Comparative Analysis of the Optimal Siting and Sizing on Different Solar Distributed Generation Models Through Stochastic Method

With the optimization of solar distributed generation (DG), different methods and models are implemented for system improvement. However, the stochastic nature and intermittency of solar power is often neglected. This paper presents an approach in finding the optimal site and size of a solar DG unit in the context of minimizing power loss and improving voltage profile. Uncertainties of the solar irradiance are incorporated in the solar data. Also, different models of DG are considered, namely, unity power factor model, constant lagging power factor model and variable lagging power factor model. The technique is based on genetic algorithm (GA) and stochastic load flow calculations. The algorithm is applied to an IEEE 37-bus distribution system. The results indicate that a constant lagging power factor shows significant reductions on real and reactive power losses on the system with values of 19.179% and 21.004%, respectively. Also, the voltage deviation is reduced to 0.954 p.u.