A Novel Multi-Objective Optimization Model for Integrated Photovoltaic/Hydroelectric Power Generation Operation

被引：0

作者：

Ding, Shidong ^{[1
]}

Zeng, Pingliang ^{[1
]}

Xing, Hao ^{[1
]}

Yang, Jingqi ^{[2
]}

Zhou, Qinyong ^{[2
]}

机构：

[1] Hangzhou Dianzi Univ, Hangzhou 310018, Peoples R China

[2] China Elect Power Res Inst, Beijing 100040, Peoples R China

来源：

PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC) | 2019年

基金：

中国国家自然科学基金;

关键词：

PV/hydroelectric hybrid power systems; Multi-objective optimization; NSGA-II; PV modelling; solar irradiance; SOLAR;

D O I：

10.23919/chicc.2019.8865947

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a multi-objective optimization model for integrated PV/hydroelectric power generation systems to minimize the fluctuation of the combined power output and at the same time maximize total income of the integrated systems. In addition, factors such as flood control, water supply, evaporation and precipitation are considered. The multi-objective optimization problem is solved by the non-dominated sorting genetic algorithm (NSGA-II) with improved sorting and diversity distribution method that significantly increases the efficiency and speed of the solution. Finally, the proposed model is applied to integrated Longyangxia PV/hydroelectric hybrid systems. Simulation results demonstrate the effectiveness of the proposed methods.

引用

页码：7328 / 7333

页数：6

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