Multi-objective optimal operation incorporating wind power

In this paper, a wind generation cost model reflecting the intermittency of wind power is proposed and integrated into a multi-objective optimal operation issue of power system. The proposed wind generation cost model is based on the frequency distribution of wind farm power output, which is obtained by applying Monte Carlo simulation to the wind speed model. Total 3 objectives involving minimization of power generation costs (inclusion of wind generation), minimization of pollution emissions and minimization of transmission losses as well as the small signal stability constraints are considered during modelling. An improved evolutionary algorithm called as self-adaptive evolutionary programming (SAEP) is employed to solve the multi-objective optimal operation problem with wind power incorporated. The IEEE New England test system is employed as benchmark to carry out the case studies. Numerical results illustrate the effectiveness and validity of the proposed model and method.