Probabilistic Energy Management for Building Climate Comfort in Smart Thermal Grids with Seasonal Storage Systems

摘要

This paper presents an energy management framework for building climatecomfort systems that are interconnected in a grid via aquifer thermal energystorage (ATES) systems in the presence of two types of uncertainty, namelyprivate and common uncertainty sources. The ATES system is considered as aseasonal storage system that can be a heat source or sink, or a storage forthermal energy. While the private uncertainty source refers to uncertainthermal energy demand of individual buildings, the common uncertainty sourcedescribes the uncertain common resource pool (ATES) between neighbors. To thisend, we develop a large-scale stochastic hybrid dynamical model to predict thethermal energy imbalance in a network of interconnected building climatecomfort systems together with mutual interactions between the local ATESsystems. We formulate a finite-horizon mixed-integer quadratic optimizationproblem with multiple chance constraints at each sampling time, which is ingeneral a non-convex problem and hard to solve. We then provide acomputationally tractable framework based on an extension to the so-calledrobust randomized approach which offers a less conservative solution for aproblem with multiple chance constraints. A simulation study is provided tocompare three different configurations, namely: completely decoupled,centralized and move-blocking centralized solutions. In addition, we present anumerical study using a geohydrological simulation environment (MODFLOW) toillustrate the advantages of our proposed framework.