Robust planning of energy storage in distribution network considering source-network-load flexible resources

被引：0
|
作者：
Zhu X. [1 ]
Lu G. [1 ]
Xie W. [1 ]
机构：
[1] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2021年 / 41卷 / 08期
关键词：
Differential evolution algorithm; Distribution network; Flexible resources; Optimal configuration of energy system; Robustness;
D O I：
10.16081/j.epae.202104004
中图分类号：
学科分类号：
摘要：
The increase of permeability of distributed generations such as wind power and photovoltaic power in distribution network causes the drastic fluctuation of net load, which leads to the sharp increase of distribution network's flexibility demand. Therefore, an optimal configuration method of energy storage in distribution network considering source-network-load flexible resources is proposed. Firstly, based on the flexibility theory, the characteristics of flexible resources in the distribution network are analyzed, and the flexibility supply-demand balance index to measure the distribution network's overall flexibility and the flexibility res-ponse ability index of branch to measure the network's flexibility are established. Then, K-means method and robust optimization theory are used to establish uncertain operation scenario sets from multiple time scales. Finally, an economical and flexible multi-objective optimization model is established with the minimum annual comprehensive cost of distribution network and the maximum daily average flexibility as its optimization objectives, which is solved by the multi-objective composite differential evolution algorithm with embedded power flow calculation. Based on IEEE 33-bus distribution network system, a numerical example is designed and simulated, and the results verify the rationality and effectiveness of the proposed model considering source-network-load flexible resources in solving the energy storage configuration scheme. © 2021, Electric Power Automation Equipment Press. All right reserved.
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页码：8 / 16
页数：8
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