학술논문

MESCOS—A Multienergy System Cosimulator for City District Energy Systems
Document Type
Periodical
Source
IEEE Transactions on Industrial Informatics IEEE Trans. Ind. Inf. Industrial Informatics, IEEE Transactions on. 10(4):2247-2256 Nov, 2014
Subject
Power, Energy and Industry Applications
Signal Processing and Analysis
Computing and Processing
Communication, Networking and Broadcast Technologies
Power system simulation
Energy management
Buildings
Simulation
Urban areas
Smart grids
Language
ISSN
1551-3203
1941-0050
Abstract
This work introduces a multidomain simulation platform that enables a holistic analysis of city district scale energy systems. The objective for the development of the simulation platform is to provide a tool that supports the design of control and energy management algorithms for those systems. The platform allows long-term simulations of a large number of buildings, including internal energy supply or energy conversion systems, in combination with external energy supply systems like the electrical grid. The simulation of those physical systems represents the environment for sophisticated control and energy management algorithms that can be tested on the platform. The concept of this work is to combine commercial-off-the-shelf software packages, here simulators and runtime infrastructure (RTI), to a high performance multidomain cosimulation platform. The high performance of the platform regarding computation time has been achieved by exploiting the parallel computing capabilities of modern simulation servers. Especially the computation time of large numbers of instances of Modelica-based models has been reduced significantly by the development of the parallel execution framework (PEF). The implementation of the PEF, including the interface to the individual models and to the RTI, is described in detail. The partitioning of the simulated system among different simulators does not influence the simulation results, as shown on the basis of a small-scale simulation scenario. The performance regarding the computation time is demonstrated on several example simulation scenarios showing the scalability of the platform.