Related references
Note: Only part of the references are listed.Data-driven framework towards realistic bottom-up energy benchmarking using an Artificial Neural Network
Matheus Soares Geraldi et al.
APPLIED ENERGY (2022)
Climate policy impacts on building energy use, emissions, and health: New York City local law 97
Parichehr Salimifard et al.
ENERGY (2022)
Managing the duck curve: Energy culture and participation in local energy management programs in the United States
Bess Krietemeyer et al.
ENERGY RESEARCH & SOCIAL SCIENCE (2021)
Building and grid system benefits of demand flexibility and energy efficiency
Roderick Jackson et al.
JOULE (2021)
US building energy efficiency and flexibility as an electric grid resource
Jared Langevin et al.
JOULE (2021)
Examining the feasibility of using open data to benchmark building energy usage in cities: A data science and policy perspective
Jonathan Roth et al.
ENERGY POLICY (2020)
Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking
Sicheng Zhan et al.
APPLIED ENERGY (2020)
EnergyStar plus plus : Towards more accurate and explanatory building energy benchmarking
Pandarasamy Arjunan et al.
APPLIED ENERGY (2020)
Harnessing smart meter data for a Multitiered Energy Management Performance Indicators (MEMPI) framework: A facility manager informed approach
Jonathan Roth et al.
APPLIED ENERGY (2020)
A Conceptual Framework to Describe Energy Efficiency and Demand Response Interactions
Andrew J. Satchwell et al.
ENERGIES (2020)
A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings
Benedetto Grillone et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2020)
Using marginal emission factors to improve estimates of emission benefits from appliance efficiency upgrades
Courtney N. Smith et al.
ENERGY EFFICIENCY (2019)
Apples or oranges? Identification of fundamental load shape profiles for benchmarking buildings using a large and diverse dataset
June Young Park et al.
APPLIED ENERGY (2019)
Grading buildings on energy performance using city benchmarking data
Sokratis Papadopoulos et al.
APPLIED ENERGY (2019)
Pattern recognition in building energy performance over time using energy benchmarking data
Sokratis Papadopoulos et al.
APPLIED ENERGY (2018)
Benchmarking building energy efficiency using quantile regression
Jonathan Roth et al.
ENERGY (2018)
Predictive modeling for US commercial building energy use: A comparison of existing statistical and machine learning algorithms using CBECS microdata
Hengfang Deng et al.
ENERGY AND BUILDINGS (2018)
Measures to improve energy demand flexibility in buildings for demand response (DR): A review
Yongbao Chen et al.
ENERGY AND BUILDINGS (2018)
Data-Driven, Multi-metric, and Time-Varying (DMT) Building Energy Benchmarking Using Smart Meter Data
Jonathan Roth et al.
ADVANCED COMPUTING STRATEGIES FOR ENGINEERING, PT I (2018)
Estimating energy savings from benchmarking policies in New York City
Ting Meng et al.
ENERGY (2017)
Machine learning approaches for estimating commercial building energy consumption
Caleb Robinson et al.
APPLIED ENERGY (2017)
On occupant-centric building performance metrics
William O'Brien et al.
BUILDING AND ENVIRONMENT (2017)
Analysis and Clustering of Residential Customers Energy Behavioral Demand Using Smart Meter Data
Stephen Haben et al.
IEEE TRANSACTIONS ON SMART GRID (2016)
Methods for benchmarking building energy consumption against its past or intended performance: An overview
Zhengwei Li et al.
APPLIED ENERGY (2014)
A new methodology for building energy performance benchmarking: An approach based on intelligent clustering algorithm
Xuefeng Gao et al.
ENERGY AND BUILDINGS (2014)
How much information disclosure of building energy performance is necessary?
David Hsu
ENERGY POLICY (2014)
Using smart meter data to estimate demand response potential, with application to solar energy integration
Mark E. H. Dyson et al.
ENERGY POLICY (2014)
Household Energy Consumption Segmentation Using Hourly Data
Jungsuk Kwac et al.
IEEE TRANSACTIONS ON SMART GRID (2014)
Smart Meter Driven Segmentation: What Your Consumption Says About You
Adrian Albert et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2013)
Overview and performance assessment of the clustering methods for electrical load pattern grouping
Gianfranco Chicco
ENERGY (2012)
Review of building energy-use performance benchmarking methodologies
William Chung
APPLIED ENERGY (2011)
Quantifying Changes in Building Electricity Use, With Application to Demand Response
Johanna L. Mathieu et al.
IEEE TRANSACTIONS ON SMART GRID (2011)
An energy benchmarking model based on artificial neural network method utilizing US Commercial Buildings Energy Consumption Survey (CBECS) database
Melek Yalcintas et al.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2007)
Benchmarking the energy efficiency of commercial buildings
W Chung et al.
APPLIED ENERGY (2006)
Benchmarking the energy efficiency and greenhouse gases emissions of school buildings in central Argentina
C Filippín
BUILDING AND ENVIRONMENT (2000)