A Capacity Allocation Strategy For Generation Company Using Sequence Operation Theory

The world-wide introduction of competition among power generators to break monopoly aims at developing power markets and achieving efficient utilization of social resources. In a multilevel electricity market, one of the key issues that the generation companies have to be faced with is how to allocate their limited generation capacity among such markets as contract market, day-ahead market as well as ancillary service market to achieve maximized revenue.In the completely competitive electricity market, individed generators bid according to their marginal costs. The market thus has the best efficiency. But the real electricity market is close to the oligopoly. The generators may adopt economic withholding or physical withholding to wield the market power and obtain more profit. This paper proposes an effective solution for the generators to solve the capability allocating and the bidding problems.In the full uncertainty markets, it's difficult for generators to control the risk resulting from the using of certainty analysis bidding strategy. So it's necessary to introduce the probability method. In view of the fact that both price and load are random, so the generator's capacity allocation is uncertainty. This paper uses the sequence theory to simulate the price probability distributing of the oligopoly market, proposes a united bidding model in the three markets and analyses the risk resulting from the participation of generators in a multilevel market.A new capacity allocation strategy is presented for generation companies under uncertain and multilevel electricity market environment. It describes the respective imperfect competition market models by sequence operation theory (SOT), and the profit of different decision-making schemes by introducing utility function in economic. Then the scheme with maximum utility is chosen as the optimal allocation one. Taking IEEE RTS 32-machine system for example, the allocation of capacity of individual generation companies to contract market, day-ahead market and spinning reserve market is analyzed. Simulation results show that the proposed method can provide an optimal capacity allocation scheme for generation companies.