Optimization and operation strategy for demand response in Park Energy Systems with Public Buildings

Abstract

Abstract Public-building central air conditioning (CAC) systems provide substantial load flexibility because of their significant thermal inertia. However, existing optimization studies of park energy systems commonly represent them as conventional flexible loads, with insufficient consideration of zonal differences and occupant thermal comfort. This paper proposes a coordinated optimization method for CAC systems participating in park-level demand response. First, an aggregated demand response model is developed by considering building thermal inertia, indoor-temperature dynamics, load-ramping limits, post-response rebound, and terminal-temperature recovery. Second, a regional temperature control considering zonal demand (RTCD) strategy is proposed by evaluating occupant density and temperature demand in different building zones. The CAC system, residential demand response, multiple energy-storage systems, and electricity–gas–heating–cooling conversion equipment are then incorporated into a unified day-ahead scheduling model. The RTCD strategy is compared with the temperature-based demand response (Tem), Model Predictive Control (MPC), and central-air-conditioning non-demand-response (Non-DR) strategies. Relative to Non-DR, RTCD reduces operating costs by 2.46 % and 1.67 % on working and non-working days, respectively, and decreases peak grid-purchased power by approximately 5.7 % under both conditions. The renewable-energy utilization rate increases to 95.55 %, while the maximum reduction in grid-purchased power during the working-day peak period reaches 11.7 %. The average indoor-temperature deviation remains at 0.29 °C. These results demonstrate that RTCD improves operating economy, peak shaving, and multi-energy coordination while maintaining acceptable thermal comfort.