Hybrid model predictive control of stratified thermal storages in buildings

• We present a heat/cold storage management control system for buildings.
• Heat/cold storage is provided by a stratified storage tank modelled with potential flows to/from every tank layer.
• Heat/cold consumption is predicted via short term load forecasting.
• Heat/cold generation is limited to specified operating modes.
• The resulting hybrid MPC problem can be approximated and solved efficiently.

In this paper a generic model predictive control (MPC) algorithm for the management of stratified thermal storage tanks in buildings is proposed that can be used independently of the building's heat/cold generation, consumption and consumption control. The main components of the considered storage management are the short term load forecasting (STLF) of the heat/cold consumer(s) using weather forecast, the MPC algorithm using a bilinear dynamic model of the stratified storage and operating modes of the heat/cold generator(s), modeled as static operating points. The MPC algorithm chooses between these operating modes to satisfy the predicted cold demand with minimal costs. By considering the generator(s) in terms of operating modes the bilinearity in the storage model is resolved which leads to a hybrid MPC problem. For computational efficiency this problem is approximated by an iterative algorithm that converges to a close to optimal solution. Simulation results suggest that the approach is well suited for the use in buildings with a limited number of heat/cold generators. Additionally, the approach is promising for practical use because of its independence from the heat/cold consumer's control and because it requires limited information and instrumentation on the plant, i.e. low costs for control equipment.