SALP SWARM ALGORITHM BASED OPTIMAL NETWORK RECONFIGURATION WITH DISTRIBUTED GENERATION FOR POWER LOSS MINIMIZATION AND VOLTAGE PROFILE IMPROVEMENT (CASE STUDY: YIRGALEM SUBSTATION)

Abstract

In a distribution system, power loss and voltage deviation are the main concern for the customers and utility. The distribution system has a lower voltage level and higher amount of flowing current than the transmission system, so that, the percentage real power loss in the distribution system is higher. Therefore, this thesis work presents optimal network reconfiguration with the distributed generation of yirgalem radial distribution network to minimize the power loss, operation cost, and enhance the voltage profile of the distribution system using the Salp Swarm Algorithm (SSA). The resource feasibility of solar and wind power in yirgalem city was analyzed and the outcomes showed that solar power generation is more desirable. For this reason, the solar-type Distributed Generation (DG) is used. The proposed SSA algorithm was compared with Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA) in three various scenarios (only optimal network reconfiguration, only optimal DG size and site, and simultaneous optimal network reconfiguration and DG allocation) for the abosto feeder. After analysis of the three scenarios in MATLAB-R2016a, it can be concluded that the simultaneous network reconfiguration with DG shows a dominant result over only network reconfiguration and only DG allocation. The simulation result of base case backward forward sweep load flow analysis revealed that the abosto feeder has a base case power loss of 401.3KW. The feeder minimum voltage profile at the base case is 0.87pu. After simultaneous optimal network reconfiguration and DG size and site with SSA, the optimal tie switch open is 11, 25, 16, 42, 14 and the optimal location of the solar-type DG is at bus 23 and its size is found to be 895.3KW. Consequently, power loss of the selected abosto feeder is reduced to 101.5KW from the base case. The power loss reduction of the abosto feeder is 74.7% with respect to the base case loss. The voltage profile after optimal network reconfiguration with DG is improved by 11.4%. As per the economic evaluations, the proposed method is cost-effective. Depending on the findings of this thesis, it is concluded that optimal network reconfiguration with DG reduces power loss, operating cost and enhance the voltage profile of the distribution system.