heshmatallah nourizadeh

Due to the increasing load growth and expansion and significant changes in structure of electricity distribution networks, the issues related to the optimization of these networks face many challenges. Optimal placement and capacity of Distribution substations and their feeder networks are among the important issues of optimization of distribution networks from technical and economic viewpoints. In this paper, considering two important factors including loss reduction and improvement of reliability in distribution networks, a new multi-objective function was presented for optimal placement of location and capacity of Distribution substations based on their service area. The proposed objective function includes all construction and operation costs of equipment, loss costs, and reliability index (Energy Not Supplied). The Artificial Bee Colony (ABC) algorithm was applied to optimize the proposed objective function with the purpose of determining the optimal placement and capacity of substations of two sample distribution networks. A comparison of results obtained from optimization of the proposed objective function by the Artificial Bee Colony (ABC) algorithm with results of other algorithms in two sample networks indicates the efficiency and effectiveness of the proposed algorithm and objective function.

One of the most critical and complex issues in long-term planning of distribution networks is the optimal placement of distribution transformers. In this paper, the optimal placement of distribution transformers was investigated based on a complete and multi-objective function. In the proposed method, location, optimal capacity, and the service area are determined by minimizing costs (investment, operation, reliability) and improving reliability and power quality parameters (voltage drop) due to electric restrictions (radial structure, voltage drop and equipment capacities). The planning of distribution networks is complicated due to the existence of numerous and multiple-criteria decision-making variables in objective functions; hence in this paper, the symbiotic organisms search (SOS) algorithm was used as a new heuristic optimization algorithm to solve the problem of long-term planning of distribution networks. The proposed method is tested on a real distribution network to evaluate the performance of the proposed algorithm,  Comparing the results of the proposed algorithm with the results of studies with genetic algorithms (GA), biogeography-based optimization (BBO) and imperialist competitive algorithm (ICA), indicates the performance and advantages of the proposed algorithm over other algorithms.