Medium/long-term virtual power plant aggregation method based on capacity leasing

VPP is an important form of energy organization in the new power system. This paper presents a medium/long-term virtual power plant aggregation method, which forms a VPP through capacity leasing. A VPP risk decision-making model is provided to select suitable distributed energy resources to form the VPP. The calculation based on actual data shows that: 1) Although VPPs with medium to long-term alliances can operate normally under existing conditions, there are significant risks involved; 2) The main tools for controlling risks are: selecting appropriate distributed resource combinations, utilizing forward contracts, and participating in frequency regulation; 3) The risk decision-making tool for distributed energy resource alliance provided in this paper can provide effective decision support.

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Published
2024-09-27
DOI
https://doi.org/10.1117/12.3037708
Primary Topic
Power Systems and Renewable Energy
Type
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article

Medium/long-term virtual power plant aggregation method based on capacity leasing

Bin Zou, zhaoling Li
Power Systems and Renewable Energy
article

Medium/long-term virtual power plant aggregation method based on capacity leasing

Bin Zou, zhaoling Li
article en

Abstract

VPP is an important form of energy organization in the new power system. This paper presents a medium/long-term virtual power plant aggregation method, which forms a VPP through capacity leasing. A VPP risk decision-making model is provided to select suitable distributed energy resources to form the VPP. The calculation based on actual data shows that: 1) Although VPPs with medium to long-term alliances can operate normally under existing conditions, there are significant risks involved; 2) The main tools for controlling risks are: selecting appropriate distributed resource combinations, utilizing forward contracts, and participating in frequency regulation; 3) The risk decision-making tool for distributed energy resource alliance provided in this paper can provide effective decision support.

Shanghai University (CN)
Openalex Percentile: Top 85%
Power Systems and Renewable Energy
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