Bidding strategy based on uncertainty decision for a Genco

To solve the problem of building optimal bidding strategies for a Genco, a model of uncertainty decision based bidding strategy is proposed. With incomplete information, a matrix of rewards is set up via estimating each rival's lowest bid. To reduce the state number, the max-min decision criterion is employed to pick up bidding strategies from the matrix of rewards for each hour period, where multiple-period auction is considered, and the dynamic programming is introduced to deal with start-up constraints. Compared with the existing methods, the model can be applied to produce an approached overall profit for the sample system with ten Gencos within 0.03 s. The simulation example is presented to illustrate the validity and practicability of the model.