Bi-Level Optimal Configuration of Hybrid Shared Energy Storage Capacity in Wind Farms Considering Prediction Error

Yifan Bian; Peng Lu; Lirong Xie; Jiahao Ye; Lan Ma; Jianbin Yang

doi:10.17775/CSEEJPES.2022.08300

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Bi-Level Optimal Configuration of Hybrid Shared Energy Storage Capacity in Wind Farms Considering Prediction Error

Regular Papers | 更新时间：2026-10-10

- Bi-Level Optimal Configuration of Hybrid Shared Energy Storage Capacity in Wind Farms Considering Prediction Error
- CSEE Journal of Power and Energy Systems Vol. 12, Issue 5, Pages: 2308-2317(2026)
- 作者机构：
  
  1. Engineering Research Center for Energy Generation & Grid of Ministry of Education, Xinjiang University,Urumqi,China
  2. State Key Laboratory of Power System, Generation Equipment Tsinghua University,Beijing,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2022.08300
  CLC：
- Published：01 September 2026
- 稿件说明：
移动端阅览
Yifan Bian, Peng Lu, Lirong Xie, et al. Bi-Level Optimal Configuration of Hybrid Shared Energy Storage Capacity in Wind Farms Considering Prediction Error[J]. CSEE Journal of Power and Energy Systems, 2026, 12(5): 2308-2317.
DOI：

Yifan Bian, Peng Lu, Lirong Xie, et al. Bi-Level Optimal Configuration of Hybrid Shared Energy Storage Capacity in Wind Farms Considering Prediction Error[J]. CSEE Journal of Power and Energy Systems, 2026, 12(5): 2308-2317. DOI： 10.17775/CSEEJPES.2022.08300.

摘要

Abstract

In wind farms

hybrid energy storage (HES) can effectively mitigate the fluctuation and intermittency of wind power output and effectively compensate for the prediction errors of wind power. However

the high cost of HES has prevented its large-scale adoption. Inspired by the sharing economy

this paper introduces the concept of hybrid shared energy storage (HSES) in wind farms. A rolling optimization (RO) strategy is formulated to obtain the reference power curve of the HES

and a bi-level optimal configuration model of HSES is established to minimize the wind farm's daily operating cost and optimize the compensation's performance for the prediction errors. The upper-level model aims to obtain the optimal rental capacity of HSES

and the lower level is an energy trading mechanism to optimize the trading power of the wind farm in real time. The simulation results reveal the excellent performance and economy of the proposed HSES model for wind farms.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Market-oriented optimal dispatching strategy for a wind farm with a multiple stage hybrid energy storage system

Economic Dispatch in Microgrids with Photovoltaic and Load Communication Failures Using Deep Reinforcement Learning with Relative Entropy Regularized Asynchronous Update

Transmission Power-Oriented Forecasting Towards Stability-Constrained Operation of Renewable Energy Power Plants with Energy Storages

Low-Carbon Economic Dispatch Considering Wind Curtailment: A Distributionally Robust Chance-Constrained Approach

Single-Cable Layout Boundary of Offshore Wind Turbines Considering Terminal Voltage Distribution

Related Author

Zhenyuan Zhang

Yun Zhang

Qi Huang

Wei-Jen Lee

Wencheng Liu

Zhizhong Mao

Feilong Fan

Chuanqing Pu

Related Institution

University of Electronic Science and Technology of China,, CN

University of Texas at Arlington, Arlington

College of Information Science and Engineering, University of Northeastern

College of Smart Energy, Shanghai Jiao Tong University

Shanghai Non-carbon Energy Conversion and Utilization Institute

AI问答

⁰