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Optimization of Battery Energy Storage and Building HVAC Systems for Energy Cost Efficiency and Frequency Regulation

We study and develop a novel and energy cost-efficient strategy for frequency regulation through optimization of a battery energy storage system (BESS) and the largely untapped demand-responsive (DR) resources of commercial buildings. Specifically, we study and model a smart commercial building, with BESS, DR heating, ventilation, and air conditioning (HVAC) fans, equipped with modern variable frequency drive (VFD) controllers. We develop a two-stage strategy for frequency regulation, by exploiting the DR characteristics of the HVAC fans and BESS. In Stage 1, we minimize the day-ahead energy cost to optimally derive power reserve capacities of BESS and HVAC fans. In Stage 2, we develop an algorithm for frequency regulation using both BESS and HVAC fans, while satisfying the requirements for power reserve capacities computed in Stage 1. Simulation results show that our proposed algorithm enables the system to follow frequency regulation signals closely, while satisfying the requirements for optimal day-ahead power reserve capacities to achieve energy cost saving.