Optimal Placement and Sizing of Distributed Generation for Power Loss Minimization and Voltage Profile Improvement in Distribution Network (Case Study: Kombolcha Distribution System)

Abstract

The continuous power demand increment and increasing rate of urbanization need a good quality and reliable power supply system to satisfy the customer’s interest. On the other hand, the fast-increasing power demand cannot be met by the current passive distribution system or the expensive power transmission system from generation. The significant issues faced by the Ethiopian power distribution system, such as high-power loss, frequent power interruptions, and inadequate voltage magnitude, severely affect productivity of individual customers. This thesis presents the technique how to improve the performance of the distribution system by reducing the system power loss and enhancing the voltage profile through optimal allocation of distributed generation (DG) at Kombolcha-I substation outgoing distribution feeder three (L3). The feeder has 138 buses, and 74 loads. To assess the selected feeder's system power loss and voltage profile, the feeder was modeled in the MATLAB computational toolbox, and its load flow analysis was simulated using the backward/forward sweep (BFS) approach. From the BFS load flow results of the base case system, the total system real and reactive power loss of the selected feeder are 400.9144 kW and 404.8814 kVAr respectively and the magnitude of most of the buses are below the minimum standard limit. The objective function of this thesis work was to minimize both real and reactive power loss and enhance the voltage profile of the feeder by integrating the optimal DG size in the optimal location. This research uses a hybrid genetic algorithm and particle swarm optimization (GA-PSO) algorithm to find the optimal size and allocation of DG. The findings of this study demonstrate that proper DG sizing and placement enhance the performance of the distribution system. From the simulation results the active power loss percentage reduction was 45.944%, 51.0277%, 58.7234%, and 58.8331%, while the reactive power loss percentage reduction was 52.267%, 59.279%, 62.9945%, 62.4686% for1-DG, 2-DG, 3-DG, and 4-DG installation respectively. And also, the base case minimum voltage was improved from 0.9155p.u to 0.95016p.u, 0.95341p.u, 0.95489p.u and 0.9571p.u. For all cases, the bus voltage of the system was within the acceptable standard range. Th multi objective function (MOF) value was 0.02295, 0.02129, 0.021022, and 0.02082 for the integration of 1-DG, 2-DG, 3-DG, and 4-DG respectively. Furthermore, a comparison analysis has also been done to investigate the effectiveness of the proposed hybrid GA-PSO algorithm with other algorithms. The results obtained from the comparison indicate that, almost in all cases the hybrid GA-PSO method gives a better system performance by minimizing the system power loss, voltage profile improvement, and better fitness values. The cost analysis of DG integration showed that integration of 3-DG in the system needs an initial capital cost of 206,302,896.8 birr with a payback period of 4.782 years and it is an optimum solution.