Conference Editor

Jianshun Zhang; Edward Bogucz; Cliff Davidson; Elizabeth Krietmeyer

Keywords:

building performance simulation, EnergyPlus, optimization, model reduction

Location

Syracuse, NY

Event Website

http://ibpc2018.org/

Start Date

25-9-2018 1:30 PM

End Date

25-9-2018 3:00 PM

Description

Optimization in building performance simulation (BPS) has become increasingly important due to the growing need for high-performance building design and operation. Numerous research efforts have been dedicated to decreasing optimization runtime by introducing improved optimization algorithms and advanced sampling techniques. This paper presents a novel model order reduction (MOR) algorithm tailored for speeding up building energy simulation. The algorithm identifies archetype zones simplifying the needless repetition of thermal zones. For an entire optimization process, this MOR method can be repeated recursively to reproduce reduced models. The proposed method can be used to speed up large-scale simulations including optimization, uncertainty analysis and model predictive controls. Preliminary results with parametric simulations show a runtime reduction of about 76% reduction for 15 simulations while still maintaining the predicted total annual energy consumption within a 10% margin. Further research will be conducted to compare the optimization results when applying the proposed MOR algorithm and determine if the reduced model produces the same optimal design. The proposed method may significantly improve the optimization runtime with a minor effect on optimization accuracy, thus increasing the overall usability of BPS optimizations.

Comments

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DOI

https://doi.org/10.14305/ibpc.2018.ms-6.01

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

COinS
 
Sep 25th, 1:30 PM Sep 25th, 3:00 PM

Achieving Faster Building Energy Model Optimization through Selective Zone Elimination

Syracuse, NY

Optimization in building performance simulation (BPS) has become increasingly important due to the growing need for high-performance building design and operation. Numerous research efforts have been dedicated to decreasing optimization runtime by introducing improved optimization algorithms and advanced sampling techniques. This paper presents a novel model order reduction (MOR) algorithm tailored for speeding up building energy simulation. The algorithm identifies archetype zones simplifying the needless repetition of thermal zones. For an entire optimization process, this MOR method can be repeated recursively to reproduce reduced models. The proposed method can be used to speed up large-scale simulations including optimization, uncertainty analysis and model predictive controls. Preliminary results with parametric simulations show a runtime reduction of about 76% reduction for 15 simulations while still maintaining the predicted total annual energy consumption within a 10% margin. Further research will be conducted to compare the optimization results when applying the proposed MOR algorithm and determine if the reduced model produces the same optimal design. The proposed method may significantly improve the optimization runtime with a minor effect on optimization accuracy, thus increasing the overall usability of BPS optimizations.

https://surface.syr.edu/ibpc/2018/MS6/1

 

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