Investigating Electricity Usage Profile for Residential Consumers in India
DOI:
https://doi.org/10.13052/spee1048-5236.4331Keywords:
Consumption pattern, electric grid, electricity consumption, K-means clustering, elbow methodAbstract
Electricity has become one of the essential needs in modern society. The demand and necessity for electricity have increased with population, trade, and industry, which has resulted in increased stress on the grid. As the development of an electricity storage system is costly, utilities are working on customer segmentation to classify the consumers according to their usage patterns to understand their demand and further develop resources accordingly. In this work, the K-Means clustering algorithm has been applied to a two-year monthly consumption data set (January 2019 to December 2020) of 100 residential consumers from Kutheda village Hamirpur (Himachal Pradesh, India) to visualize the diverse consumption behaviour. It resulted in four different clusters of consumers. It also showed that there is a group having a large number of consumers whose consumption is low and consumption pattern is very less flexible in different seasons. Another group of consumers with high consumption also shows high flexibility in consumption patterns, but their number is less. Also, the winter season shows the highest consumption of electricity and the monsoon season shows the lowest consumption of electricity in this particular region. This analysis will certainly help the electricity provider to make production planning for a different group of consumers in a specific season based on electricity consumption patterns.
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