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...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2015-05-01
|
Series: | Buildings |
Subjects: | |
Online Access: | http://www.mdpi.com/2075-5309/5/2/650 |
id |
doaj-2571e66311d548e68b196051b9ed0b5f |
---|---|
record_format |
Article |
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 |
_version_ |
1725773543614971904 |