Distribution network reconfiguration (DNR) and distribution generation (DG) sizing simultaneously based on rank evolutionary particle swarm optimization (REPSO)

Nur Faziera , Napis (2014) Distribution network reconfiguration (DNR) and distribution generation (DG) sizing simultaneously based on rank evolutionary particle swarm optimization (REPSO). Project Report. UTeM. (Submitted)

Text DISTRIBUTION NETWORK RECONFIGURATION (DNR) AND DISTRIBUTION GENERATION (DG) SIZING SIMULTANEOUSLY BASED ON RANK EVOLUTIONARY PARTICLE SWARM OPTIMIZATION (REPSO) 24pages.pdf Download (286kB)

Abstract

The detrimental of losses in the network can be solved by using Distribution Network Reconfiguration (DNR) and sizing the Distribution Generation (DG) concurrently. An energy policy promote the distributed power sources like power competencies, Distribution Generation (DG), power storage devices, and sources of renewable energy, increase the number of Distribution Generation (DG) installations and manufacturing resources, particularly variable as wind, solar, small hydropower and the combination of heat and power. In determining the optimal sizing of Distribution Generation (DG) and identifying the switching operation plan for network reconfiguration, an optimization method which is called as Rank Evolutionary Particle Swarm Optimization (REPSO) has been introduced. The main objectives of this study are to minimize the total power losses in a radial distribution network and to find the most suitable and acceptable size of Distribution Generation (DG). A comprehensive performance analysis has been carried out on IEEE-33 bus system to show the effectiveness of the Rank Evolutionary Particle Swarm Optimization (REPSO) over conventional Particle Swarm Optimization (PSO) and hybridization Evolutionary Particle Swarm Optimization (EPSO) method. The reliability of the proposed method will hope to help the power system engineer in reducing the distribution feeder losses and improve system security in the future by changing the switches status and give optimal size of Distribution Generation (DG).

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