Nowadays, the utilization of renewable energy resources in distribution systems (DSs) has been rapidly increased. Since distribution generation (DG) use renewable resources (i.e., biomass, wind and solar) are emerging as proper solutions for electricity generation. Regarding the tremendous deployment of DG, common distribution networks are undergoing a transition to DSs, and the common planning methods have become traditional in the high penetration level. Indeed, in conformity with the voltage violation challenge of these resources, this problem must be dealt with too. So, due to the high penetration of DG resources and nonlinear nature of most industrial loads, the planning of DG installation has become an important issue in power systems. The goal of this paper is to determine the planning of DG in distribution systems through smart grid to minimize losses and control grid factors. In this regard, the present work intending to propose a suitable method for the planning of DSs, the key properties of DS planning problem are evaluated from the various aspects, such as the allocation of DGs, and planning, and high-level uncertainties. Also depending on these analyses, this universal literature review addressed the updated study associated with DS planning. In this work, an operational design has been prepared for a higher performance of the power distribution system in the presence of DG. Artificial neural network (ANN) has been used as a method for voltage monitoring and generation output optimization. The findings of the study show that the proposed method can be utilized as a technique to improve the process of the distribution system under various penetration levels and in the presence of DG. Also, the findings revealed that the optimal use of ANN method leads to more controllable and apparent DS.
Power Distribution System Planning for Smart Grid Applications using ANN
