Robustness Indicators for the Impact of Occupant Behavior Uncertainty on Building Energy Consumption

Due to the significant impact of occupant behavior uncertainty on building performance, robustness indicators are crucial for assessing and predicting building energy consumption. This study evaluates the robustness of building performance under occupant behavior uncertainty using various robustness indicators such as Maximax, Maximin, Hurwicz, and Laplace. Benchmark values (0.635) and coefficients of variation (0.544) from statistics were introduced to quantify the relative performance of each indicator and the relative dispersion of the data, allowing for fair comparisons across different magnitudes of indicators. “Variance”, “Starr’s Domain”, “Kurtosis”, and “Maximin” were identified as key indicators for assessing the robustness of energy consumption and load data. Based on these indicators and statistical principles, assuming the data follows a normal distribution, energy consumption and loads were predicted, showing that the optimized outcomes demonstrate good robustness.

Authors

Institutions

Publication Details

Journal
Energies
Published
2024-09-12
DOI
https://doi.org/10.3390/en17184571
Citations
3
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
0.80
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Robustness Indicators for the Impact of Occupant Behavior Uncertainty on Building Energy Consumption

Jian Yao, Rongyue Zheng, Jiahui Ying
3 citations
Energies
Building Energy and Comfort Optimization
0.80
article

Robustness Indicators for the Impact of Occupant Behavior Uncertainty on Building Energy Consumption

Jian Yao, Rongyue Zheng, Jiahui Ying
article en
3 citations

Abstract

Due to the significant impact of occupant behavior uncertainty on building performance, robustness indicators are crucial for assessing and predicting building energy consumption. This study evaluates the robustness of building performance under occupant behavior uncertainty using various robustness indicators such as Maximax, Maximin, Hurwicz, and Laplace. Benchmark values (0.635) and coefficients of variation (0.544) from statistics were introduced to quantify the relative performance of each indicator and the relative dispersion of the data, allowing for fair comparisons across different magnitudes of indicators. “Variance”, “Starr’s Domain”, “Kurtosis”, and “Maximin” were identified as key indicators for assessing the robustness of energy consumption and load data. Based on these indicators and statistical principles, assuming the data follows a normal distribution, energy consumption and loads were predicted, showing that the optimized outcomes demonstrate good robustness.

EnergiesVol. 17(18)
Ningbo University (CN)
Openalex Percentile: Top 29%
Building Energy and Comfort Optimization
0.80
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.