State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Forecasting renewable energy efficiency significantly impacts system management and
operation because more precise forecasts mean reduced risk and improved stability and …
operation because more precise forecasts mean reduced risk and improved stability and …
[HTML][HTML] A hybrid stacking model for enhanced short-term load forecasting
The high penetration of distributed energy resources poses significant challenges to the
dispatch and operation of power systems. Improving the accuracy of short-term load …
dispatch and operation of power systems. Improving the accuracy of short-term load …
[HTML][HTML] A critical analysis of different power quality improvement techniques in microgrid
S Choudhury, GK Sahoo - e-Prime-Advances in Electrical Engineering …, 2024 - Elsevier
Recently, the exponential decay of traditional petroleum and coal-based reserves with the
ever-rising energy demand has led to the need for alternate energy sources. Distributed …
ever-rising energy demand has led to the need for alternate energy sources. Distributed …
[HTML][HTML] A novel cyber-Resilient solar power forecasting model based on secure federated deep learning and data visualization
A Moradzadeh, H Moayyed, B Mohammadi-Ivatloo… - Renewable Energy, 2023 - Elsevier
Improving the accuracy of photovoltaic (PV) power forecasting is crucial to ensure more
effective use of energy resources. Improvements are especially important for regions for …
effective use of energy resources. Improvements are especially important for regions for …
[HTML][HTML] Smart grid enterprise decision-making and economic benefit analysis based on LSTM-GAN and edge computing algorithm
P Yang, S Li, S Qin, L Wang, M Hu, F Yang - Alexandria Engineering …, 2024 - Elsevier
As the next-generation power system, smart grid presents challenges to enterprises in
managing and analyzing massive data, meeting complex operational and decision-making …
managing and analyzing massive data, meeting complex operational and decision-making …
Data-driven short term load forecasting with deep neural networks: Unlocking insights for sustainable energy management
W Waheed, Q Xu - Electric Power Systems Research, 2024 - Elsevier
In today's smart grid and building infrastructure, it is strongly suggested to implement short-
term demand forecasting for future power generation. There is a growing demand for …
term demand forecasting for future power generation. There is a growing demand for …
probabilistic forecasting of residential energy consumption based on SWT-QRTCN-ADSC-NLSTM Model
N Jin, L Song, GJ Huang, K Yan - Information, 2023 - mdpi.com
Residential electricity consumption forecasting plays a crucial role in the rational allocation
of resources reducing energy waste and enhancing the grid-connected operation of power …
of resources reducing energy waste and enhancing the grid-connected operation of power …
Dynamic Load Prediction Model of Electric Bus Charging Based on WNN
C Zheng, T Peng, Z Chao, Z Shasha… - Mobile Information …, 2022 - Wiley Online Library
Electric buses have a significant penetration rate and high charging frequency and amount.
Therefore, their charging load has a momentous influence on the power grid's operation and …
Therefore, their charging load has a momentous influence on the power grid's operation and …
Federated Deep Learning Technique for Power and Energy Systems Data Analysis
H Moayyed, A Moradzadeh… - … Data Mining and …, 2022 - Wiley Online Library
In recent years, there has been a tremendous increase in the application of information and
communication technologies (ICTs) in critical infrastructures, such as energy grids and …
communication technologies (ICTs) in critical infrastructures, such as energy grids and …
[PDF][PDF] e-Prime-Advances in Electrical Engineering, Electronics and Energy
S Choudhury, GK Sahoo - researchgate.net
Recently, the exponential decay of traditional petroleum and coal-based reserves with the
ever-rising energy demand has led to the need for alternate energy sources. Distributed …
ever-rising energy demand has led to the need for alternate energy sources. Distributed …