Because of the random availability of wind energy, the economic emission scheduling (EED) problem with wind energy becomes more complex. Therefore, in order to solve this problem, this paper describes the problem as opportunity constrained to deal with the stochastic characteristics of wind power generation. A chaotic sine cosine algorithm (CSCA) is proposed to provide the optimal generation plan to minimize the generation cost and emission at the same time. The algorithm uses a chaotic sequence to replace the random number of an SCA, avoids premature convergence into a local optimum and improves the accuracy of solution. Finally, by comparing the real coded chemical reaction optimization algorithm with the hybrid artificial collaborative search algorithm based on quadratic approximation, the effectiveness and accuracy of the proposed method are demonstrated by two 10-unit case simulations. Finally, the impact of threshold level of constraints σ on optimization results is studied. When σ increases, the wind power permeability increases, resulting in the reduction of total production cost and emission value. This work is supported by the Science and Technology Project of State Grid Corporation of China (No. 5108- 202040024A-0-0-00).