An Analysis of Market Mechanism and Bidding Strategy for Power Balancing Market in Micro-grid

With the penetration of renewable energy sources such as photovoltaics or wind power, it becomes a more important issue to keep power system stable in terms of power balance with proper frequency. To this end, balancing markets have been developed and utilized in order to ensure the security of frequency regulation with lower cost based on the market principle. For example, in the European countries and regions, secondary and tertiary control balancing energy have been traded through balancing markets. Although the details about those market mechanisms are different from country to country, there are two mainstreams: "uniform-price auction" based on marginal fuel cost and "pay-as-bid auction" with discriminatory pricing. Under the uniform-price auctions, all players whose biddings are cleared receive the same market-clearing price which is the highest offer price cleared. In contrast, in the case of pay-as-bid auction, prices paid to cleared players are based on their own actual discriminatory bidding price, rather than the highest clearing price. For power suppliers, one of the most important issues is how to determine the bidding strategy in the electricity balancing auction market to satisfy their profit maximizing goals. In this paper, supposing the frequency regulation in Micro-grid will be also realized based on balancing market, fundamental characteristics of two auction mechanisms, uniform-price and pay-as-bid methods, were examined. The behavior of each player in the balancing market, namely bidding strategy, is modelled by using Q-Learning algorithm to maximize player's profit. In this approach, the bidding strategy is regarded as one kind of stochastic optimal control problems and agent-based simulations are performed in which each player can learn from past experience. The performance comparison of the balancing market is discussed based on the simulation results.