Abstract:With the development of the power internet of things (IOT), load forecasting will play an important role the power system. It can optimize the power generation planning and improve the economical operation of power IOT. In this paper, a new loading forecasting algorithm for power IOT is proposed using training data dimension expansion and ensemble learning. In the offline phase, the obtained meteorological data and time information is normalized to remove the unit effect at first. Then, the Hampel filter is us… Show more
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