In winter heating period, the heating mode of “determining power by heating load” in Northeast China causes tremendous wind curtailment. And wind power accommodation by thermal storage becomes an effective solution. Wind curtailment is random and its price elasticity is small. Thermal storage demand is controllable and its price elasticity is big. Thus in wind accommodation by thermal storage market, curtailment of wind power and load which is in conventional electric power market has similar property and property of thermal storage demand is analogous to conventional electricity generation. After analyzing wind curtailment and thermal storage’s peculiarity, this paper proposes a bidding strategy algorithm which is based on linear supply function model. The algorithm fully considers wind curtailment randomness and thermal storage demand elasticity’s impact on market clearing prices. This method describes bidding strategies by stochastic variable which is handled by scene classification. By using data of Liaoning Province wind curtailment in 2013 for case analysis, this paper has verified effectiveness and practicability of the proposed algorithm. This work is supported by Key Project of the National Science and Technology Program of China (No. 2015BAA01B02).