Model-Based Estimation of Energy Savings in Load Control Events for Thermostatically Controlled Loads

Abstract

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.