Optimal Economic Load Dispatch using Parallel Genetic Algorithms in Large Scale Power Systems

병렬유전알고리즘을 응용한 대규모 전력계통의 최적 부하배분

  • Published : 1999.04.01

Abstract

This paper is concerned with an application of Parallel Genetic Algorithms(PGA) to optimal econmic load dispatch(ELD) in power systems. The ELD problem is to minimize the total generation fuel cost of power outputs for all generating units while satisfying load balancing constraints. Genetic Algorithms(GA) is a good candidate for effective parallelization because of their inherent principle of evolving in parallel a population of individuals. Each individual of a population evaluates the fitness function without data exchanges between individuals. In application of the parallel processing to GA, it is possible to use Single Instruction stream, Multiple Data stream(SIMD), a kind of parallel system. The architecture of SIMD system need not data communications between processors assigned. The proposed ELD problem with C code is implemented by SIMSCRIPT language for parallel processing which is a powerfrul, free-from and versatile computer simulation programming language. The proposed algorithms has been tested for 38 units system and has been compared with Sequential Quadratic programming(SQP).

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References

  1. Operation and Control Power Generation A. J. Wood;B. F. Wollenberg
  2. IEEE Trans. on Power Systems v.10 no.3 Short-Term Generation Scheduling with Transmission and Environmental Constraints using an Augmented Lagrangian Relaxation S. J. Wang(et al.)
  3. IEEE Trans. on Power Systems v.8 no.3 Economic load dispatch for piecewise quadratic cost function using Hopfield neural network J. H. Park(et al.)
  4. IEEE Trans. on Power Systems v.12 no.4 A Fast-Computation Hopfield Method to Economic Dispatch of Power Systems C. T. Su;G. J. Chiou
  5. IEEE Trans. on Power Systems v.10 no.1 Refined Genetic Algorithm - Economic Dispatch Example G. B. Sheble(et al.)
  6. Proceeding of the International Conference on Electrical Engineering v.2 Optimal VAR Dispatching considering contingency by Genetic Algorithms Kyu-Ho Kim;Seok-Ku You
  7. Parallel Genetic Algorithms: Theory and Applications J. Stender
  8. Genetic algorithms + Data structures = Evolution Programs(Second Edition) Z. Michalewicz
  9. IEEE Trans. on Power Apparatus and Systems v.12 no.2 A Genetic Algorithm Approach to Solving Implementation on the Transputer Networks H. T. Yang(et al.)