面向用户侧的电池储能配置与运行优化策略

赵乙潼; 王慧芳; 何奔腾; 徐伟娜

doi:10.7500/AEPS20190507001

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面向用户侧的电池储能配置与运行优化策略

研制与开发 | 更新时间：2020-07-14

- 面向用户侧的电池储能配置与运行优化策略
- Optimization Strategy of Configuration and Operation for User-side Battery Energy Storage
- 电力系统自动化-方正平台 2020年第6期页码：121-128
- 作者机构：
  
  1. 浙江大学电气工程学院，浙江省杭州市 310027
  2. 浙江华云信息科技有限公司，浙江省杭州市 310051
- 作者简介：
  
  赵乙潼(1995—)，女，硕士研究生，主要研究方向：储能优化、增量配电网。E-mail： 21710022@zju.edu.cn
  王慧芳(1974—)，女，通信作者，博士，副教授，主要研究方向：继电保护与控制、电网状态检修、电力数据挖掘。E-mail： huifangwang@zju.edu.cn
  何奔腾(1959—)，男，博士，教授，主要研究方向：继电保护与控制。E-mail： hebt@zju.edu.cn
- 基金信息：
- DOI：10.7500/AEPS20190507001
  中图分类号：
- 收稿日期：2019-05-07，
  
  修回日期：2019-08-09，
  
  网络出版日期：2019-10-21，
  
  纸质出版日期：2020-03-25
- 稿件说明：
移动端阅览
赵乙潼,王慧芳,何奔腾等.面向用户侧的电池储能配置与运行优化策略[J].电力系统自动化,2020,44(06):121-128.

ZHAO Yitong,WANG Huifang,HE Benteng,et al.Optimization Strategy of Configuration and Operation for User-side Battery Energy Storage[J].Automation of Electric Power Systems,2020,44(06):121-128.
赵乙潼,王慧芳,何奔腾等.面向用户侧的电池储能配置与运行优化策略[J].电力系统自动化,2020,44(06):121-128. DOI： 10.7500/AEPS20190507001.

ZHAO Yitong,WANG Huifang,HE Benteng,et al.Optimization Strategy of Configuration and Operation for User-side Battery Energy Storage[J].Automation of Electric Power Systems,2020,44(06):121-128. DOI： 10.7500/AEPS20190507001.

摘要

为提高用户侧电池储能投资与运行的经济性，降低用户用电成本，提出了用户侧电池储能配置优化及运行调度滚动优化方法。首先，分析了用户加装储能的收益以及储能运行的约束，然后构建了储能配置优化模型、储能月前和日内运行滚动优化模型，并用CPLEX求解器进行求解。在构建模型时加入了储能性能约束，能有效减少储能运行时充放电状态之间的转换次数，延长储能寿命。在月前优化中，确定一个预测的月需量防守值；在日内滚动优化中，构建了储能日运行分段优化模型及月需量防守值更新模型，实时更新日负荷数据及月需量防守值，进行滚动优化，不断修正负荷预测误差影响。最后，对工业大用户进行算例仿真，验证了所提优化模型的有效性。

Abstract

In order to improve the economy of the investment and operation of user-side battery energy storage and reduce the cost of users’ power consumption

a rolling optimization method of configuration and operation scheduling for user-side battery energy storage is proposed. Firstly

the benefit of users after installing energy storage and the constraints of energy storage operation are analyzed. Then the configuration optimization model of energy storage

the optimization model of energy storage before month and the rolling optimization model for intra-day operation are constructed and solved by CPLEX solver. Performance constraints of energy storage are added to the model

which can effectively reduce the number of transitions between charging and discharging states and prolong the life of energy storage. In the pre-month optimization

a predicted monthly demand defense value is determined. In the intra-day rolling optimization

a subsection optimization model of daily operation for energy storage and a renewal model of monthly demand defense value are constructed. The daily load data and monthly demand defense value are updated in real time

and the rolling optimization is carried out to continuously correct the impact of load forecasting error. Finally

an industrial user is simulated to verify the validity of the proposed optimization model.

关键词

Keywords

references

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