Agent-based modeling for trading wind power with uncertainty in the day-ahead wholesale electricity markets of single-sided auctions
DOI: 10.1016/J.APENERGY.2012.04.022
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摘要: Abstract This paper, for the first time, adopts agent-based simulation approach to investigate bidding optimization of a wind generation company in deregulated day-ahead electricity wholesale markets, by considering effect short-term forecasting accuracy power generation. Two different penetration levels (12% and 24%) are investigated compared. Based on MATPOWER 4.0 software package 9-bus 3-generator system defined Western System Coordinating Council, models built run under uniform price auction rule locational marginal pricing mechanism. Each could learn from its past experience improves strategic offers using Variant Roth–Erev reinforcement learning algorithm. The results clearly demonstrate that improving helps increase net earnings company. Also, can further with adoption Besides, it is verified increasing level within investigation range help reduce market clearing price. Furthermore, also demonstrated viable modeling tool which provide realistic insights complex interactions among participants various factors.
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