Research on Microgrid Operational Economy Based on Energy Storage Optimization

With the growing global energy demand and worsening environmental issues, microgrids have gained attention for integrating renewable energy. However, their economic operation is challenged by the volatility of renewable energy, making efficient operation a key research focus. This study collected and integrated microgrid data from three parks and established a microgrid energy storage optimization model using the NSWOA algorithm. Economic indices were calculated through methods like the composite rectangle formula and sensitivity analysis, focusing on key factors such as the price of the main power station and wind power costs. The study found that coordinated configuration of wind, solar, and storage systems improved economic efficiency by 1% to 4% across the three parks. Based on these findings, optimal operation strategies and power purchase plans were developed, with the recommendation that wind power and storage be prioritized during peak periods, supplemented by power purchases from the main grid. Excess power should be stored to reduce the abandonment of wind power generation. This study provides a framework for enhancing the stability and economic viability of renewable energy systems and offers decision support for coordinated wind and storage allocation and economic power purchase strategies.

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Publication Details

Journal
Transactions on Computer Science and Intelligent Systems Research
Published
2024-10-17
DOI
https://doi.org/10.62051/cfsfs591
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Research on Microgrid Operational Economy Based on Energy Storage Optimization

Hai Lan, Zhe Zhao, Qin Wang
Transactions on Computer Science and Intelligent Systems Research
Power Systems and Renewable Energy
article

Research on Microgrid Operational Economy Based on Energy Storage Optimization

Hai Lan, Zhe Zhao, Qin Wang
article en

Abstract

With the growing global energy demand and worsening environmental issues, microgrids have gained attention for integrating renewable energy. However, their economic operation is challenged by the volatility of renewable energy, making efficient operation a key research focus. This study collected and integrated microgrid data from three parks and established a microgrid energy storage optimization model using the NSWOA algorithm. Economic indices were calculated through methods like the composite rectangle formula and sensitivity analysis, focusing on key factors such as the price of the main power station and wind power costs. The study found that coordinated configuration of wind, solar, and storage systems improved economic efficiency by 1% to 4% across the three parks. Based on these findings, optimal operation strategies and power purchase plans were developed, with the recommendation that wind power and storage be prioritized during peak periods, supplemented by power purchases from the main grid. Excess power should be stored to reduce the abandonment of wind power generation. This study provides a framework for enhancing the stability and economic viability of renewable energy systems and offers decision support for coordinated wind and storage allocation and economic power purchase strategies.

Transactions on Computer Science and Intelligent Systems ResearchVol. 6
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Openalex Percentile: Top 83%
Power Systems and Renewable Energy
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Research on Microgrid Operational Economy Based on Energy Storage Optimization — Hai Lan, Zhe Zhao, et al. · Transactions on Computer Science and Intelligent Systems Research (2024) | TGRS Research Map | TGRS