Evaluating demand flexibility of commercial building HVAC systems in South Korea

Demand flexibility is becoming increasingly vital to ensure stability and reliability in power systems by managing the fluctuating generation of renewable energy resources (RESs) and increasing electricity demand. This study proposes a novel method to evaluate the demand flexibility of Heating, Ventilation, and Air Conditioning (HVAC) systems in commercial buildings based on real-world data. To reflect the thermal dynamic response of HVAC systems, a data-driven model utilizing an artificial neural network (ANN) with online learning is developed, enhancing modeling accuracy using historical operation data. Considering the replicated ANN model, the optimal Demand Response (DR) schedules in response to Time-Of-Use (TOU) prices from the grid operator are determined to minimize building electricity costs. Consequently, the flexibility quantification of HVAC systems is evaluated by comparing t…