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Virtual Power Plant Participates in the Two-Level Decision-Making Optimization of Internal Purchase and Sale of Electricity and External Multi-Market
- Source :
- IEEE Access, Vol 9, Pp 133625-133640 (2021)
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- The power industry’s participation in carbon trading and green certificate trading is an effective market-based approach to solve the negative externalities of power production. In this paper, the Virtual power plant (VPP) is taken as the aggregator to coordinate and optimize the carbon trading and green certificate trading between the power purchasing end and the power selling end, so as to achieve the goal of maximizing the comprehensive benefits of the VPP. Firstly, the operation model of VPP aggregating various types of distributed energy and different users participating in green certificate market and carbon trading market is analyzed; Secondly, a two-level collaborative optimization model of VPP participating in power purchase and sale transaction and green certificate transaction is constructed. On the one hand, the cost of power purchase and green certificate acquisition is minimized by combining various types of power generation resources at the power purchase end. On the other hand, the power purchased is distributed among various types of users at the power sale end, so as to maximize the power sale income and green certificate sales income. On this basis, the VPP as a whole participates in the electric energy market, carbon trading market and green certificate trading market to maximize the comprehensive income. Finally, a VPP is taken as an example to verify the economy and effectiveness of the proposed model in this paper.
- Subjects :
- Comprehensive income
General Computer Science
business.industry
Green certificate trading
General Engineering
VPP
Environmental economics
decision optimization
Purchasing
Green certificate
TK1-9971
Virtual power plant
Electricity generation
Distributed generation
optimal scheduling
General Materials Science
Business
Emissions trading
Electrical engineering. Electronics. Nuclear engineering
Electric power industry
carbon trading
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....4c8f9f1b160be859d515866f219d1c2d