Multi-agent based experiments on uniform price and pay-as-bid electricity auction markets

Abstract

Discriminatory pricing rule or pay-as-bid pricing rule has been proposed to replace the uniform pricing rule in the deregulated electricity markets, with the expectation that it would lower market prices and reduce price volatility. Using a multi-agent approach, where each adaptive agent represents a generator who develops bid prices based on Q-learning algorithm, the pay-as-bid auction and the uniform price auction are compared. The experimental results show that the pay-as-bid auction indeed results in lower market prices and price volatility, as expected. Also the experimental results show that the demand-side response has less effect on the reduction of market prices in the pay-as-bid auction, because bidders in the pay-as-bid auction bid as close to the market prices as possible and this makes the aggregate supply curve more flattened than that in the uniform price auction.