Conference article

Concepts such as smart grids; distributed generation and micro–generation of energy; market–driven as well as demand–side energy management; are becoming increasingly important and relevant as emerging trends in the design; management and control of energy systems. Appropriate modeling and design; efficient management and control strategies of such systems are currently being studied. In this line of research a very important enabling component is efficient and reliable simulation. However those energy models are typically large; stiff and exhibiting heavy discontinuities; and at the same time consist of interconnected multi–domain subsystems encompassing electrical; thermal; and thermo-fluid models. Object-Oriented (O–O) languages such as Modelica are obviously well-suited for the modeling of such systems; however; traditional state-ofthe-art hybrid differential algebraic equation solvers cannot efficiently simulate these systems especially when their size grows to the order of hundreds; thousands; or even more interconnected units.

The goal of this paper is to show; through a couple of exemplary case studies; that Quantized State System (QSS) integration methods are ideally suited to solve models of such systems; as they scale up better than traditional methods with the system size; and provide time savings of several orders of magnitude; while achieving comparable numerical precision.

Quantization–Based Integration Methods; QSS; DASSL; Smart–Grids; EnergyMarket; Modelica