Energy consumption clustering analysis in residential building

Abstract

Demand for electricity has been rapidly increasing in the residential sector as it is one of the necessities proportional to the increase in human population. However, most of the occupants less aware on how to use energy efficiently. The major factors that contribute to the energy consumption in residential buildings consumption are due to occupant’s activities and their lifestyle. Some of the occupants also not realize that they have used the electrical energy inefficiently because they utilize inefficient household appliances. As a result, inefficient energy has caused waste of energy. Waste of electrical energy will not only impact the costs of processing energy resources; it also impacts our environment. In order to save the electricity, we have to improve the energy efficiency by conserving or improving the efficiency. By improving the efficiency, the consumer should be able to know the household appliances that use high power consumption via their electrical appliances. The main aim of this project is to implement the clustering techniques to the measured data and to determine the most energy usage in home appliances using MATLAB simulation. In order to determine the number of cluster data for household appliances, the measured data will go through certain techniques that usually being used in clustering.