Joint Robust Planning of Wind-Photovoltaic-Energy Storage System Based on Multi-scenario Confidence Gap Decision

被引：0
|
作者：
Peng C. [1 ]
Xiong Z. [1 ]
Zhang Y. [1 ]
Sun H. [1 ]
机构：
[1] School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2022年 / 46卷 / 16期
基金：
中国国家自然科学基金;
关键词：
cross entropy differential evolution; joint planning of wind-photovoltaic-energy storage system; multi-scenario confidence gap decision; radar scanning mechanism; robust optimization;
D O I：
10.7500/AEPS20211221004
中图分类号：
学科分类号：
摘要：
In order to achieve the joint planning with robustness of wind-photovoltaic-energy storage system (ESS) to deal with the negative impact of the uncertainties of renewable energy output, a robust-driven multi-scenario confidence gap decision theory (MCGDT) is proposed. Considering the optimization objectives of maximizing the wind/photovoltaic power consumption rate and minimizing the total investment cost, a wind-photovoltaic-ESS joint robust planning model based on MCGDT is established. Furthermore, the complex chance constraints are transformed into the equivalent determinate constraints according to the uncertainty theory, and a novel cross entropy-radar scanning differential evolution (CE-RSDE) algorithm is proposed to solve the model efficiently. MCGDT can not only make up for the inadequacy of conventional robust optimization and information gap decision theory (IGDT) that fails to measure the robustness accuracy and embody the polymorphism of randomness, but also solve the problem of non-interval ergodicity of typical scenarios in stochastic programming. Therefore, a more reasonable and accurate uncertainty planning can be realized. The validity and superiority of the proposed theory and method are verified by case study. © 2022 Automation of Electric Power Systems Press. All rights reserved.
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页码：178 / 187
页数：9
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