OPTIMAL SITING AND SIZING OF DISTRIBUTED GENERATION USING MIX-INTEGER GENETIC ALGORITHM
Publication Date : 01/08/2018
Exponential growth in Distributed Generation (DG) penetration to low voltage (LV) distribution networks has been observed in recent years. This huge penetration of DG can be advantageous in light of environmental, economic and technical aspects when properly planned. However, if these systems are not appropriately planned, the reliability and stability of the network will be endangered or quality of the supply will be dreadfully jeopardized. Among the measures taken to avoid such is determining the optimal location and size of each DG unit in the distribution network. DG optimal placement is a non-linear, multi-objective, constrained and highly combinatorial optimization problem. In this study, an analytical approach coupled with meta-heuristic optimization technique; Mix-Integer Genetic Algorithm (GA) are employed to optimally determine the best locations and sizes of various types of DGs and electric vehicle (EV) charging stations in primary distribution network. The sole objective of the proposed technique is to minimize the power loss and improve bus voltage profile. Three well-known IEEE test distribution systems; 15, 33 and 69-bus systems modelled in MATLAB environment are used for testing the proposed technique. The simulation results demonstrate that the proposed approach is capable of finding both the optimal site and size of DG units simultaneously and accurately. From the optimized solution, the power loss and voltage deviation are reduced by almost 79% and 91%.
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