Abstract

The main climatic factors including temperature and relative humidity, and various disturbances including faults have conspicuous influence on either the trend or short-term variations of system load. It is very useful to acquire better understanding of the influence. This paper applies data-mining techniques to the CLP (China Light and Power) Power database in order to analyze (a) the effect of temperature and relative humidity on the peak load, (b) the cluster of load profiles in various buses in response to disturbances.

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