Hybrid DE–SQP algorithm for non-convex short term hydrothermal scheduling problem

Abstract

This paper proposes a hybrid method combining differential evolution (DE) and sequential quadratic programming (SQP) for solving short term hydrothermal scheduling problem with non-convex fuel cost function. In this paper, differential evolution (DE) is used as a global optimizer and sequential quadratic programming (SQP) method as a local optimizer to fine tune the solution. The proposed method has been tested on a multichain cascaded reservoir with an equivalent thermal test system and the simulation results are compared with existing methods reported in literatures. From the results, it clearly shows that the proposed method is giving better quality solutions than existing methods.