Simulating Performance Risk for Lighting Retrofit Decisions

In building retrofit projects, dynamic simulations are performed to simulate building performance. Uncertainty may negatively affect model calibration and predicted lighting energy savings, which increases the chance of default on performance-based contracts. Therefore, the aim of this paper is to d...

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Main Authors: Jia Hu, Eric Shen, Yun Gu
Format: Article
Language:English
Published: MDPI AG 2015-05-01
Series:Buildings
Subjects:
Online Access:http://www.mdpi.com/2075-5309/5/2/650
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spelling doaj-2571e66311d548e68b196051b9ed0b5f2020-11-24T22:20:51ZengMDPI AGBuildings2075-53092015-05-015265066710.3390/buildings5020650buildings5020650Simulating Performance Risk for Lighting Retrofit DecisionsJia Hu0Eric Shen1Yun Gu2Philips Research North America, Briarcliff Manor, NY 10510, USAPhilips Research North America, Briarcliff Manor, NY 10510, USAPhilips Research North America, Briarcliff Manor, NY 10510, USAIn building retrofit projects, dynamic simulations are performed to simulate building performance. Uncertainty may negatively affect model calibration and predicted lighting energy savings, which increases the chance of default on performance-based contracts. Therefore, the aim of this paper is to develop a simulation-based method that can analyze lighting performance risk in lighting retrofit decisions. The model uses a surrogate model, which is constructed by adaptively selecting sample points and generating approximation surfaces with fast computing time. The surrogate model is a replacement of the computation intensive process. A statistical method is developed to generate extreme weather profile based on the 20-year historical weather data. A stochastic occupancy model was created using actual occupancy data to generate realistic occupancy patterns. Energy usage of lighting, and heating, ventilation, and air conditioning (HVAC) is simulated using EnergyPlus. The method can evaluate the influence of different risk factors (e.g., variation of luminaire input wattage, varying weather conditions) on lighting and HVAC energy consumption and lighting electricity demand. Probability distributions are generated to quantify the risk values. A case study was conducted to demonstrate and validate the methods. The surrogate model is a good solution for quantifying the risk factors and probability distribution of the building performance.http://www.mdpi.com/2075-5309/5/2/650risklightingretrofitsimulationEnergyPlussurrogate model
collection DOAJ
language English
format Article
sources DOAJ
author Jia Hu
Eric Shen
Yun Gu
spellingShingle Jia Hu
Eric Shen
Yun Gu
Simulating Performance Risk for Lighting Retrofit Decisions
Buildings
risk
lighting
retrofit
simulation
EnergyPlus
surrogate model
author_facet Jia Hu
Eric Shen
Yun Gu
author_sort Jia Hu
title Simulating Performance Risk for Lighting Retrofit Decisions
title_short Simulating Performance Risk for Lighting Retrofit Decisions
title_full Simulating Performance Risk for Lighting Retrofit Decisions
title_fullStr Simulating Performance Risk for Lighting Retrofit Decisions
title_full_unstemmed Simulating Performance Risk for Lighting Retrofit Decisions
title_sort simulating performance risk for lighting retrofit decisions
publisher MDPI AG
series Buildings
issn 2075-5309
publishDate 2015-05-01
description In building retrofit projects, dynamic simulations are performed to simulate building performance. Uncertainty may negatively affect model calibration and predicted lighting energy savings, which increases the chance of default on performance-based contracts. Therefore, the aim of this paper is to develop a simulation-based method that can analyze lighting performance risk in lighting retrofit decisions. The model uses a surrogate model, which is constructed by adaptively selecting sample points and generating approximation surfaces with fast computing time. The surrogate model is a replacement of the computation intensive process. A statistical method is developed to generate extreme weather profile based on the 20-year historical weather data. A stochastic occupancy model was created using actual occupancy data to generate realistic occupancy patterns. Energy usage of lighting, and heating, ventilation, and air conditioning (HVAC) is simulated using EnergyPlus. The method can evaluate the influence of different risk factors (e.g., variation of luminaire input wattage, varying weather conditions) on lighting and HVAC energy consumption and lighting electricity demand. Probability distributions are generated to quantify the risk values. A case study was conducted to demonstrate and validate the methods. The surrogate model is a good solution for quantifying the risk factors and probability distribution of the building performance.
topic risk
lighting
retrofit
simulation
EnergyPlus
surrogate model
url http://www.mdpi.com/2075-5309/5/2/650
work_keys_str_mv AT jiahu simulatingperformanceriskforlightingretrofitdecisions
AT ericshen simulatingperformanceriskforlightingretrofitdecisions
AT yungu simulatingperformanceriskforlightingretrofitdecisions
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