A peak-load reduction computing tool sensitive to commercial building environmental preferences

Demand Response (DR) as an option for electric utility peak load management has gained significant attention in the recent past as it helps to avoid stress conditions and possibly defer or avoid construction of new power generation, transmission and distribution infrastructures. DR in commercial buildings can play a major role in reducing peak load and mitigate network overloading conditions. Small and medium-sized commercial buildings have not historically played much role as a DR resource both due to lack of hardware and software tools and awareness. This paper presents a peak load reduction computing tool for commercial building DR applications. The proposed tool provides optimal control of building's cooling set points with the aim to reduce building's peak load, while maintaining occupant comfort measured by the Predicted Mean Vote (PMV) index. This is unlike other studies which use global cooling set point adjustment resulting in an uneven distribution of occupant satisfaction across the building. The approach is validated by experimentation conducted on a simulated medium-sized office building, which reflects an existing commercial building in Virginia, USA. Research findings indicate that the proposed methodology can effectively reduce the simulated building's peak load and energy consumption during a DR event, while maintaining occupant comfort requirements. The paper also addresses the issue of rebound peaks following a DR event, and offers a means to help avoid this situation.