-
constrainted economic dispatch model, further considering
frequency stability constraints. The aim is to optimize the
cost of power generation subject to operation and frequency
stability constraints under normal & contingency condition.
10. Farhad Nazari-Heris
[10]
2019 It preesents a new optimiztion model based on mixed-
integer non-linear programming (MINLP). The main goal of
this paper is t0 find the optimal solution of ELD of micro
grids in power systems in which technical constraints like
AC powerflow limitations are taken into account.
11 Dr. Eberhart and Dr.
Kennedy
1995 The paper presents a swram based optimization algorithm
namely Particle Swarm Optimization (PSO). The algorithms
inspired by social behavior of bird flocking or fish schooling.
5/13/201
9
7
8. LITERATURE SURVEY
SL.NO. AUTHOR NAME YEAR SUMMARY
12. Kazem Zare [12] 2016 This paper presents heuristic modified group
search optimization (MGSO) algorithm for
solving multi-objective combined economic
power and emission dispatch problem. Some
modifications are applied on the conventional
GSO method to improve its convergence
characteristics.
13. Hassan Barati [13] 2016 Hence, in this paper, a new hybrid method
based on modified particle swarm optimization
and genetic algorithm (MPSO-GA) is proposed
to solve complicated problem such as Valve-
point effect, the ramp rate limits, prohibited
operation zones (POZs), Multiple-fuel and
transmission losses make the ED a complicated,
non-linear constrained problem.
5/13/201
9
8
11. What is “Economic Dispatch?”
Economic dispatch (ED) determines the least cost
dispatch of generation for a system.
Economic Dispatch (From EPACT 1992)
The operation of generation facilities to produce energy
at the lowest cost to reliably serve consumers,
recognizing any operational limits of generation and
transmission facilities.
5/13/2019 11
12. To minimize total system generating cost, relationships between
cost of power output and operating costs, input has been
modeled
5/13/2019 12
Body of
water
Stack
Thermal Turbine
G
Generat
or
Cooling
Tower
Condenser
Pump
Boile
r
Coal
feed
er Burner
13. NECESSITIES
Economic dispatch is the short term
determination of the optimal output of
the number of electricity generation
facilities, to meet the system load, at the
lowest possible cost.
The purpose of economic dispatch is to
determine the optimal power generation
of the units participating in supplying
load.
5/13/201
9
13
14. Economic Dispatch: Problem Formulation
• The goal of economic dispatch is to determine the
generation dispatch that minimizes the instantaneous
operating cost, subject to the constraint that total
generation = total load + losses
5/13/201
9
14
(1
)
(2)
15. Continued…
ELD problem considering valve point effects-
The generation units with multi steam valve
create more variations in plant cost
function. Since the existence of steam
valve leads to ripple creation in plants
characteristics, the cost function would
have a more non linear formula.
Therefore, the cost function should be
replaced by the following cost functions
5/13/201
9
15
(3)
16. DIFFERENT CONSTRAINTS IN
ECONOMIC LOAD DISPATCH
CONSTRAINTS
Power Balance Constraints:
𝑖=1
𝑁
𝑃𝐺𝑖 = 𝑃𝑙𝑜𝑠𝑠 + 𝐷 (4)
The total power loss in the transmission line network
which may be represented as below:
𝑃𝑙𝑜𝑠𝑠 = 𝑖=1
𝑁
𝑗=1
𝑁
𝑃𝐺𝑖 𝑇𝑖𝑗𝑃𝐺𝑖 + 𝑖=1
𝑁
𝑇𝑖0 𝑃𝐺𝑖 + 𝑇00 (5)
5/13/201
9
16
17. 5/13/201
9
17
Capacity Constraints:
𝑃𝑖
𝑚𝑖𝑛
≤ 𝑃𝑖 ≤ 𝑃𝑖
𝑚𝑎𝑥
(6)
Prohibited Operating Zone:
Generating units can have the prohibited operating zones.
So in economic power dispatch the prohibited operating
zone has broken cost fuel curve and hence in economic load
dispatch the prohibited operating zones having the
operation border values of generation units as shown
𝑃𝑖
𝑚𝑖𝑛
≤ 𝑃𝑖 ≤ 𝑃𝑖,1
𝐿𝐿
𝑃𝑖,𝑗−1
𝑈𝐿
≤ 𝑃𝑖 ≤ 𝑃𝑖,𝑗
𝐿𝐿
𝑗 = 2,3, … . 𝑛𝑝𝑖
𝑃𝑖,𝑛𝑝𝑖
𝑈𝐿
≤ 𝑃𝑖 ≤ 𝑃𝑖
𝑚𝑎𝑥
(7)
18. CONCLUSION
In this work, an efficient and comparatively new algorithm named ECBO is
proposed to solve the economic load dispatch problem taking the valve
point loading effect into consideration. The proposed method is efficiently
and effectively applied on 4 different test systems which are 3,5,13 and
18 generating units. The governing law from the physics gives a
theoretical foundation to the ECBO algorithm. After two bodies collide,
having specified masses and velocities, these agents are separated from
each other with new velocities to explore the design space. Numerical
results show that ECBO method has superior features, superior solution
quality, robustness, and better convergent characteristics with less
computational efforts.
