Simulation of Smart-Grid Models using Quantization-Based Integration Methods

Abstract

Concepts such as smart grids, distributed genera-tion 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 con-trol 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 compo-nent is efficient and reliable simulation. However those energy models are typically large, stiff and ex-hibiting 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 model-ing of such systems; however, traditional state-of-the-art hybrid differential algebraic equation solvers cannot efficiently simulate these systems especially when their size grows to the order of hundreds, thou-sands, 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.