Placement and Sizing of Various Renewable Generations in Distribution Networks with Consideration of Generation Uncertainties using Point Estimate Method

Abstract: Deploying Distributed Generation (DG) units has increased due to yearly increase of electric energy demand and technological advancements beyond Smart Grid. Although, DGs offer several advantages such as reducing economic costs and environmental impacts, the operation of these units in power systems creates several problems. In this paper, optimal allocation and sizing of DG units in radial distribution network with the aim of power losses reduction is investigated. Different types of DGs are considered in the proposed method. Moreover, the conventional and stochastic generation units are simultaneously considered. To calculate the uncertainty wind and photovoltaic generation, Weibull and Beta probabilistic distributions are used. The point estimation method is employed to estimate stochastic generation outputs. Modified Teaching-Learning-Based Optimization (TLBO) method is used to optimize the cost objective function while satisfying the constraints. Maximum injected power into network from DGs and maximum power generation of each unit are considered as problem constraints. Moreover, by installing each DG unit, the maximum generation power of the units is determined in order to reduce network power losses. The proposed method is implemented on 33-and-69-bus IEEE test systems. Simulation results proved that optimal network losses reduction is accomplished by installation of DG units.