Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units

Jinjiao Hou, Chaoshun Li, Ziqin Tian, Yanhe Xu, Xinjie Lai, Nan Zhang, Taoping Zheng and Wei Wu
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Jinjiao Hou: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Chaoshun Li: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Ziqin Tian: Changjiang Institute of Survey, Planning, Design and Research, Wuhan 430010 China
Yanhe Xu: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Xinjie Lai: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Nan Zhang: School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Taoping Zheng: Changjiang Institute of Survey, Planning, Design and Research, Wuhan 430010 China
Wei Wu: China Yangtze Power Co., Ltd., Yichang 443000, China

Energies, 2018, vol. 11, issue 5, 1-19

Abstract: This paper proposes a multi-objective optimization method for the start-up strategy of pumped storage units (PSU) for the first time. In the multi-objective optimization method, the speed rise time and the overshoot during the process of the start-up are taken as the objectives. A precise simulation platform is built for simulating the transient process of start-up, and for calculating the objectives based on the process. The Multi-objective Particle Swarm Optimization algorithm (MOPSO) is adopted to optimize the widely applied start-up strategies based on one-stage direct guide vane control (DGVC), and two-stage DGVC. Based on the Pareto Front obtained, a multi-objective decision-making method based on the relative objective proximity is used to sort the solutions in the Pareto Front. Start-up strategy optimization for a PSU of a pumped storage power station in Jiangxi Province in China is conducted in experiments. The results show that: (1) compared with the single objective optimization, the proposed multi-objective optimization of start-up strategy not only greatly shortens the speed rise time and the speed overshoot, but also makes the speed curve quickly stabilize; (2) multi-objective optimization of strategy based on two-stage DGVC achieves better solution for a quick and smooth start-up of PSU than that of the strategy based on one-stage DGVC.

Keywords: pumped storage units; refine modeling; full characteristic curve; multi-target start-up; multi-objective decision-making Method (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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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