Bidding strategy for participation of virtual power plant in energy market considering uncertainty of generation and market price

Mohsen Khorasany, Mahdi Raoofat

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

5 Citations (Scopus)


Due to the small capacity of DGs, their individual participation in the energy market is not beneficial. In the case of wind and solar plants, their uncertain power generation is another issue for their participation in the market, especially when their capacity is low. Commercial Virtual Power Plant (CVPP) is a new market participant, which represents a group of various DGs in the market, and bids to the market. This paper proposes a new bidding strategy approach for the participation of CVPP in the day-ahead energy market, considering uncertainties of wind turbine generation and Market Clearing Price (MCP). The market is pay as bid, and each participant bids a multi-step price-power curve. The uncertainty of MCP has formulated analytically, while the wind uncertainty is modeled by a quantized Rayleigh probability distribution function. Particle Swarm Optimization (PSO) algorithm is utilized for optimizing the objective function, which is the expected benefit of the CVPP. Numerical results are provided to evaluate the performance of proposed approach in increasing the benefit of VPP.

Original languageEnglish
Title of host publication2017 Smart Grid Conference (SGC 2017)
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781538642795
ISBN (Print)9781538642801
Publication statusPublished - 2017
Externally publishedYes
EventIEEE Smart Grid Conference 2017 - Tehran, Iran
Duration: 20 Dec 201721 Dec 2017


ConferenceIEEE Smart Grid Conference 2017
Abbreviated titleSGC 2017


  • Commercial Virtual Power Plant (CVPP)
  • component
  • Electricity Market
  • Energy Storage Device (ESD)
  • Uncertainty
  • Wind Energy

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