相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。User behaviour models to forecast electricity consumption of residential customers based on smart metering data
Florencia Lazzari et al.
ENERGY REPORTS (2022)
Deep learning for load forecasting with smart meter data: Online Adaptive Recurrent Neural Network
Mohammad Navid Fekri et al.
APPLIED ENERGY (2021)
A data mining-based framework for the identification of daily electricity usage patterns and anomaly detection in building electricity consumption data
Xue Liu et al.
ENERGY AND BUILDINGS (2021)
Cluster Analysis and Model Comparison Using Smart Meter Data
Muhammad Arslan Shaukat et al.
SENSORS (2021)
Evaluation of end user requirements for Smart Home applications and services based on a decision support system
Dede Georgia et al.
INTERNET OF THINGS (2021)
Household-Level Energy Forecasting in Smart Buildings Using a Novel Hybrid Deep Learning Model
Dabeeruddin Syed et al.
IEEE ACCESS (2021)
Deep Learning-Based Real-Time Building Occupancy Detection Using AMI Data
Cong Feng et al.
IEEE TRANSACTIONS ON SMART GRID (2020)
Big data analytics for future electricity grids
Mladen Kezunovic et al.
ELECTRIC POWER SYSTEMS RESEARCH (2020)
Smart Meter Data Based Load Forecasting and Demand Side Management in Distribution Networks With Embedded PV Systems
Zafar A. Khan et al.
IEEE ACCESS (2020)
A Machine Learning Framework to Infer Time-of-Use of Flexible Loads: Resident Behavior Learning for Demand Response
Milad Afzalan et al.
IEEE ACCESS (2020)
Incorporating Appliance Usage Patterns for Non-Intrusive Load Monitoring and Load Forecasting
Shirantha Welikala et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network
Weicong Kong et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
Detection of Non-Technical Losses Using Smart Meter Data and Supervised Learning
Madalina Mihaela Buzau et al.
IEEE TRANSACTIONS ON SMART GRID (2019)
Predicting residential energy consumption using CNN-LSTM neural networks
Tae-Young Kim et al.
ENERGY (2019)
Conventional models and artificial intelligence-based models for energy consumption forecasting: A review
Nan Wei et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2019)
Daily-seasonal operation in net-zero energy building powered by hybrid renewable energies and hydrogen storage systems
Hasan Mehrjerdi et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Deep Learning for Household Load Forecasting-A Novel Pooling Deep RNN
Heng Shi et al.
IEEE TRANSACTIONS ON SMART GRID (2018)
Non-intrusive load monitoring algorithm based on features of V-I trajectory
A. Longjun Wang et al.
ELECTRIC POWER SYSTEMS RESEARCH (2018)
Clustering-based analysis for residential district heating data
Panagiota Gianniou et al.
ENERGY CONVERSION AND MANAGEMENT (2018)
Association rule mining based quantitative analysis approach of household characteristics impacts on residential electricity consumption patterns
Fei Wang et al.
ENERGY CONVERSION AND MANAGEMENT (2018)
An Extensible Approach for Non-Intrusive Load Disaggregation With Smart Meter Data
Weicong Kong et al.
IEEE TRANSACTIONS ON SMART GRID (2018)
Economic and environmental scheduling of smart homes with microgrid: DER operation and electrical tasks
Di Zhang et al.
ENERGY CONVERSION AND MANAGEMENT (2016)
Feature Construction and Calibration for Clustering Daily Load Curves from Smart-Meter Data
Reem Al-Otaibi et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2016)
Analysis and Clustering of Residential Customers Energy Behavioral Demand Using Smart Meter Data
Stephen Haben et al.
IEEE TRANSACTIONS ON SMART GRID (2016)
Deep learning for estimating building energy consumption
Elena Mocanu et al.
SUSTAINABLE ENERGY GRIDS & NETWORKS (2016)
Robust optimization for load scheduling of a smart home with photovoltaic system
Chengshan Wang et al.
ENERGY CONVERSION AND MANAGEMENT (2015)
Optimal joint scheduling of electrical and thermal appliances in a smart home environment
Elham Shirazi et al.
ENERGY CONVERSION AND MANAGEMENT (2015)
Home Appliance Load Modeling From Aggregated Smart Meter Data
Zhenyu Guo et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2015)
Load Profiles of Selected Major Household Appliances and Their Demand Response Opportunities
Manisa Pipattanasomporn et al.
IEEE TRANSACTIONS ON SMART GRID (2014)
Household Energy Consumption Segmentation Using Hourly Data
Jungsuk Kwac et al.
IEEE TRANSACTIONS ON SMART GRID (2014)
Efficient energy consumption and operation management in a smart building with microgrid
Di Zhang et al.
ENERGY CONVERSION AND MANAGEMENT (2013)
Smart Meter Driven Segmentation: What Your Consumption Says About You
Adrian Albert et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2013)
分享论文
