[HTML][HTML] Artificial intelligence techniques for enabling Big Data services in distribution networks: A review
Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …
systems by extracting value from the data generated by the deployed metering and sensing …
A comprehensive overview on demand side energy management towards smart grids: challenges, solutions, and future direction
Demand-side management, a new development in smart grid technology, has enabled
communication between energy suppliers and consumers. Demand side energy …
communication between energy suppliers and consumers. Demand side energy …
Towards trustworthy energy disaggregation: A review of challenges, methods, and perspectives for non-intrusive load monitoring
Non-intrusive load monitoring (NILM) is the task of disaggregating the total power
consumption into its individual sub-components. Over the years, signal processing and …
consumption into its individual sub-components. Over the years, signal processing and …
LSTM enhanced by dual-attention-based encoder-decoder for daily peak load forecasting
K Zhu, Y Li, W Mao, F Li, J Yan - Electric Power Systems Research, 2022 - Elsevier
Daily peak load forecasting is a challenging problem in the filed of electric power load
forecasting. Since the nonlinear and dynamic of influence factors and their sequential …
forecasting. Since the nonlinear and dynamic of influence factors and their sequential …
Non-intrusive load disaggregation by convolutional neural network and multilabel classification
Non-intrusive load monitoring (NILM) is the main method used to monitor the energy
footprint of a residential building and disaggregate total electrical usage into appliance …
footprint of a residential building and disaggregate total electrical usage into appliance …
Real-time corporate carbon footprint estimation methodology based on appliance identification
Achieving carbon neutrality is widely recognized as the key measure to mitigate climate
change. As the basis for achieving carbon neutrality, corporate carbon footprint (CCF) …
change. As the basis for achieving carbon neutrality, corporate carbon footprint (CCF) …
Optimization and planning of renewable energy sources based microgrid for a residential complex
World population growth and increased energy demand are taking a heavy toll on the
environment. Aside from developed countries, the adverse effects are far more apparent in …
environment. Aside from developed countries, the adverse effects are far more apparent in …
Nonintrusive load monitoring using an LSTM with feedback structure
H Hwang, S Kang - IEEE Transactions on Instrumentation and …, 2022 - ieeexplore.ieee.org
Many non-intrusive load monitoring (NILM) studies use high-frequency data to classify the
device's ON/OFF state. However, these approaches cannot be applied in real-world …
device's ON/OFF state. However, these approaches cannot be applied in real-world …
Industrial load disaggregation based on hidden Markov models
Non-intrusive load monitoring (NILM) technology can identify the energy consumed by each
individual device from the aggregate electricity measurements, contributing to energy saving …
individual device from the aggregate electricity measurements, contributing to energy saving …
[HTML][HTML] An IoT deep learning-based home appliances management and classification system
The rise in household energy consumption globally has increased the necessity for effective
electricity consumption management and load monitoring. Smart meters can facilitate fine …
electricity consumption management and load monitoring. Smart meters can facilitate fine …