An Analysis of Distribution Automation Reliability Using Monte Carlo Simulation

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Norsabrina Binti Madzlan
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This project is about simulation on distribution automation technique (DAT) using Monte Carlo Simulation (MCS). The main idea behind is to improve the power system network and the efficiency by evaluating reliability performances. Therefore, in order to improve the reliability, three case studies have been conducted in this project. To prove the validity of the research, a real power distribution of 11 kV underground distribution network will be performed as a case study. The reliability analysis is using the MCS, that provides a random behaviour creates important parameters such as failure rate, hour and unavailability. The parameter is very important to calculate the reliability indices. The objective of the project is to identify the effect of the distribution automation system reliability due to disturbances, to analyse the distribution automation system using Monte Carlo Simulation for radial distribution network and recommend ways to improve system reliability. The reliability indices studied in this project are SAIDI, SAIFI and CAIDI. The results are presented in the form of comparative study between none automated and automated distribution network. The results show that automated distribution network is best technique to improve system performance indices and has an acceptable results of reliability indices.
FYP 2 SEM 2 2019/2020
Reliability Analysis