Abstract
An electrical energy monitoring system helps improve the security and reliability of a hospital operating system which can also indirectly enhance energy efficiency itself. However, a large hospital has a complex electrical system which leads to the big data issue from the installed monitoring system in this size-scaled hospital. Therefore, this paper proposes K-mean clustering technique, which is one of the effective data mining techniques, to analyze the big data from the electrical energy monitoring system in hospital. The case study is a large hospital with 200 in-patient beds in Thailand. Without loss of generality, electrical load profile is used for analyzing instead of using the electrical energy. Finally, the proposed data clustering technique is able to characterize electrical load profiles effectively for each hospital floor. This technique also identify the abnormality of these characterized electrical load profiles in various scenarios which hospital system operators can use them to consider the security, reliability, and energy efficiency of their operating systems.
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