Load Clustering Technique Application to PV Solar Rooftop Installation Planning for Improving Energy Efficiency Index

Abstract

This research paper presents to load clustering technique application to PV Solar rooftop installation planning at the center of Rajamangala University of Technology Isan. By considering the building load profile that has high continuous power consumption during the day which can improve the load factor which is the energy efficiency index to be higher. We collect the daily load profile of the 34 target buildings from the digital power meter and analyze of the load clustering by K-Means Clustering technic using the SPSS program. The results showed that load clustering can be divided into 3 groups. The first group, all buildings have low power consumption but high deviations of the load profile, low load factor level. The second group, Medium power consumption and minimize deviations of the load profile, high load factor. The third group, High power consumption, especially during the daytime, low load factor level. Therefore, Group 3 consist of 19 buildings has appropriate and setup to the plan for installation of PV solar rooftop. This will reduce the peak load demand from the Provincial Electricity Authority’s system, can improve the energy efficiency index.