Due to its promising performances, the ECBO method seems to be an
important tool for solving several other complex power system
optimisation problems.
5/13/201
9
18
19. FUTURE SCOPE
Despite of the present work there is some scope to work further and these
can be summarized as follows:
The present work has been done considering the conventional energy
sources. In future the work can be done considering renewable energy
sources.
Although ECBO shows promising results still there is some scope of further
improvement. So ECBO can be hybridized with other algorithm to make it
more powerful optimization tool.
In the present work static ELD problem has been solved. In future dynamic
ELD problem along with load uncertainty can be chosen for further study.
5/13/201
9
19
21. REFERENCES
5/13/2019
21
[1] Bhattacharjee, K, Bhattacharya, A and Halder nee Dey, S. (2014). “ Solution
of economic emission load dispatch problems of power system by real coded
chemical reaction algorithm”, International Journal of Electrical Power & Energy
Systems, vol.59, pp.176-187.
[2] Mandal, B, Roy, P.K. and Mandal, S. (2014). “ Economic load dispatch using
krill herd algorithm”, International Journal of Electrical Power & Energy Systems,
v ol.57,pp.1-10.
[3] Banerjee, S, Maity, D and Chanda, C.K.(2015). “ Teaching Learning based
optimization for economic load dispatch problem considering valve point
loading effect”, International Journal of Electrical Power & Energy Systems,
vol.73,pp.456-464.
[4] Vasani, R, (2015).“An Advancements Review paper on Economic Load
Dispatch” , Journal of Emerging Technologies and Innovative Research
(JETIR),vol.2,pp.2349-5162.
[5] Ghorbani, N and Babaei, E. (2016). “ Exchange market algorithm for
economic load dispatch”, International Journal of Electrical Power & Energy
Systems, vol.75, pp.19-27.
[6] Pradhan, M, Roy, P.K. and Pal, T (2016).“Grey wolf optimization applied to
economic load dispatch problems”, ”, International Journal of Electrical Power &
Energy Systems, vol.83,pp. 325–334.
22. REFERENCES
[7] Sekhar, P and Mohanty, S (2016). “An enhanced cuckoo search algorithm
based contingency load dispatch for security enhancement,” International
Journal of Electrical Power & Energy Systems,vol.75,pp.303-310.
[8] P, Girish, T, Yuvaraj and R, Hariharan (2018). “ Solution For Economic Load
Dispatch Problem Using Optimization Algorithm-Review”, International
Journal of Pure and Applied Mathematics, vol.119,pp.263-269.
[9] Javadi, M and Capitanescu, F (2019). “Look ahead dynamic security
constrainted economic dispatch considering frequency stability and smart
loads”, International Journal of Electrical Power & Energy Systems,
v0l.108,pp.240-251.
[10] Heris, F.N. and Nazarpour, D (2019). “Network constrainted economic
dispatch of renewable energy and CHP based microgrids”, International
Journal of Electrical Power & Energy Systems, vol.110,pp.144-160.
[11] Kennedy, J. and Eberhart, R. C. Particle swarm optimization. Proc. IEEE int'l
conf. on neural networks Vol. IV, pp. 1942-1948. IEEE service center,
Piscataway, NJ, 1995.
5/13/201
9
22
23. REFERENCES
[12] Daryani, N and Zare, K (2016). “Multiobjective power and
emission dispatch using modified group search optimization
method”, Ain Shams Engineering Journal,pp.319-328.
[13] Barati, H and Mohammad, S, (2016). “An efficient hybrid
MPSO-GA algorithm for solving non-smooth/ non-convex
economic dispatch problem with practical constraints”, Ain
Shams Engineering Journal,pp.1279-1287.
[14] Mallikarjuna, B, Reddy, K.H. and Hemakeshavulu, O, (2014). “
Economic Load Dispatch with valve- point result employing a
binary bat formula”, International Journal of Electrical and
Computer Engineering, vol-4, pp.101-107.
[15] Roy, P.K, Bhui, S and Paul, C, (2013). “Solution of economic
load dispatch using hybrid chemical reaction optimization
approach”, Applied Soft Computing Journal of Electrical
Engineering,vol-24,pp.109-125.
5/13/201
9
23