Building loads have a great potential to provide ancillary services because of its large power consumption. In order to quantify their flexibility, methods of modeling building loads as virtual battery (VB) have been proposed. The VB model provides an effective way to coordinate building loads and energy storage systems together when providing service to grid. However, after grid send a power signal to VB, the control strategy has not been fully studied to let building consumes this desired amount of power yet. This paper introduces a method to control commercial heating, ventilation, and air conditioning (HVAC) system. First, the thermal model of commercial building is introduced. We then used several data-driven models to approximate this thermal dynamic and the operation of different HVAC components. Base on these data-driven models, we developed a centralized control algorithm to utilize HVAC system consuming the desired amount of power. Finally, we modeled a realistic commercial building in EnergyPlus to test the performance of this proposed control algorithm
Revised: August 13, 2020 |
Published: August 5, 2019
Citation
Wang J., N. Lu, S. Huang, and D. Wu. 2019.A Data-driven Control Method for Operating the Commercial HVAC Load as a Virtual Battery. In IEEE Power & Energy Society General Meeting (PESGM 2019), August 4-8, 2019, Atlanta, GA, 1-5. Piscataway, New Jersey:IEEE.PNNL-SA-139487.doi:10.1109/PESGM40551.2019.8973486