A novel space contraction based on evolutionary strategy for economic dispatch

摘要

With economic development, environmental issues have become a top priority in urban governance. Furthermore, various energy conservation issues have emerged. To allocate energy resources rationally, Economic Dispatch (ED) has been proposed. ED is a common problem in power systems. It aims to minimize the cost while meeting the overall load demand. In this study, a Dynamically adjusted Space Contraction based on the Adaptive Tradeoff Model and Adaptive Evolutionary Strategy (DSC-ATM-AES) has been proposed to solve ED problems. This algorithm proposes a definition for the Differential Variance (DV) and self-adaptive slack to enhance the searching capacity of Evolutionary Strategy (ES). It also introduces a Space Contraction (SC) technique and further improves it. The algorithm is tested on various ED problems (including 6,11,13, and 40 generators), namely standard ED problems and ED problems with valve-point effects. Moreover, DSC-ATM-AES and some popular heuristic algorithms are compared. The experimental results indicate that the DSC-ATM-AES algorithm obtains competitive results and powerful performances.