Dynamic construction strategy of the virtual power plant based on day-ahead-intraday joint scheduling

As a new technological form, the virtual power plant can aggregate the distributed resources of each plant to explore the potential of distributed energy scheduling deeply. How to coordinate the scheduling of each power-generating body to improve the overall profitability and low-carbon operation ha...

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Published in:Journal of physics. Conference series Vol. 2896; no. 1; pp. 12069 - 12078
Main Authors: Wang, Su, Chen, Peng, Fu, Chen, Ran, Lü, Lan, Li
Format: Journal Article
Language:English
Published: Bristol IOP Publishing 01.11.2024
Subjects:
Algorithms
Alternative energy
Distributed generation
Electric vehicles
Energy management
Energy storage
Power plants
Renewable energy
Renewable resources
Resource scheduling
Scheduling
Storage equipment
Uncertainty
Virtual power plants
ISSN:1742-6588, 1742-6596
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Abstract As a new technological form, the virtual power plant can aggregate the distributed resources of each plant to explore the potential of distributed energy scheduling deeply. How to coordinate the scheduling of each power-generating body to improve the overall profitability and low-carbon operation has become an important issue that needs to be solved urgently. Therefore, in this paper, considering the non-renewability of traditional energy sources, the uncertainty of renewable energy output power, and the limitations of energy storage equipment within the virtual power plant, we design a day-ahead-intraday operation strategy. This strategy is facilitated by demand response guidance and the rapid response of electric vehicles to participate in the intraday optimal scheduling of the virtual power plant and to balance the internal output error. It also uses the improved multi-objective particle swarm algorithm to obtain the virtual power plant for each part of the output power. The simulation results show that the EV aggregator combined with energy storage equipment reduces the impact of renewable energy output uncertainty on the virtual power plant and reduces the large-scale investment in energy storage equipment in the virtual power plant in a short period. At the same time, it brings economic benefits to the EV aggregator, making the EV aggregator’s participation in the scheduling of the virtual power plant more valuable for practical applications.
AbstractList As a new technological form, the virtual power plant can aggregate the distributed resources of each plant to explore the potential of distributed energy scheduling deeply. How to coordinate the scheduling of each power-generating body to improve the overall profitability and low-carbon operation has become an important issue that needs to be solved urgently. Therefore, in this paper, considering the non-renewability of traditional energy sources, the uncertainty of renewable energy output power, and the limitations of energy storage equipment within the virtual power plant, we design a day-ahead-intraday operation strategy. This strategy is facilitated by demand response guidance and the rapid response of electric vehicles to participate in the intraday optimal scheduling of the virtual power plant and to balance the internal output error. It also uses the improved multi-objective particle swarm algorithm to obtain the virtual power plant for each part of the output power. The simulation results show that the EV aggregator combined with energy storage equipment reduces the impact of renewable energy output uncertainty on the virtual power plant and reduces the large-scale investment in energy storage equipment in the virtual power plant in a short period. At the same time, it brings economic benefits to the EV aggregator, making the EV aggregator’s participation in the scheduling of the virtual power plant more valuable for practical applications.
Author Lan, Li
Fu, Chen
Ran, Lü
Wang, Su
Chen, Peng
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  organization: State Grid Economic and Technological Research Institute Co., Ltd ., Shanghai, 200000, China
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Cites_doi 10.1109/TIA.2021.3100321
10.1109/TPWRS.2011.2161350
10.1109/TPWRS.2017.2741920
10.1016/j.segan.2022.100964
10.1109/TSG.2013.2248399
10.1016/j.icheatmasstransfer.2022.105896
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SubjectTerms Algorithms
Alternative energy
Distributed generation
Electric vehicles
Energy management
Energy storage
Power plants
Renewable energy
Renewable resources
Resource scheduling
Scheduling
Storage equipment
Uncertainty
Virtual power plants
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Title Dynamic construction strategy of the virtual power plant based on day-ahead-intraday joint scheduling
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