A flexible optimization framework for district systems based on topological graph and hybrid models. (November 2021) - Manganini, Giorgio; Riverso, Stefano; Kouramas, Kostantinos
Abstract: This paper proposes a scalable and widely replicable framework for the energy management of district systems. The framework is built on a graph-based energy characterization of the system, whose supply and demand dynamics are numerically represented by hybrid mathematical models involving the available control inputs and measurable outputs. Following the graph topology connecting supply and demand nodes, a suitable optimization problem is formulated to take into consideration the actual availability of the involved control input and measurements, resulting in a computationally tractable mixed-integer linear control problem which can be implemented in a receding-horizon fashion. As an illustrative case, the framework is applied to a real-case district heating system, and the validity of the approach is showed through model-in-the-loop and system-in-the-loop numerical results. Highlights: Wide replicability and applicability of District Energy Management is a challenge. Data-driven hybrid systems offer flexibility to capture complex system dynamics. Replicable optimization framework based on district topological graph. Topological graph and hybrid models captures the district energy characterization. Performances and applicability proved in real and simulated district system.