With the growing development in demand response, load serving entities (LSEs) may participate in electricity market as strategic bidders by offering coupon-based demand response (C-DR) programs to customers. However, due to customers' versatile electricity consumption patterns under C-DR programs as well as the increasing penetration of wind power generation, obtaining the deterministic bidding decision becomes unprecedented complex for LSEs. To address this challenge, a new strategic bidding model for an LSE is proposed in which the primary objective is to maximize the LSE's profit by providing optimal C-DR considering high wind power penetration. The proposed strategic bidding is a bi-level optimization problem with the LSE's net revenue maximization as the upper level problem and the ISO's economic dispatch (ED) for generation cost minimization as the lower level problem. This bi-level model is converted to a stochastic mathematic program with equilibrium constraints (MPEC) by recasting the lower level problem as its Karush-Kuhn-Tucher (KKT) optimality conditions. Then, the stochastic MPEC is transformed to a mixed-integer linear programming (MILP) problem, which is solvable using available optimization software, based on strong duality theory. In addition, the effectiveness of the proposed method has been verified with simulation studies of two sample systems.