Thermal management of a school room via quadratic multi-objective optimization

This paper presents a multi-objective optimization framework to reduce energy costs while maintaining thermal comfort in a school classroom. The room is thermally controlled with an HVAC system. A first-order resistance-capacitance (RC) model is used to characterize the thermal behavior of the room. The multi-objective problem is solved using a scalarization method, which leads to a constrained quadratic programming (QP) problem. Simulations are carried out over a four-day period, considering dynamic electricity pricing and thermal inertia effects. The results demonstrate how increasing the thermal parameters of the room affects the thermal response and cost minimization. The study identifies optimal HVAC operation strategies that use the building's thermal storage. The proposed framework can be used for real-time control and multi-agent coordination in large-scale building networks.