上海交通大学学报

上海交通大学学报 >

2021 , Vol. 55 >Issue 12: 1689 - 1699

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2021.322

基于自适应均衡技术的分布式储能聚合模型及评估方法

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  • 1.沈阳工程学院 电力学院,沈阳 110136
    2.沈阳工程学院 能源与动力学院,沈阳 110136
    3.国网辽宁省电力有限公司 电力科学研究院, 沈阳 110006
    4.中建安装集团有限公司 工程研究院,南京 210046
叶 鹏(1974-),男,吉林省吉林市人,博士后,教授,主要从事新能源并网与分布式储能相关研究.

收稿日期: 2021-08-27

  网络出版日期: 2021-12-30

基金资助

辽宁省创新能力提升联合基金(1600743366464)

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An Aggregation Model and Evaluation Method of Distributed Energy Storage Based on Adaptive Equalization Technology

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  • 1. School of Electric Power, Shenyang Institute of Engineering, Shenyang 110136, China
    2. College of Energy and Power, Shenyang Institute of Engineering, Shenyang 110136, China
    3. Electric Power Research Institute, State Grid Liaoning Electric Power Supply Co., Ltd., Shenyang 110006, China
    4. Engineering Research Institute, China Construction Industrial and Energy Engineering Group Co., Ltd., Nanjing 210046, China

Received date: 2021-08-27

  Online published: 2021-12-30

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摘要

针对分布式储能广域分布、资源分散、无法高效聚合等问题,提出一种基于自适应均衡技术的分布式储能聚合模型及评估方法.首先,建立基于储能容量、功率、荷电状态等动态特性参数的自适应均衡函数模型.然后,在自适应均衡函数模型基础上,建立以储能功率调节度、自适应均衡度和容量贡献度3种聚合度动态参数为决策的储能聚合模型.通过算例仿真,验证了该模型可实现各储能单体以更小的体内差异性、更高的体间聚合度完成储能单体到储能聚合体的聚合,可实际应用于大规模参与辅助服务的分布式储能的聚合,实现储能资源的高效利用.

关键词： 自适应均衡技术; 分布式储能聚合模型; 储能单体; 聚合; 储能聚合体

本文引用格式

叶鹏, 刘思奇, 关多娇, 姜竹楠, 孙峰, 顾海飞 . 基于自适应均衡技术的分布式储能聚合模型及评估方法[J]. 上海交通大学学报, 2021 , 55(12) : 1689 -1699 . DOI: 10.16183/j.cnki.jsjtu.2021.322

Abstract

Aimed at the problems of wide area distribution, resource dispersion, and inefficient aggregation of distributed energy storage, this paper proposes an aggregation model and evaluation method of distributed energy storage based on the adaptive equalization technology. First, this paper establishes an adaptive equalization function model based on dynamic characteristic parameters such as energy storage capacity, power, and state of charge. Then, based on the adaptive equalization function model, it establishes the aggregation model and evaluation method of distributed energy storage, which takes the power regulation rate, adaptive equalization rate, and capacity contribution rate as the dynamic parameters of aggregation degree. The example simulation verifies that the model can realize the fact that each energy storage unit can complete the aggregation from energy storage unit to energy storage aggregate with a smaller internal difference and a higher external aggregation rate. It can be applied to a large number of distributed energy storage aggregation participating in grid auxiliary services, and realize the efficient utilization of energy storage resources.

Key words： adaptive equalization technology; aggregation model of distributed energy storage; energy storage unit; aggregate; energy storage aggregation

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