Abstract
This paper presents a closed-loop model in which commercial building aggregators (CBAs) minimize their operating costs in a wholesale electricity market, considering wind power uncertainties that are modeled as contingencies using a set of forecast error scenarios. Specifically, the CBAs determine the optimal energy consumption and reserve deployment of variable speed heat pumps (VSHPs) and plug-in electric vehicles (PEVs) in response to locational marginal prices (LMPs). A two-stage stochastic optimization problem is formulated to model the price-based demand response (DR) of the CBAs. Simulated case studies are performed to estimate variation in the operational costs of the CBAs under various conditions, as determined by the room temperature control methods and the building energy storage resource penetrations.
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