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Bi-level multi-time scale scheduling method based on bidding for multi-operator virtual power plant
- Source :
- Applied Energy. 249:178-189
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- With the development of energy internet and power market, the operation regulation and pricing mechanism of traditional virtual power plants are improved to adapt to the new environment. In this paper, a bi-level multi-time scale scheduling method based on bidding for multi-operator virtual power plant is proposed to provide a framework for solving the interest distribution between operators and optimal scheduling problems of multiple-operator virtual power plant. An operator power allocation and internal electricity price formation method based on bidding equilibrium is proposed in the upper level, which introduces the fluctuation cost coefficient to express the influence of the uncertainty of renewable energy power generation on the bidding process. A multi-time scale optimal scheduling method combining scheduling model and adjustment strategy is established in the lower level. A default penalty mechanism in the scheduling model is used to ensure that operators provide the electricity allocated from the bidding process and considering the influence of demand response based on internal electricity price on adjustment strategy. Simulation results show that the proposed method can realize the optimal distribution of operators’ power generation and form the internal electricity price that reflects the internal supply and demand level of virtual power plant. Besides, it can reduce the impact of uncertainty on dispatching results and improve the application range of virtual power plant to enhance the competitiveness of virtual power plant in market transactions.
- Subjects :
- Mathematical optimization
Computer science
business.industry
Mechanical Engineering
Scheduling (production processes)
Building and Construction
Management, Monitoring, Policy and Law
Bidding
Renewable energy
Supply and demand
Demand response
Virtual power plant
General Energy
Electricity generation
Electricity
business
Subjects
Details
- ISSN :
- 03062619
- Volume :
- 249
- Database :
- OpenAIRE
- Journal :
- Applied Energy
- Accession number :
- edsair.doi...........d29ac14498b9cf36a6931c6783d8046e
- Full Text :
- https://doi.org/10.1016/j.apenergy.2019.04.130