Group for Research in Decision Analysis


Characterizing and controlling the statistics of aggregated demand-based reserve resources

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There are few systematic methodologies capable of predicting and managing the potential of large populations of appliances working as aggregated reserve resources. For demand-side based reserves to have economic and technical value, it is essential that demand-side exibility aggregators and system operators be able to do so unequivocally. This paper introduces an analytical approach to characterize and control statistical bounds on the potential aggregated response of populations of thermostatically-controlled loads (TCLs). First, the uncertainty associated with the instantaneous power consumption of a TCL in a population is described by a set of random variables and their statistics. TCL statistics are then employed to characterize the exploitable exibility from a large population of similar devices. From this, a control strategy and parameters are introduced to manage the aggregated response of the TCL population in response to a control signal as well as its post-response reconnection to grid. Monte Carlo simulations are employed to validate the proposed approach for the special case of a population of electric water heaters used to provide reserve capacity.

, 19 pages