Optimal HVAC Regulation Capacity for Congestion Management in Local Flexibility Markets

With the increasing proportion of renewable energy and the rise of seasonal peak loads, congestion in distribution networks has become a growing concern. The heating, ventilation, and air conditioning (HVAC) system, as a flexible resource on the demand side, has considerable regulation capabilities, requiring further study. Therefore, this paper proposes a local flexibility markets designed specifically for HVAC systems to enhance congestion management. Firstly, a physical model for HVAC is constructed, and indoor temperature variations are simulated using an equivalent thermal parameter model. Subsequently, the PMV comfort index is employed to determine the upper and lower limits of indoor temperature, allowing for the quantification of the adjustable power of HVAC systems and the introduction of a virtual storage model. Based on this, a system optimization model is formulated with user comfort temperature and maximum adjustable capacity as the objective function. Finally, an optimization model for the distribution system operator's congestion management is designed to get flexibility services. Through the aforementioned optimization model, requests and bids for flexibility services are conducted, utilizing an improved Alternating Direction Method of Multipliers (ADMM) to clear the local flexibility markets, ensuring data privacy and market scalability. The proposed method is analyzed using a real dataset within the IEEE 33-bus system.