Generation Scheduling problem by Intelligent Genetic Algorithm

This paper presents a Genetic Algorithm (GA) solution to solve the Generation Scheduling (GS) problem with intelligent coding scheme. The intelligent coding scheme effectively handles minimum up/down time constraints of GS problem. GA with intelligent coding is called as Intelligent Genetic Algorithm (IGA). Penalty parameter-less constraint handling technique is used for satisfying power balance constraint. Performance of the IGA is tested on a 10-unit 24-h and 26-unit 24-h unit commitment test systems. The result obtained using IGA is compared with the results reported using Lagrangian Relaxation (LR), Enhanced Lagrangian Relaxation (ELR), LRGA, GA and Evolutionary Programming methods. Simulation results show the effects of intelligent coding scheme in obtaining feasible and minimum cost solution.

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► Generation Scheduling problem using Genetic Algorithm with and without intelligent coding has been solved.
► Minimum up/down time constraints are handled using intelligent coding.
► Standard 10-unit 24-h and 26-unit 24-h test systems are considered.
► Genetic Algorithm with intelligent coding is performing better even for higher order systems.