Priority-Based Energy Allocation in Buildings Through Distributed Model Predictive Control

Hongyi Li, Jun Xu, Qianchuan Zhao

Abstract: Many countries are facing energy shortages today and most of the global energy is consumed by HVAC systems in buildings. For the scenarios where the energy system is not sufficiently supplied to HVAC systems, a priority-based allocation scheme based on distributed model predictive control is proposed in this paper, which distributes the energy rationally based on priority order. According to the scenarios, two distributed allocation strategies, i.e., one-to-one priority strategy and multi-to-one priority strategy, are developed in this paper and validated by simulation in a building containing three zones and a building containing 36 rooms, respectively. Both priority-based strategies fully exploit the potential of predictive control solutions. The experiment shows that our scheme has good scalability and achieves the performance of the centralized strategy while making the calculation tractable. Note to Practitioners—The motivation of this paper is to develop a priority-based allocation strategy adapted to energy-limited systems. When energy is limited, the strategy can rationally allocate energy and satisfy the urgent need for energy supply in some specific zones. Two priority strategies are proposed for the case that a single subsystem corresponds to a particular priority and multiple subsystems correspond to the same priority, respectively. The developed strategies have been validated by co-simulation with MATLAB and EnergyPlus in a small-scale three-zone building and a large-scale 36-zone building to show their effectiveness.