Open AccessBidding strategy of thermal power compound differential evolution game under the market mechanism of peak regulation auxiliary service
Author(s) -
Dong Fugui,
Li Wanying,
Ji Zhengsen,
Fatema Shafaq
Publication year - 2021
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/gtd2.12141
Subject(s) - bidding , revenue , service (business) , ebidding , mathematical optimization , computer science , differential evolution , game theory , thermal power station , power (physics) , microeconomics , economics , mathematics , engineering , finance , electrical engineering , economy , physics , quantum mechanics
As the main provider of peak regulation auxiliary services, thermal power units are particularly important to ensure their revenue in an uncertain environment. To obtain the optimal bidding strategy for thermal power units, a thermal power peak regulation bidding model based on the Northeast Power Grid's auxiliary service market bidding mechanism is established. Secondly, the evolutionary game theory is introduced into the bidding strategy of thermal power units. Meanwhile, in order to solve the multi‐party game problem, a compound differential evolution game algorithm is constructed to solve the two‐tiers bidding. Finally, based on the actual operating data of a typical day, the efficiency of the compound differential evolution game algorithm bidding strategy is verified, and the bidding strategy of thermal power units in different situations is discussed. The results show that when all units participate in peak regulation, the first‐tier quotation is an optimal strategy at 0.19 yuan kWh −1 and below, and the second‐tier quotation is distributed between 0.6–0.8 yuan kWh −1 . When only some units are involved in peak regulation, the first‐tier quotation of thermal power units adopts a high price strategy, mostly at 0.3 yuan kWh −1 , and the second‐tier quotation is still based on a high price strategy.