Model predictive control of commercial buildings in demand response programs in the presence of thermal storage

The flexibility of buildings in Building-to-Grid (B2G) systems has led to the participation of buildings as one of the largest energy consumers in energy management and moving towards clean, reliable and sustainable energy systems. The development of appropriate frameworks for B2G requires appropriate control strategies for the active participation of buildings in these services. These frameworks require the demand side management (DSM) and participation in demand response (DR) programs that can increase the flexibility of the building, reduce operating costs, and reduce the need for capacity development in energy networks. A significant part of the energy cost of commercial buildings is related to the demand charge. As a result, commercial buildings to reduce this cost should reduce the peak demand or the length of the period of this peak demand. To do this, commercial buildings require operational flexibility to change their operating schedule. In this paper, a multi-level demand charge, along with a real time pricing (RTP) program and incentivize signals for the participation of thermal energy storage (TES) integrated commercial buildings in DR programs, has been used to examine building performance in the presence of these complex pricing schemes. In this regard, a model predictive control (MPC) strategy has been developed to optimize the performance of the building and to benefit from the operational flexibility of the TES. The results showed that the existence TES in a commercial building leads to more flexibility for partaking in DR programs, and so a reduction in energy costs and demand charge besides maintaining occupants comfort level. (C) 2019 Published by Elsevier Ltd.