Intraday Optimization of Photovoltaic and Energy Storage-Driven HVAC Systems Based on an Equivalent RC Model

Abstract

Efficient management of building energy systems, particularly those integrating photovoltaic (PV) generation and energy storage systems (ESSs), is challenging due to the fluctuating nature of energy demand, supply, and electricity prices. Traditional optimization methods, such as day-ahead or intraday scheduling, often fail to fully meet the operational needs of energy systems, leading to wasted renewable energy, unmet load demand, and suboptimal cost-efficiency. This study addresses these gaps by proposing an integrated optimization strategy that combines day-ahead predictive scheduling with intraday adjustments, leveraging a second-order equivalent resistance–capacitance (RC) model to manage ESS charging and discharging. The strategy optimizes energy storage utilization and minimizes reliance on grid power by dynamically adjusting charging and discharging based on intraday conditions and price fluctuations. Tested on an office building, the proposed strategy reduced operating costs by 29.66% compared to day-ahead scheduling alone and by 15.48% compared to intraday optimization while eliminating unmet load demand and minimizing wasted PV generation. Grid reliance was also reduced by 33.33%. These findings underscore the critical role of coordinated charging and discharging strategies in improving energy management efficiency and reducing costs in PV–ESS integrated systems.