6. Optimal Siting and Sizing of Wind Turbines Based on Genetic Algorithm and Optimal Power Flow

This chapter proposes a hybrid optimization method for optimal siting and sizing of wind turbines (WTs) that combines genetic algorithm (GA) and market-based optimal power flow (OPF). The method jointly minimizes total energy losses and maximizes social welfare (SW) considering different combinations of wind generation and load demand. The GA is used to choose the optimal size while the market-based OPF to determine the optimal number of WTs at each candidate bus. WTs are modeled with a PQ generator model, with a constant power factor. The stochastic nature of both load demand and wind power generation is modeled by hourly time series analysis. The interrelationships between demand and generation potential are preserved with their joint probability defining the number of coincident hours over a year. For each generation level, each WT is modeled with equivalent number of blocks in the WT’s offer with the same price dependent on the WT’s size. The method is conceived for distribution network operators (DNOs) to strategically allocate a number of WTs among different potential combinations. The effectiveness of the method is demonstrated with an 84-bus 11.4 kV radial distribution system.