Solution of optimal power flow with wind power uncertainty using hybridized self-adaptive differential evolution.

The current research presents an optimal power flow (OPF) solution in an electrical system network with the integration of wind power using enhanced self-adaptive differential evolution method with a mixed crossover (ESDE-MC). A model for wind power cost is considered, which contemplates the random nature of wind speed based on Weibull probability density function. The wind energy cost model incorporates the estimated reserve and penalty cost for wind power shortfall and surplus, respectively. In the present work, the wound rotor induction generator (WRIG) model is being utilized for wind power production. Further, WRIGs reactive power (Q) - voltage (V) formulation is developed and is enhanced by changes to conventional power flows. In order to verify the performance and reliability of the proposed method, modified IEEE 30-bus, and IEEE 57-bus systems are considered to solve the OPF with the minimization of thermal generation cost inclusion of wind power. The proposed ESDE-MC method achieved 2788.69$/h which is 8.4 $/h less value in comparison to the best optimal value in the existed literature for IEEE 57-bu system in less computational time. Like these, for IEEE 30 bus system also propose method is proved best optimal value in comparison to all the other methods in the literature. Furthermore, Kruskal-Wallis test is performed to show the effectiveness of the proposed ESDE-MC method.