A hierarchical scheduling and control strategy for thermal energy storage systems

Abstract

Energy storage in buildings is an important component of peak shifting and load leveling strategies devised to improve the operation of the electric grid. Maximizing the load-leveling benefits afforded by both active and passive thermal energy storage (TES) requires coordinating the charge/discharge events with external factors, such as weather, occupancy, and time-of-use pricing. The development of such controllers (typically following the model predictive control (MPC) paradigm) is challenging owing to the dimensions and multiple time scale nature of the problem. In this work, we propose a hierarchical control strategy, comprising a dynamic scheduling problem for managing active TES in the slow time scale, and a control scheme with a shorter horizon for managing passive TES in the fast time scale. The approach is demonstrated through an application to a TES system with phase change material (PCM), which presents unique modeling challenges. The proposed formulation and solution strategy allow for obtaining solutions in real time. Moreover, it is shown that the proposed approach leads to significant cost savings, outperforming (reasonable) operating heuristics even under uncertainty in forecasting building loads.