New Energy Station Energy Storage Configuration Strategy Considering New Energy Consumption

This paper proposes an energy storage configuration method in new energy stations to promote the consumption of new energy. At first, the cost model included three sub-modules of energy storage systems is constructed based on the characteristics of energy storage. Then, taking the intermittency and uncertainty of new energy output into account, as well as the constraints of each energy source in the power generation process, an objective function is established with the goal of minimizing the comprehensive cost of energy storage. The improved cat swarm optimization algorithm (ICSOA) is utilized to solve the proposed model and determine the optimal energy storage configuration for new energy stations. Finally, the feasibility and correctness of the proposed model are verified through some case studies.

Authors

Institutions

Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/icpre62586.2024.10768648
Citations
3
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.51
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

New Energy Station Energy Storage Configuration Strategy Considering New Energy Consumption

Lidong Zhou, Leyi Wang, Yuan Yuan
3 citations
Power Systems and Renewable Energy
0.51
article

New Energy Station Energy Storage Configuration Strategy Considering New Energy Consumption

Lidong Zhou, Leyi Wang, Yuan Yuan
article en
3 citations

Abstract

This paper proposes an energy storage configuration method in new energy stations to promote the consumption of new energy. At first, the cost model included three sub-modules of energy storage systems is constructed based on the characteristics of energy storage. Then, taking the intermittency and uncertainty of new energy output into account, as well as the constraints of each energy source in the power generation process, an objective function is established with the goal of minimizing the comprehensive cost of energy storage. The improved cat swarm optimization algorithm (ICSOA) is utilized to solve the proposed model and determine the optimal energy storage configuration for new energy stations. Finally, the feasibility and correctness of the proposed model are verified through some case studies.

Taiyuan University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 28%
Power Systems and Renewable Energy
0.51
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.