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Research on Optimization Strategy for Low Carbon Joint Trading of Virtual Power Plants Considering Aggregatable Resources

Published: 31 July 2024 Publication History

Abstract

This study focuses on low-carbon trading optimization strategies for virtual power plants to enhance energy efficiency and renewable energy use. It evaluates the maximum resources that virtual power plants can aggregate, considering technological and economic aspects on the source side and adjustable capacities on the load side. The study designs a framework for low-carbon virtual power plant operations, with individual modeling for each unit. It then develops an optimization strategy for these plants to engage in electricity, carbon trading, and peak shaving markets. A regional case study validates the model's effectiveness.

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    PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial Intelligence
    January 2024
    969 pages
    ISBN:9798400716638
    DOI:10.1145/3674225
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 31 July 2024

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