An adaptive hybrid backtracking search optimization algorithm for dynamic economic dispatch with valve-point effects

Dynamic economic dispatch with valve-point effects (DED_vpe) is a high-dimensional constrained optimization problem with non-convex and non-smooth characteristics. Hybrid methods are one of the most advanced methods to solve the problem. However, most of these methods improve the solution accuracy at the expense of algorithm robustness. This paper proposes an adaptive hybrid backtracking search optimization algorithm (AHBSA) for solving the DED_vpe. The core idea of AHBSA lies in designing a suitable coupling structure based on the current best individual (called optimal partial coupling). The structure hybridizes an improved BSA mutation operator and the DE/best/1 operator with equal probability. The improved BSA mutation operator uses the current best individual and the historical population to update individual position, called BSA/best/old. It is also the first research work of extending BSA to the problem. In addition, an adaptive parameter control mechanism is proposed to select an appropriate 'mixrate' value for achieving better coupling. The performance of AHBSA is validated on six DED test cases of three systems. Experimental results demonstrate that, compared with some representative methods, AHBSA not only reduces the fuel cost but also ensures the robustness of the algorithm. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This paper proposes an adaptive hybrid backtracking search optimization algorithm (AHBSA) for solving dynamic economic dispatch with valve-point effects (DED_vpe). By designing a suitable coupling structure and an improved mutation operator, AHBSA improves the solution accuracy while ensuring algorithm robustness, and achieves good performance in experiments.