LAPSE:2023.7567v1
Published Article

LAPSE:2023.7567v1
Research on the Electricity Market Clearing Model for Renewable Energy
February 24, 2023
Abstract
The development of renewable energy in China has made remarkable achievements, but the problem of renewable energy consumption has become increasingly prominent. This paper establishes a power market trading system for renewable energy, with the aim of promoting large-scale renewable energy consumption and increasing the enthusiasm of renewable energy producers and users to participate in market transactions. First, according to the power generation cost, the backup cost of renewable energy power plants and the possible quotation strategies of other renewable energy producers, a quotation model of renewable energy producers is established. In the clearing of the spot market by renewable energy producers, the independent market operator conducts the first-stage clearing of the electricity market with the goal of maximizing social welfare. After the announcement of the clearing results, the renewable energy producers that did not win the bid will revise their quotations and carry out the second stage clearing to realize the consumption of renewable energy. In this paper, the particle swarm algorithm combined with the CPLEX solver is used to solve the problem, and finally, different scenarios are analyzed through example analysis. The results show that, compared with the conventional power market trading mechanism, the energy abandonment rate of the power market trading mechanism for renewable energy proposed in this paper drops from 8.2% to 2.1%, and the profit margin of renewable energy producers increase by 6.6%. It is demonstrated that the proposed electricity market mechanism can effectively promote the consumption of renewable energy and increase the income of renewable energy producers.
The development of renewable energy in China has made remarkable achievements, but the problem of renewable energy consumption has become increasingly prominent. This paper establishes a power market trading system for renewable energy, with the aim of promoting large-scale renewable energy consumption and increasing the enthusiasm of renewable energy producers and users to participate in market transactions. First, according to the power generation cost, the backup cost of renewable energy power plants and the possible quotation strategies of other renewable energy producers, a quotation model of renewable energy producers is established. In the clearing of the spot market by renewable energy producers, the independent market operator conducts the first-stage clearing of the electricity market with the goal of maximizing social welfare. After the announcement of the clearing results, the renewable energy producers that did not win the bid will revise their quotations and carry out the second stage clearing to realize the consumption of renewable energy. In this paper, the particle swarm algorithm combined with the CPLEX solver is used to solve the problem, and finally, different scenarios are analyzed through example analysis. The results show that, compared with the conventional power market trading mechanism, the energy abandonment rate of the power market trading mechanism for renewable energy proposed in this paper drops from 8.2% to 2.1%, and the profit margin of renewable energy producers increase by 6.6%. It is demonstrated that the proposed electricity market mechanism can effectively promote the consumption of renewable energy and increase the income of renewable energy producers.
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Keywords
clearing mechanism, electricity spot market, renewable energy consumption, wind power photovoltaic
Subject
Suggested Citation
Xu G, Wang X. Research on the Electricity Market Clearing Model for Renewable Energy. (2023). LAPSE:2023.7567v1
Author Affiliations
Xu G: School of Electrical Engineering, Xinjiang University, Urumqi 830017, China
Wang X: School of Electrical Engineering, Xinjiang University, Urumqi 830017, China
Wang X: School of Electrical Engineering, Xinjiang University, Urumqi 830017, China
Journal Name
Energies
Volume
15
Issue
23
First Page
9124
Year
2022
Publication Date
2022-12-01
ISSN
1996-1073
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PII: en15239124, Publication Type: Journal Article
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LAPSE:2023.7567v1
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https://doi.org/10.3390/en15239124
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Feb 24, 2023
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