A generalized normal distribution optimization for optimal power flow with solar and wind power

In this study, a Generalized Normal Distribution Optimization was presented to resolve the optimal power flow problem that integrated solar and wind energies with stochasticity. Solar and wind plants, along with conventional generators, were coordinated to optimize the total generation costs through the optimal power flow problem. As part of the objective function, emission costs were also included. The uncertainty of solar and wind power was calculated according to Weibull and lognormal probability distribution functions. Accordingly, solar and wind power generation costs comprise direct, reserve, and penalty components. The developed optimization method was tested and compared to published results for the IEEE 30 bus network, indicating that the Generalized Normal Distribution Optimization provides a highly promising solution to optimal power flow problems.