Genetic algorithm-based simulated annealing method for solving unit commitment problem in utility system

Abstract

This paper presents a new approach to solve the short-term unit commitment problem using genetic algorithm-based simulated annealing method for utility system. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimised when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. Genetic Algorithms (GAs) are general-purpose optimisation techniques based on principles inspired from the biological evolution using metaphors of mechanisms such as neural section, genetic recombination and survival of the fittest. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all the units according to their initial status ('flat start'). Here, the parents are obtained from a predefined set of solutions, i.e., each and every solutio...