Unit commitment by genetic algorithm with penalty methods and a comparison of Lagrangian search and genetic algorithm - Economic dispatch example

A genetic algorithm is a random search procedure which is based on the survival of the fittest theory. This paper presents the genetic algorithm applied to the unit commitment scheduling problem and to the economic dispatch of generating units. The first half of the paper applies the genetic algorithm to the unit commitment scheduling problem, which is the problem of determining the optimal set of generating units within a power system, to be used during the next one to seven days. The first half of the paper presents an explanation of the genetic-based unit commitment algorithm, the implementation of this algorithm and a discussion of the problems encountered when using this algorithm with penalty methods for unit commitment scheduling. The second half of the paper applies a genetic algorithm to solve the economic dispatch problem. Using the economic dispatch problem as a basic for comparison, several approaches to implementing a refined genetic algorithm are explored. The results are verified for a sample problem using a classical Lagrangian search technique. (C) 1996 Published by Elsevier Science Ltd.