Characterization of Aggregated Building Heating, Ventilation, and Air Conditioning Load as a Flexibility Service Using Gray‐Box Modeling

Integrating large amounts of volatile renewable power into the electricity grid requires ancillary services (ASs) from multiple providers including flexible demand. These should be comparable by uniform and efficiently evaluable performance criteria. The objective is to characterize the technical flexibility of aggregated building heating, ventilation, and air conditioning (HVAC) under different operating conditions. New bounds of flexible power and holding durations, accordingly pay-back power and recovery times, and ramping rates are derived, using a new gray-box model of stochastically actuated aggregations of thermostatically controlled loads (TCLs) that can serve as well for load control. New closed formulas of the expected switching temperatures are derived using survival processes and hazard functions. This ex-ante characterization enables fast decision tools for AS feasibility testing and planning by demand aggregators, as it neither relies on simulation or optimization, nor on the identification and clustering of unit-level parameters. The estimates are explored in a sensitivity study of urban-level heat pump heating with respect to six key input factors. A case study using dynamic regulation signals from Pennsylvania–New Jersey–Maryland (PJM) demonstrates the benefit, in terms of tracking precision, of the refined energy measures over pure energy or power capacity bounds