Abstract
The goal of this study is to include a model of human decisions and preference in the control loop of a cyber-physical system (CPS). An electrical smart grid is selected as an example of such a CPS, and human decision and preference in utilization of thermostatically controlled loads (TCLs) are considered to be included in the control loop of TCLs. A two-stage planning and control framework is proposed. In the planning stage, a multi-objective dynamic program is developed for determining the expected optimal cumulative cost of operating a TCL over a planning horizon. The household demand is modeled with a series of Markov chains over the planning horizon and temperature comfort zone is represented by an interval as the preference. The day-ahead price of electricity is used for the price forecast, and the trade-off value between the cost of operating the TCL and the comfort obtained from its operation is user-specified. In the second stage, the expected optimal cumulative cost profile is used as the reference signal for the TCL's controller. The framework is simulated for an electric water heater unit to highlight its advantages.
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