Smoothing Net Load Demand Variations Using Residential Demand Management

Abstract

One of the major obstacles facing the large-scale integration of renewable energy sources to existing power networks is the large magnitude of fluctuations and uncertainties introduced to aggregated demand profiles. Such variations make the supply–demand matching a more challenging task, and increase the operational cost of the power system. In this paper, we provide an effective, yet simple, methodology for smoothing power variations using the demand response of a large number of residential appliances. We first present a demand aggregation model based on queueing theory that can accommodate both deferrable and thermostatically controlled loads. Second, controllable demands are scheduled using an online algorithm to smooth the net noncontrollable demand profile. The performance of our methodology is evaluated using realistic data.