Michael Wetter, Kyle Benne, Hubertus Tummescheit, Christian Winther
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引用次数: 0
Abstract
Spawn is DOE's next-generation tool chain for whole building energy control simulation. Spawn couples traditional imperative load-based envelope modelling with new equation-based modelling of HVAC and controls. Spawn uses EnergyPlus for the former and the Modelica Buildings Library for the latter. Because it leverages the Modelica Buildings Library, Spawn can evaluate advanced energy systems at the building and district scale, including new architectures and controls for heat pump systems with storage, and the coupling of such systems to electrical distribution networks. Spawn's Modelica integration likewise enables it to simulate realistic control sequences and therefore to bridge energy simulation and control implementation workflows. From EnergyPlus, Spawn inherits efficient envelope simulation and the ability to use existing envelope model authoring tools. This paper describes the architecture and implementation of Spawn, which automatically couples Modelica and EnergyPlus for run-time data exchange. This paper closes with examples that illustrate Spawn's modelling and simulation processes.
期刊介绍:
The Journal of Building Performance Simulation (JBPS) aims to make a substantial and lasting contribution to the international building community by supporting our authors and the high-quality, original research they submit. The journal also offers a forum for original review papers and researched case studies
We welcome building performance simulation contributions that explore the following topics related to buildings and communities:
-Theoretical aspects related to modelling and simulating the physical processes (thermal, air flow, moisture, lighting, acoustics).
-Theoretical aspects related to modelling and simulating conventional and innovative energy conversion, storage, distribution, and control systems.
-Theoretical aspects related to occupants, weather data, and other boundary conditions.
-Methods and algorithms for optimizing the performance of buildings and communities and the systems which service them, including interaction with the electrical grid.
-Uncertainty, sensitivity analysis, and calibration.
-Methods and algorithms for validating models and for verifying solution methods and tools.
-Development and validation of controls-oriented models that are appropriate for model predictive control and/or automated fault detection and diagnostics.
-Techniques for educating and training tool users.
-Software development techniques and interoperability issues with direct applicability to building performance simulation.
-Case studies involving the application of building performance simulation for any stage of the design, construction, commissioning, operation, or management of buildings and the systems which service them are welcomed if they include validation or aspects that make a novel contribution to the knowledge base.