Optimal generation bidding strategy for CHP units in deep peak regulation ancillary service market based on two-stage programming

Abstract

With the deepening of China’s electricity market reform, the diversity of combined heat and power (CHP) units participating in the energy market has greatly increased. To maximize the profit of CHP units, an optimal generation bidding strategy for deep peak regulation ancillary service market is proposed. Firstly, the uncertainty of loads is modelled with the Latin hypercube sampling (LHS) method. Secondly, in order to obtain the period when CHP units obtain higher profits in deep peak regulation ancillary service market, the first stage dispatch model is established. Thirdly, queueing method is applied to clear the ancillary service market. Then the clearing amount and price of the market are used to determine the bidding capacities of CHP units in the market. Finally, the second stage dispatch model and algorithm are established to maximize the operating profit of the target units. The proposed model and techniques are validated through case study.