Fast evolutionary programming techniques for short-term hydrothermal scheduling

Abstract

Fast evolutionary programming techniques are applied for the solution of a short-term hydrothermal scheduling problem. Evolutionary programming (EP)-based algorithms with Gaussian and other mutation techniques have been developed and tested on a multi-reservoir cascaded hydroelectric system having prohibited operating zones and a thermal unit with valve point loading. Numerical results show that all of the EP algorithms are capable of finding very nearly global solutions within a reasonable time but an EP algorithm with better of Gaussian and Cauchy mutations appears to be the best amongst all EPs in terms of convergence speed, solution time, and minimum cost.