Distribution Network Reconfiguration (DNR) And Voltage Stability Analysis For Radial Distribution Network Using Improved Genetic Algorithm (IGA)

Kamaruddin, Noor Fathin Nabila (2016) Distribution Network Reconfiguration (DNR) And Voltage Stability Analysis For Radial Distribution Network Using Improved Genetic Algorithm (IGA). Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

Text Distribution Network Reconfiguration (DNR) And Voltage Stability Analysis For Radial Distribution Network Using Improved Genetic Algorithm (IGA) - Noor Fathin Nabila Kamaruddin - 24 Pages.pdf - Submitted Version Download (173kB)

Abstract

Distribution system is carried out to improve the reliability, stability, efficiency and service quality of a system. An increment in load demand has affected the reliability and effectiveness of the distribution system. Operation and planning of large interconnected power system are becoming more complex with the increase in power demand, so power system will become less secure. It is important for distribution system to be more reliable, flexible and stable electric system. This project is to determine the best combination set of open switches with lowest power losses and maximum voltage stability. Thus, the distribution network reconfiguration (DNR) method is introduced to protect the distribution system. Distribution network reconfiguration (DNR) is applied to determine the best combination of open switches that acts as the best route to optimize the reduction of power losses during load restoration process. At the same time, a radial network structure is maintained with all loads energized. Another major concern in power distribution networks recently is the problem of voltage stability. Voltage stability is the ability of the power system to maintain the voltage at all buses system at normal operating condition and after the occurrence of disturbance. A disturbance or an increase in load demand causes an uncontrollable and continuous voltage drop in system voltage. The voltage drop occurs at the receiving end in the system can cause voltage collapse in a power system or even leads the system to be blackout. Therefore, by using voltage stability index (VSI), it is possible to compute the stability index value at every node. The most sensitive node that has the lowest voltage stability index might experience the voltage collapse. Improved Genetic Algorithm (IGA) is proposed in this project and tested on the IEEE 16 and IEEE 69 buses system using MATLAB vr2015b. The improvement of genetic algorithm is implemented at crossover operator. Double point and multi point crossover are now apply for IEEE 16 and IEEE 69 buses system respectively rather than single point crossover. The improvement of genetic algorithm shows that there is a reduction in power losses and increment in voltage stability index.

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