A Distribution Network Reconfiguration (DNR) Of 132/11KV Distribution Network Using Improved Genetic Algorithms (IGA)

Mohamad Shah, Mustafa (2015) A Distribution Network Reconfiguration (DNR) Of 132/11KV Distribution Network Using Improved Genetic Algorithms (IGA). Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text (24 pages) A Distribution Network Reconfiguration (DNR) Of 132 11KV Distribution Network Using Improved Genetic Algorithms (IGA) 24 Pages.pdf - Submitted Version Download (301kB)

Abstract

The function of distribution system is to deliver power to the customers continuously. However, the increasing amount of load demand has affected the reliability and effectiveness of the distribution system due to the increasing in power losses. Hence, the distribution network reconfiguration (DNR) method is introduced. The initial network is reconfigured by changing the status of tie-switches and sectionalizing switches located at certain points in the network to find the best route that has the lowest power losses. At the same time, a radial network structure is maintained with all loads energized. Multiple parameter constraints are considered for real-power loss reduction, in which all buses voltage profile is kept within a range and is not allowed to exceed their rated capacities. Since the complex branch network, thus genetic algorithm is used to ensure that the DNR process is completed immediately. In addition, the percentage of power losses reduction in the distribution system can be increase by utilizing a small scale power generation known as distribution generation (DG) into the network system. In this project an implementation of DNR using an improved genetic algorithm (IGA) is applied to IEEE 69 bus system to verify the validity and effectiveness of the proposed algorithm. The task consists of two parts; first is the DNR without DG while the other part is the DNR with DG for the identified of IEEE bus system. The results show that the reconfiguration process has given a great impact in term of power losses reduction and voltage profile improvement. Besides that, the participation from distribution generator (DG) make the distribution system perform greater than before DG installation. From the results, the performance of the selection and crossover IGA is better than of the other approaches which is GA, selection IGA and crossover IGA.

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