Analysis and Evaluation of the Complementarity Characteristics of Wind and Photovoltaic Considering Source-load Matching

被引:0
|
作者
Wan J. [1 ]
Su H. [1 ]
Feng D. [1 ]
Zhao Y. [1 ]
Fan Y. [2 ]
Yu B. [3 ]
机构
[1] Key Laboratory of Control of Power Transmission and Conversion (SJTU), Ministry of Education, Minhang District, Shanghai
[2] State Grid Qinghai Electric Power Co., Ltd., Xining, 810008, Qinghai Province
[3] State Grid Xinjiang Electric Power Co., Ltd., Urumqi, 830002, Xinjiang Uygur Autonomous Region
来源
Feng, Donghan (seed@sjtu.edu.cn) | 1600年 / Power System Technology Press卷 / 44期
关键词
Capacity allocation; Complementarity evaluation; Renewable energy; Source-load matching;
D O I
10.13335/j.1000-3673.pst.2020.0690
中图分类号
学科分类号
摘要
Multi-energy complementarity has become an important means to reduce the fluctuation of the output of renewable energy and promote the utilization of renewable energy. In order to improve the complementarity analysis and evaluation methods of the renewable energy, this paper evaluates the complementarity of renewable energy from the perspective of source-load matching. For the renewable energy stations that have been built, rank correlation coefficient and tail correlation coefficient are applied in this paper to describe the load matching abilities of multiple renewable energy stations based on mix-Copula, so as to obtain the complementarity evaluation among the outputs of the renewable energy. As for those stations to be built, an optimization model of wind and photovoltaic capacity allocation is solved based on the Charnes-Cooper method and the branch and bound method. The penetration rate and utilization rate of the renewable energy of the optimal capacity are used as the complementarity indices. Besides, the load matching degree, a complementarity index to describe the closeness of the total output of the renewable energy units and the load, is proposed. Research shows that the load matching degree is able to consider the utilization rate and penetration rate comprehensively and provides a simple but effective method for the optimization of wind and photovoltaic capacity allocation. © 2020, Power System Technology Press. All right reserved.
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页码:3219 / 3226
页数:7
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