A stochastic optimization approach to cooperative building energy management via an energy hub

Building energy management is an active field of research since the potential in energy savings can be substantial. Nevertheless, the opportunities for large savings within individual buildings can be limited by the flexibility of the installed climate control devices and the individual construction characteristics. The energy hub concept allows one to manage a collection of buildings in a cooperative manner, by providing opportunities for load shifting between buildings and the sharing of expensive but energy efficient equipment housed in the hub, such as heat pumps, boilers, batteries. Typically, control design for the buildings and the energy hub are done separately, underutilizing the potential flexibility provided by the interconnected system. To address these issues, we propose a unified framework for controlling the operation of the energy hub and the buildings it connects to. By modeling all exogenous disturbance parameters as stochastic processes, and by using state-space representation of the building dynamics, we formulate a multistage stochastic optimization problem to minimize the total energy consumption of the system in a cooperative manner. We solve the resulting infinite dimensional optimization problem using a decision rule approximation, and we benchmark its performance on a numerical study, comparing it with established solution techniques.