With the growing maturity of wind power technologies and the decrease of wind power construction costs, wind power producers, who are always price takers, gradually participate in electricity market strategically. However, wind power producers should be responsible for the loss caused by bidding deviation when they participate in electricity market due to uncertainty of wind power, which can cut down their benefits. In order to reduce the impact of bidding deviation penalty on wind power producer's profit, a wind & thermal power joint (W&T) bidding strategy is proposed, in which the deviation electricity caused by the uncertainty of wind power can be compensated by thermal power units with flexible adjustment capability. At first, a W&T bidding model considering penalties for wind power's bidding deviation, which aims to maximize bidding profit of a W&T producer in day-ahead market, is established based on supply function equilibrium approach, in which Monte-Carlo method and backward reduction are used to simulate future wind power. Then, particle swarm optimization method are used to solve the model and obtain the optimal bidding strategy. Compared with the independent bidding, a simulation example shows that W&T bidding can effectively improve the revenues of wind power producers, especially increase the incomes from day-ahead market, so that the initiative of wind power producers in day-ahead market can be greatly enhanced.