面向空气净化型光伏光热建筑一体化系统与虚拟储能集成的双层滚动优化控制方法

Abstract In the post-pandemic era, improving energy efficiency while ensuring indoor air quality has become a key challenge in building system design. Air-purifying building-integrated photovoltaic/thermal (BIPVT) systems efficiently integrate space heating, power generation, and air purification functions, while virtual energy storage systems (VESS) enable flexible load shifting without relying on physical storage devices. The integration of these two technologies holds great potential for application in smart and healthy buildings. However, existing operation strategies often overlook intraday dynamic optimization targeting indoor air quality. To address the above problems, a novel method for intraday optimization control of air purification BIPVT system, considering building energy storage, is proposed to reduce electricity costs and enhance indoor environmental quality. Case studies show that, compared to day-ahead optimization, proposed strategy reduces thermal discomfort violations by 78.9 %. The strategy improves renewable energy consumption and shifts electricity load during peak electricity prices. Compared to control strategies that do not consider BIPVT or VESS, operation costs are reduced by 47.8 % and 10.3 %, respectively. As the prediction horizon is extended from 1 h to 2.5 h, operating costs decrease by 3.33 %, but further increasing prediction horizon yields minimal additional benefits. The strategy performs well under various meteorological conditions, demonstrating its adaptability in different climate regions.