Improvement Of Radial Distribution Network With Distributed Generation (DG) By Using Improved Genetic Algorithm (IGA)

Azahar, Muhd Afif Fikri (2016) Improvement Of Radial Distribution Network With Distributed Generation (DG) By Using Improved Genetic Algorithm (IGA). Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

Text Improvement Of Radial Distribution Network With Distributed Generation (DG) By Using Improved Genetic Algorithm (IGA) - Muhd Afif Fikri Azahar - 24 Pages.pdf - Submitted Version Download (150kB)

Abstract

The distribution systems deliver power to the customers from a set of distribution substations and these are normally configured radially for effective co-ordination of the protective systems. The distribution system contains two types of switches which are sectionalizing switches (normally closed) and tie switches (normally opened). The functions of these two switches are for protection and configuration management in the system. Power losses in electrical power network are mainly come from the distribution system due to the increment in load demand. The growth of load demand has led to poor performances and efficiency of the distribution system. Therefore, distribution network reconfiguration (DNR) is introduced to solve the problem of power losses in distribution system. Distribution network reconfiguration (DNR) is a technique that resolves the group of tie-switches in the network that perform as the best route of optimal solution for power losses. Furthermore, the implementation of Distribution Generation (DG) in distribution system also helps to cater the power losses and fulfill the customers’ demand. Improved genetic algorithm (IGA) is proposed and tested on IEEE 33 and IEEE 69 bus system to ensure the validity and efficiency of the algorithm. There are two tested cases that are DNR without DG and DNR with DG. The results from the distribution network reconfiguration by using Improved Genetic Algorithm (IGA) help to reduce the total power losses and achieve faster computational time. Besides that, the presence of distribution generator (DG) makes the distribution system performs better than before DG installation. From the results, the performance of the crossover IGA is better than of the other approach that is GA.

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