Research on the optimal configuration method of shared energy storage basing on cooperative game in wind farms

Aiming at the problems of low energy storage utilization and high investment cost that exist in the separate configuration of energy storage in power-side wind farms, a capacity optimization method based on cooperative game for wind farm-side shared energy storage power plant is proposed. Firstly, the wind power output scenarios on different typical days are clustered using the Latin hypercubic sampling method and the k-means method; then, the capacity optimization model of the shared energy storage plant is established with the objective of minimizing the total cost of constructing the shared energy storage plant in wind farms; secondly, the cooperative allocation strategy based on the Shapley value is designed to allocate the total cost of investing in and constructing the shared energy storage system; finally, it is demonstrated through examples that the method proposed in this paper effectively reduces the cost of the total investment in the energy storage system for new energy power plants, reduces the cost of wind abandonment penalties for new energy power plants, improves the output effect of new energy power plants, and increases the utilization rate of the shared energy storage power plant.

Authors

Publication Details

Journal
Energy Reports
Published
2024-09-28
DOI
https://doi.org/10.1016/j.egyr.2024.09.053
Citations
11
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
2.30

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the optimal configuration method of shared energy storage basing on cooperative game in wind farms

Zhiqiang Zhao, Hongwei Zhou, Xingxu Zhu, Haojun Liu et al.
11 citations
Energy Reports
Integrated Energy Systems Optimization
2.30
article

Research on the optimal configuration method of shared energy storage basing on cooperative game in wind farms

Zhiqiang Zhao, Hongwei Zhou, Xingxu Zhu, Haojun Liu, Zhi Li, Cuiping Li, Junhui Li, Yang Liu
article en
11 citations

Abstract

Aiming at the problems of low energy storage utilization and high investment cost that exist in the separate configuration of energy storage in power-side wind farms, a capacity optimization method based on cooperative game for wind farm-side shared energy storage power plant is proposed. Firstly, the wind power output scenarios on different typical days are clustered using the Latin hypercubic sampling method and the k-means method; then, the capacity optimization model of the shared energy storage plant is established with the objective of minimizing the total cost of constructing the shared energy storage plant in wind farms; secondly, the cooperative allocation strategy based on the Shapley value is designed to allocate the total cost of investing in and constructing the shared energy storage system; finally, it is demonstrated through examples that the method proposed in this paper effectively reduces the cost of the total investment in the energy storage system for new energy power plants, reduces the cost of wind abandonment penalties for new energy power plants, improves the output effect of new energy power plants, and increases the utilization rate of the shared energy storage power plant.

Energy ReportsVol. 12
Science and Technology Department of Xinjiang Uyghur Autonomous Region
Affordable and clean energy
Openalex Percentile: Top 11%
Integrated Energy Systems Optimization
2.30
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research on the optimal configuration method of shared energy storage basing on cooperative game in wind farms — Zhiqiang Zhao, Hongwei Zhou, et al. · Energy Reports (2024) | TGRS Research Map | TGRS