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A residential load scheduling approach based on load behavior analysis

Residential load scheduling is of great significance for the building energy saving. But it is difficult for current methods to discover and consider the relationship between the various comfort requirements and uncertain load demand of customers. In this paper, a new method for the residential load scheduling based on load behavior analysis is proposed to reduce the electrical cost while considering the human behavior. Firstly, the multi-dimensional feature-based load profile identification is applied to identify the operating status of the appliances from the historical load data. Then, the environment record and the state models of appliances are used to estimate the comfort preferences and load demand of customers. The personalized optimal strategy of the household appliance operation is given to minimize the daily cost, according to the dynamic electrical price and the real time weather condition. Three simulations are designed to demonstrate how to identify the operation status of appliances, how to obtain the load behavior, and the performance of proposed method on cost saving.