Hydropower Unit Commitment Using a Genetic Algorithm with Dynamic Programming

Shuangquan Liu, Pengcheng Wang, Zifan Xu, Zhipeng Feng, Congtong Zhang, Jinwen Wang and Cheng Chen ()
Additional contact information
Shuangquan Liu: System Operation Department, Yunnan Power Grid Co., Ltd., 73# Tuodong Road, Kunming 650011, China
Pengcheng Wang: School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
Zifan Xu: School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
Zhipeng Feng: Huaneng Lancang River Hydropower Inc., 1# Shijicheng Road, Kunming 650214, China
Congtong Zhang: System Operation Department, Yunnan Power Grid Co., Ltd., 73# Tuodong Road, Kunming 650011, China
Jinwen Wang: School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China
Cheng Chen: Faculty of Electric Engineering, Kunming University of Science and Technology, 727# Jingming South Road, Kunming 650500, China

Energies, 2023, vol. 16, issue 15, 1-13

Abstract: This study presents a genetic algorithm integrated with dynamic programming to address the challenges of the hydropower unit commitment problem, which is a nonlinear, nonconvex, and discrete optimization, involving the hourly scheduling of generators in a hydropower system to maximize benefits and meet various constraints. The introduction of a progressive generating discharge allocation enhances the performance of dynamic programming in fitness evaluations, allowing for the fulfillment of various constraints, such as unit start-up times, shutdown/operating durations, and output ranges, thereby reducing complexity and improving the efficiency of the genetic algorithm. The application of the genetic algorithm with dynamic programming and progressive generating discharge allocation at the Manwan Hydropower Plant in Yunnan Province, China, showcases increased flexibility in outflow allocation, reducing spillages by 79%, and expanding high-efficiency zones by 43%.

Keywords: hydropower unit commitment (HUC); dynamic programming (DP); genetic algorithm (GA); progressive generating discharge allocation (PGDA) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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