An MPC-based optimal control strategy of active thermal storage in commercial buildings during fast demand response events in smart grids

Abstract

Demand response (DR) is a set of demand-side activities to reduce or shift electricity use to improve the electric grid efficiency and reliability. Shutting down part of operating chillers directly in central air-conditioning systems of buildings to meet the urgent demand reduction needs of power grids has received increasing attention recently. A model predictive control strategy is developed for optimizing the operation of a central air-conditioning system integrated with an active cold storage during such fast demand response events. The primary objective of the proposed control strategy is to maximize the power reduction with a profile pattern preferred by power grids as well as to maintain the indoor air temperature within an acceptable level during fast DR period. The MPC controller determines the control outputs of chiller power demand and active storage discharge rate based on the discrete-time state space building thermal response model. Test results show that expected profile pattern (i.e., maximum and stable) of power reduction was achieved by the proposed MPC strategy during fast DR events. Meanwhile, the indoor air temperature was maintained within the acceptable range.