• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.681-688
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• 2012

This paper presents the application of Differential Evolution (DE) algorithm to obtain a solution for Bid Based Dynamic Economic Dispatch (BBDED) problem including the transmission losses and to maximize the social profit in a deregulated power system. The IEEE-30 bus test system with six generators, two customers and two trading periods are considered under various bidding strategies in a day-ahead electricity market. By matching the bids received from supplying and distributing entities, the Independent System Operator (ISO) maximize the social profit, (with the choices available). The simulation results of DE are compared with the results of Particle swarm optimization (PSO). The results demonstrate the potential of DE algorithm and show its effectiveness to solve BBDED.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1417-1426
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• 2017

Power system analysis, Non-Convex Economic Dispatch (NED) is considered as an open and demanding optimization problem. Despite the fact that realistic ED problems have non-convex cost functions with equality and inequality constraints, conventional search methods have not been able to effectively find the global answers. Considering the great potential of meta-heuristic optimization techniques, many researchers have started applying these techniques in order to solve NED problems. In this paper, a new and efficient approach is proposed based on imperialist competitive algorithm (ICA). The proposed algorithm which is named multi-operator ICA (MuICA) merges three operators with the original ICA in order to simultaneously avoid the premature convergence and achieve the global optimum answer. In this study, the proposed algorithm has been applied to different test systems and the results have been compared with other optimization methods, tending to study the performance of the MuICA. Simulation results are the confirmation of superior performance of MuICA in solving NED problems.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.8
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• pp.47-53
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• 2014

This paper presents an Differential Search(DS) Algorithm for solving the economic load dispatch(ELD) problems with Valve-Point loading constraints. DS algorithm simulates the Brownian-like random-walk movement used by an organism to migrate. Numerical results on a test system consisting of 13 units show that the proposed approach is faster, more robust and powerful than conventional algorithms. Case studies show the simulation results are better than Lagrange method, the Hopfield neural networks and GA.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.11
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• pp.520-527
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• 2001

This paper suggests a new methodology of evolutionary computations - an Adaptive Evolutionary Algorithm (AEA) for solving the Economic Load Dispatch (ELD) problem which has piecewise quadratic cost functions and prohibited operating zones with many local minima. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and the population by ES are adaptively modulated according to the fitness. Case studies illustrate the superiority of the proposed methods to existing conventional methods in power generation cost and computation time. The results demonstrate that the AEA can be applied successfully in the solution of ELD with piecewise quadratic cost functions and prohibited operating zones

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1334-1341
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• 2008

This paper introduces an approach of Hybrid Particle Swarm Optimization(HPSO) for a security-constrained economic dispatch(SCED) with line flow constraints. To reduce a early convergence effect of PSO algorithm, we proposed HPSO algorithm considering a mutation characteristic of Genetic Algorithm(GA). In power system, for considering N-1 line contingency, we have chosen critical line contingency through a process of Screening and Selection based on PI(performance Index). To prove the ability of the proposed HPSO in solving nonlinear optimization problems, SCED problems with nonconvex solution spaces are considered and solved with three different approach(Conventional GA, PSO, HPSO). We have applied to IEEE 118 bus system for verifying a usefulness of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.122-124
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• 2001

This Paper presents an application technique for solving the Security Constrained Economic Dispatch(SCED) problem using the Interior Point Method. The optimal power flow solution is obtained by optimizing the given generation cost objectives function subject to the system security constraints. The proposed technique is applied to a prototype 6-bus system for evaluation and test.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.1
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• pp.1-8
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• 1992

Hopfield neural network has been applied to the problem of economic load dispatch(ELD) of electric power. The optimum values of neuron potentials are represented in terms of large numbers. The differential synchronous transition mode is used in this simulation. Through case studies, we have shown the possibility of the application of neural network to ELD. In case of including the transmission losses, the proposed method has an advantage that the problem can be solved simply with one neural network, without calculating incremental fuel costs and incremental losses required by traditional method.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.790-792
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• 1996

According to increase in electric power demand, the increasing rate of peak load compared with that of base load grows larger every year. Thus this paper deals with the optimal dynamic dispatch problem due to power rate limits and spinning reserve with loss or without loss. The first is adjusting module for gradual change of generator power by Object-Oriented Programming. The latter is an efficient dispatch module for the consideration of reasonable spinning reserve requirements. The proposed algorithm has been shown efficiency in real power system with loss.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.366-368
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• 2002

This paper presents a technique that can obtain an optimal solution for the Security-Constrained Economic Dispatch (SCED) problems using the Interior Point Method (IPM) while taking into account of the power flow constraints. The SCED equations are formulated by using only the real power flow equations from the optimal power flow. Then an algorithm is presented that can linearize the SCED equations based on the relationships among generation real power outputs, loads, and transmission losses to obtain the optimal solutions by applying the linear programming (LP) technique. Finally, the application of the Primal Interior Point Method (PIPM) for solving the optimization problem based on the proposed linearized objective function is presented. The results are compared with the Simplex Method and the Promising results ard obtained.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.406-410
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• 2001

This paper develops an efficient evolutionary programming based algorithm for solving the environmentally constrained economic dispatch problem in thermal power system. The proposed algorithm can deal with the power balance constraints and the emission constraints which are equality and inequality constraints, respectively. Numerical results show that the proposed algorithm can provide superior solutions within reasonable time through its application to a test system.