EnergyStar++: Towards more accurate and explanatory building energy benchmarking (2019-10-30T00:00:00.000000Z)

TL;DR

A methodology that enhances the existing Energy Star calculation method by increasing accuracy and providing additional model output processing to help explain why a building is achieving a particular score is proposed.

Authors

P. Arjunan

1 papers

K. Poolla

1 papers

Clayton Miller

1 papers

TL;DR

Authors

References64 items

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Examining the feasibility of using open data to benchmark building energy usage in cities: A data science and policy perspective

The impact of mandatory energy audits on building energy use

Impact of energy benchmarking and disclosure policy on office buildings

A comparative analysis of data-driven methods in building energy benchmarking

Comparing energy and comfort metrics for building benchmarking

Development of an energy benchmarking database based on cost-effective energy performance indicators: Case study on public buildings in South Korea

A data envelopment analysis (DEA) model for building energy benchmarking

A Grounded Interaction Protocol for Explainable Artificial Intelligence

Data-Driven

DUE-A: Data-driven Urban Energy Analytics for understanding relationships between building energy use and urban systems

A study of city-level building energy efficiency benchmarking system for China

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery

Data-Driven, Multi-metric, and Time-Varying (DMT) Building Energy Benchmarking Using Smart Meter Data

Benchmarking building energy efficiency using quantile regression

DUE-B: Data-driven urban energy benchmarking of buildings using recursive partitioning and stochastic frontier analysis

Benchmark analysis of electricity consumption for complex campus buildings in China

Consistent Individualized Feature Attribution for Tree Ensembles

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

A review of data-driven approaches for prediction and classification of building energy consumption

Building energy retrofit index for policy making and decision support at regional and national scales

A Unified Approach to Interpreting Model Predictions

Objective Building Energy Performance Benchmarking Using Data Envelopment Analysis and Monte Carlo Sampling

Evaluation of U.S. Building Energy Benchmarking and Transparency Programs: Attributes, Impacts, and Best Practices

Development of a new energy benchmark for improving the operational rating system of office buildings using various data-mining techniques

XGBoost: A Scalable Tree Boosting System

“Why Should I Trust You?”: Explaining the Predictions of Any Classifier

Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission

Does Information Provision Shrink the Energy Efficiency Gap? A Cross-City Comparison of Commercial Building Benchmarking and Disclosure Laws

Methods for benchmarking building energy consumption against its past or intended performance: An overview

From the Good

A classification of building energy performance indices

Towards nearly zero-energy buildings: The state-of-art of national regulations in Europe

The use of normative energy calculation beyond building performance rating

A study on the energy performance of hotel buildings in Taiwan

Review of building energy-use performance benchmarking methodologies

Benchmarking energy use and greenhouse gas emissions in Singapore's hotel industry

Benchmarking the performance of building energy management using data envelopment analysis

Applying support vector machine to predict hourly cooling load in the building

Detecting gene–gene interactions that underlie human diseases

A review of benchmarking, rating and labelling concepts within the framework of building energy certification schemes

引言 (Introduction)

Building energy efficiency labeling programme in Singapore

The potential for energy efficiency gains in the Canadian commercial building sector: A stochastic frontier study

An energy benchmarking model based on artificial neural network method utilizing US Commercial Buildings Energy Consumption Survey (CBECS) database

A holistic utility bill analysis method for baselining whole commercial building energy consumption in Singapore

On the use of decision tree induction for discovery of interactions in a photolithographic process

The Elements of Statistical Learning

Greedy function approximation: A gradient boosting machine.

EnergyPlus: creating a new-generation building energy simulation program

others

A Value for n-person Games

Grading buildings on energy performance using city benchmarking data

Institute for Market Transformation

Points of Significance: Classification and regression trees

Does Information Provision Shrink the Energy E ffi ciency Gap ?

ENERGY STAR Building Benchmarking Scores: Good Idea, Bad Science

New York City's Energy and Water Use

China - Green Energy for Low-Carbon City Project in Shanghai Project

NABERS: Lessons from 12 Years of Performance Based Ratings in Australia

EPA Portfolio Manager Data Trends

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Random Forests

Multiple Regression: Testing and Interpreting Interactions.

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