A Moving Horizon State Estimator in the Control of Thermostatically Controlled Loads for Demand Response

Abstract

The quality and effectiveness of the load following services provided by centralized control of thermostatically controlled loads depend highly on the communication requirements and the underlying cyber-infrastructure characteristics. Specifically, ensuring end-user comfort while providing realtime demand response services depends on the availability of the upstream information provided from the thermostatically controlled loads to the main controller regarding their operating statuses and internal temperatures. State estimation techniques can be used to infer the necessary information from the aggregate power consumption of these loads, replacing the need for an upstream communication platform carrying information from appliances to the main controller in real-time. In this paper, we introduce a moving-window mean squared error state estimator with constraints as an alternative to a Kalman filter approach, which assumes a linear model without constraints. The results show that some improvement is possible for scenarios when loads are expected to be toggled frequently.