Solving dynamic economic emission dispatch problem considering wind power by multi-objective differential evolution with ensemble of selection method

Clean energy resources such as wind power are playing an important role in power generation recently. In this paper, a modified version of multi-objective differential evolution (MODE) is used to tackle the extended dynamic economic emission dispatch (DEED) problem by incorporating wind power plant into the system. DEED is a nonlinear and highly constrained multi-objective optimization problem and the predicted load is varying with time. Fuel costs and pollution emission are the two objectives to be optimized and the valve point effect, spinning reserve, real power loss as well as the ramping rate are considered. To solve the model effectively, an ensemble of selection method is used in the MODE algorithm. The real-time output adjustment and penalty factor methods are used to deal with the complex constraints. The proposed method is firstly examined on several multi-objective benchmark problems and the DEED problem without considering the wind power to test its effectiveness of solving multi-objective optimization problems. Secondly, the model considering wind power is solved and the results show that the proposed algorithm is effective in handling such problems.