Results 81 to 90 of about 57,754 (187)

Towards Trustworthy Energy Disaggregation: A Review of Challenges, Methods, and Perspectives for Non-Intrusive Load Monitoring. [PDF]

Sensors (Basel), 2022
Kaselimi M, Protopapadakis E, Voulodimos A, Doulamis N, Doulamis A.   +4 more
europepmc   +1 more source

Forecasting monthly us consumer price indexes through a disaggregated I(2) analysis [PDF]

, 2002
In this paper we carry a disaggregated study of the monthly US Consumer Price Index (CPI). We consider a breakdown of US CPI in four subindexes, corresponding to four groups of markets: energy, food, rest of commodities and rest of services. This is seen
Espasa, Antoni, Poncela, Pilar, Senra, Eva   +2 more
core   +1 more source

A VMD-deep learning approach for individual load monitoring and forecasting for residential buildings energy management

e-Prime: Advances in Electrical Engineering, Electronics and Energy
This paper presents a comprehensive solution for Multi-Individual load disaggregation and Multi-individual load Forecasting in residential energy systems. The approach combines Variable Mode Decomposition (VMD) and deep learning algorithms, incorporating
Ismael Jrhilifa, Hamid Ouadi, Abdelilah Jilbab, Nada Mounir, Abdellah Ouaguid   +4 more
doaj   +1 more source

A Fusion Load Disaggregation Method Based on Clustering Algorithm and Support Vector Regression Optimization for Low Sampling Data

Future Internet, 2019
In order to achieve more efficient energy consumption, it is crucial that accurate detailed information is given on how power is consumed. Electricity details benefit both market utilities and also power consumers. Non-intrusive load monitoring (NILM), a
Quanbo Yuan, Huijuan Wang, Botao Wu, Yaodong Song, Hejia Wang   +4 more
doaj   +1 more source

Structural basis for substrate gripping and translocation by the ClpB AAA+ disaggregase. [PDF]

, 2019
Bacterial ClpB and yeast Hsp104 are homologous Hsp100 protein disaggregases that serve critical functions in proteostasis by solubilizing protein aggregates.
Bart, Stephen M, Castellano, Laura M, DiMaio, Frank, Gates, Stephanie N, Lin, JiaBei, Rizo, Alexandrea N, Shorter, James, Southworth, Daniel R, Tse, Eric   +8 more
core  

Load Energy Decomposition Algorithm Based on Improved Bidirectional Transformer Combined With Time-Sensing Self-Attention

IEEE Access
Non-Intrusive Load Monitoring (NILM) represents a technique for energy monitoring that is adept at discerning the quantity, type, and operational status of appliances through the analysis of aggregate power data within a specified area.
Yang Xuan, Chengxin Pang, Haimeng Yu, Xinhua Zeng, Yongbo Chen   +4 more
doaj   +1 more source

Occupancy detection for enhanced energy disaggregation

Procedia Computer Science
Non-Intrusive Load Monitoring (NILM) attempts to break down the aggregated electrical consumption signal into the power consumption of each individual appliance, which can provide helpful understanding on energy consumption patterns and helps reduce overall energy usage and costs. This paper proposes an occupancy-aided energy disaggregation approach to
Balti, Nidhal, Vrigneau, Baptiste, Scalart, Pascal   +2 more
openaire   +2 more sources

China's Changing Energy Intensity Trend: A Decomposition Analysis [PDF]

China experienced a dramatic decline in energy intensity from the onset of economic reform in the late 1970s until 2000, but since then rate of decline slowed and energy intensity actually increased in 2003.
Chunbo Ma, David I. Stern
core  

A novel hybrid architecture for agriculture and land use in an integrated modeling framework : MATISSE (Methods and Tools for Integrated Sustainability Assesment) [PDF]

, 2008
As part of a cluster workshop on sustainability of hydrogen transport technologies held in Frankfurt on 21st February 2006, MATISSE researchers conducted break-out discussion groups with, and distributed self-completion questionnaires to, stakeholders in
Cassen, Christophe, Crassous, Renaud, Dorin, Bruno, Gitz, Vincent, Hourcade, Jean-Charles   +4 more
core  

Heat pump detection and load disaggregation in low-resolution smart meter data with convolutional neural networks

Energy and AI
The transition from fossil heating systems to heat pumps introduces new challenges for energy grid management, particularly due to their contribution to peak loads.
Olivier Gisiger, Andreas Melillo, Philipp Schuetz   +2 more
doaj   +1 more source