Optimal Virtual Battery Model for Aggregating Storage-Like Resources with Network Constraints

Zhenfei Tan; Ao Yu; Haiwang Zhong; Xianfeng Zhang; Qing Xia; Chongqing Kang

doi:10.17775/CSEEJPES.2022.04090

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Optimal Virtual Battery Model for Aggregating Storage-Like Resources with Network Constraints

Regular Papers | 更新时间：2026-10-15

- Optimal Virtual Battery Model for Aggregating Storage-Like Resources with Network Constraints
- Optimal Virtual Battery Model for Aggregating Storage-Like Resources with Network Constraints
- 中国电机工程学会电力与能源系统学报(英文) 2024年10卷第4期页码：1843-1847
- 作者机构：
  
  1. Department of Electrical Engineering, Sichuan Energy Internet Research Institute, Tsinghua University,Beijing,China
  2. Science and Technology Institute of China Three Gorges Corporation,Hubei,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2022.04090
  中图分类号：
- 纸质出版：2024-07-01
- 稿件说明：
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Zhenfei Tan, Ao Yu, Haiwang Zhong, 等. Optimal Virtual Battery Model for Aggregating Storage-Like Resources with Network Constraints[J]. 中国电机工程学会电力与能源系统学报(英文), 2024,10(4):1843-1847.

Zhenfei Tan, Ao Yu, Haiwang Zhong, et al. Optimal Virtual Battery Model for Aggregating Storage-Like Resources with Network Constraints[J]. CSEE Journal of Power and Energy Systems, 2024, 10(4): 1843-1847.
Zhenfei Tan, Ao Yu, Haiwang Zhong, 等. Optimal Virtual Battery Model for Aggregating Storage-Like Resources with Network Constraints[J]. 中国电机工程学会电力与能源系统学报(英文), 2024,10(4):1843-1847. DOI： 10.17775/CSEEJPES.2022.04090.

Zhenfei Tan, Ao Yu, Haiwang Zhong, et al. Optimal Virtual Battery Model for Aggregating Storage-Like Resources with Network Constraints[J]. CSEE Journal of Power and Energy Systems, 2024, 10(4): 1843-1847. DOI： 10.17775/CSEEJPES.2022.04090.

摘要

Abstract

A virtual battery (VB) provides a succinct interface for aggregating distributed storage-like resources (SLR) to interact with a utility-level system. To overcome the drawbacks of existing VB models

including conservatism and neglecting network constraints

this paper optimizes the power and energy parameters of VB to enlarge its flexibility region. An optimal VB is identified by a robust optimization problem with decision-dependent uncertainty. An algorithm based on the Benders decomposition is developed to solve this problem. The proposed method yields the largest VB satisfying constraints of both network and SLRs. Case studies verify the superiority of the optimal VB in terms of security guarantee and less conservatism.

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