Model-based estimation of energy savings in load control events for thermostatically controlled loads

Load control (LC) of populations of air conditioners (ACs) is considered suitable to shift energy from on- to off-peak times, and track the intermittent power output of renewable generation. From a technical and economical point of view, it is paramount to quantify the amount of energy that can be saved by implementing these LC events. This paper proposes a new causal methodology to estimate such energy savings using a Kalman filter that includes a parametric second-order model of the aggregate demand of a population of ACs. The proposed methodology relies only on readings of aggregate electrical power at the feeder level and does not require historical load data, or a control group, and hence, it can be used where other methods reported in the literature are inapplicable. The proposed estimator is evaluated on a numerical case study that embeds simulated ACs in real power and temperature data from a 70-house residential precinct.