Optimal integrated planning of MV-LV distribution systems using DPSO
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A new technique for optimal planning of MV and LV segments of a distribution system is presented in this paper. The main goal is to find optimally distribution transformer and substation locations and ratings, as well as, the route and type of Medium Voltage (MV) and Low Voltage (LV) feeders. The proposed technique is applicable to both uniform and non-uniform load densities areas. In this method, the planning area is divided into regions with relatively uniform load density such as urban, semi-urban, sub-urban. Each of regions is divided into zones, called LV zone. Each LV zone is supplied by an MV/LV transformer. The dimensions of LV zones are found based on the average load of each region. The placement and rating of MV/LV transformers, the type and route of LV conductors in an LV zone all depend on its loads’ location and power. Regarding the placement and rating of MV/LV transformers in planning area and the space of regions, the dimensions of a zone which is supplied by a HV/MV transformer, called MV zone, is determined. Additionally, the location and rating of HV/MV transformers as well as the feeder’s routes and types are calculated. Since the dimensions of an LV zone influence the associated length of MV feeder, the MV feeder cost needs to be included in the total cost associated with the LV zone. This requires the MV feeder type to be known to calculate the corresponding cost. However, the MV feeder type is determined as an output from MV zone planning. As a result, an iterative based method is proposed to consider this common element in computations to develop integrated planning of both LV and MV zones. It is observed that the iterative technique quickly converges to the same results as the exhaustive search method. Discrete particle swarm optimization (DPSO) method is employed for solving the planning problem. The results are compared with nonlinear programming, genetic algorithm and exhaustive search methods. It is observed that DPSO is as accurate as the exhaustive search method for integrated planning of MV–LV distribution systems while its computation time is significantly lower.
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