Recently, with the penetration of renewable energy sources, the balancing market becomes more important worldwide. With the purpose of profit-maximization, suppliers are constantly researching the bidding strategy when bidding into the auction of balancing market. There are two mainstreams of auction mechanisms in balancing markets: “uniform-price auction” based on marginal fuel cost and “pay-as-bid auction” with discriminatory pricing. We have so far analyzed the difference of the clearing point given by both these two mechanisms. Here, the bidding strategy of market participants were modelled by using Q-Learning in which expected final reward of each player in the balancing market was maximized. The simulation result also depends on the simulation model, in particular, the marginal cost of generating plants. So, it is necessary for us to explore the various simulation settings to find out the desirable market mechanism. On the other hand, in Japan, the balancing market should be set out in the future as real time market. Under this condition, in this paper, we mainly evaluate the rationality of the trading based on the uniform-price and pay-as-bid auction mechanisms by using more realistic power system model considering the future power and energy situation in Japan.
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