Cristian Perfumo, Julio H. Braslavsky, and John K. Ward
Smart grids, demand side management, load control, thermostati-cally controlled loads, intermittent renewable energy, load population dynamics
Populations of distributed thermostatically controlled loads (TCLs) can be remotely controlled as a demand-side approach to maintain the generation–consumption balance in the electricity grid. Adjusting load to generation can result in reduced emissions and lower network operating costs than adjusting generation to load (its traditional counterpart). TCLs have been the focus of a number of recent studies proposing model-based feedback load control (LC) strategies, with promising results. However, commonly made assumptions limit the practicality of such strategies in LC scenarios involving small populations of TCLs, or where the requirement of power demand readings of the controlled devices for feedback may be prohibitively expensive. This paper exploits a parametric second-order TCL model previously developed by the authors to design a proportional-integral-derivative (PID) controller readily implementable in such LC scenarios. The proposed PID controller, based on the broadcast of setpoint offset changes, only requires feedback of aggregate demand readings at the distribution feeder level. LC performance is evaluated on a numerical case study that embeds simulated TCLs in real power and temperature data from a 70-house residential precinct. The case study highlights the potential of the proposed model-based approach in practical LC scenarios.
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