A tool for generating reduced-order models from building energy simulation input files to enable optimal design and control analysis.
Number: pap. 3614
Author(s) : KIM D., BAE Y., BRAUN J. E., et al.
Summary
Representing building envelope systems with linear time invariant (LTI) state-space forms is advantageous for development and implementation of advanced control methodologies, such as model predictive control, and for enabling design optimization when computational efficiency is important. For example, system properties such as time constants and frequency response of building envelopes can be easily investigated with the help of control toolkits such as MATLAB/Simulink. Furthermore, an LTI building representation enables the development of a reduced-order model using standard model reduction techniques. However, in order to make the LTI representation approach useful for industry, an interfacing tool that automatically extracts building system information from input files for popular building energy simulation (BES) tools and constructs a physical thermal network from the data is needed. This paper presents a conceptual strategy for interpreting an object (class) of a building energy simulation software and a methodology to develop a high fidelity LTI thermal network model. A case study applying this approach is provided which utilizes a model-order reduction method that converts a BES building envelope model for a building into a reduced-order LTI model (ROM). Comparisons of predicted building load profiles and computation times between the BES model and ROM are also provided.
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Details
- Original title: A tool for generating reduced-order models from building energy simulation input files to enable optimal design and control analysis.
- Record ID : 30025050
- Languages: English
- Subject: Environment
- Source: 2018 Purdue Conferences. 5th International High Performance Buildings Conference at Purdue.
- Publication date: 2018/07/09
Links
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Indexing
- Themes: Green buildings
- Keywords: Software; Building; Design; Simulation; Prediction; Modelling; Case study; Control (generic); Thermal load
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