In this paper, we investigate the residential load scheduling problem within a smart energy community, which is powered by a primary utility along with a small scale local power supplier. As a premise, unit prices set by these two suppliers are different and both are time-varying. Therefore, users are motivated to control their household appliances' operation time and calculate appropriate portions of power purchased from these two suppliers to achieve bill curtailments. The capacity constraint of local power supplier, arising from the renewable energy source and the limited storage capability, also should not be violated. We formulate a residential load scheduling problem to address this situation. Distributed scheme based on information exchange among users is proposed, without over revealing individual user's load profile. Then we propose a distributed algorithm to solve this scheduling problem. Simulation results show that the proposed approach can reduce energy cost of the community and cut down electricity payments of users, and the peak-to-average ratio in load demand is also decreased.
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