<p>The heating, ventilation, and air conditioning (HVAC) system is a promising flexibility resource for building energy management and grid stability. Quantitatively assessing HVAC demand response (DR) potential is crucial for integrating buildings into DR programs. However, utilities and load aggregators typically only have total building energy data, making HVAC energy disaggregation challenging. This study proposes an unsupervised and hybrid time-frequency domain decomposition method (MSTL-VMD) to disaggregate HVAC energy from total consumption and an improved equivalent thermal parameter model to quantify DR potential while considering outdoor weather, indoor environment, and occupant comfort. The effectiveness of the proposed method is verified based on historical data from 10 office buildings over 3 years. The results indicate that the HVAC energy can be accurately disaggregated using the MSTL-VMD method with NRMSE of 2.4%–12.6%. The proposed equivalent thermal parameter model can realize HVAC energy regression with an <i>R</i>² value exceeding 0.8 for 80% of cases. A 1 °C indoor temperature increase results in energy savings of 7.3%–18.4% over the summer. The proposed method provides utilities and load aggregators with an effective and practical technique to quantify HVAC DR potential, enabling the development of optimal energy management strategies to enhance energy system resilience and efficiency.</p>