Digital technologies for a net-zero energy future: A comprehensive review

MM Ferdaus, T Dam, S Anavatti, S Das - Renewable and Sustainable …, 2024 - Elsevier
The energy sector plays a vital role in achieving a sustainable net-zero future, and the
adoption of advanced technologies such as AI, blockchain, quantum computing, digital twin …

A Kalman filter-based bottom-up approach for household short-term load forecast

Z Zheng, H Chen, X Luo - Applied Energy, 2019 - Elsevier
Renewable energy sources are now being used with buildings like PV panels.
Consequently, short-term household load forecast plays an important role in managing …

[HTML][HTML] A comprehensive review towards resilient rainfall forecasting models using artificial intelligence techniques

MA Saleh, HM Rasel, B Ray - Green Technologies and Sustainability, 2024 - Elsevier
Rainfall is one of the remarkable hydrologic variables that is directly connected to the
sustainable environment for any region over the globe. The present study aims to review …

An optimal hybrid bi-component series-parallel structure for time series forecasting

Z Hajirahimi, M Khashei - IEEE Transactions on Knowledge …, 2023 - ieeexplore.ieee.org
Modeling and forecasting of real-world systems have become one of the most critical needs
in different science kinds. Among various factors considered in selecting an appropriate …

A rank analysis and ensemble machine learning model for load forecasting in the nodes of the central Mongolian power system

T Osgonbaatar, P Matrenin, M Safaraliev, I Zicmane… - Inventions, 2023 - mdpi.com
Forecasting electricity consumption is currently one of the most important scientific and
practical tasks in the field of electric power industry. The early retrieval of data on expected …

A deep neural network-assisted approach to enhance short-term optimal operational scheduling of a microgrid

F Yaprakdal, MB Yılmaz, M Baysal… - Sustainability, 2020 - mdpi.com
The inherent variability of large-scale renewable energy generation leads to significant
difficulties in microgrid energy management. Likewise, the effects of human behaviors in …

Online hour-ahead load forecasting using appropriate time-delay neural network based on multiple correlation–multicollinearity analysis in IoT energy network

MA Zamee, D Han, D Won - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
To meet up fluctuations of the real-time electric load demands, many electricity markets have
gone for the real-time-market-based operation. To do so, online forecasting of the real-time …

Weighted MLP-ARIMA series hybrid model for time series forecasting

Z Hajirahimi, M Khashei - Journal of Industrial Engineering and …, 2020 - jiems.icms.ac.ir
With the increasing importance of forecasting with the utmost degree of accuracy, utilizing
hybrid frameworks become a must for obtaining more accurate and more reliable forecasting …

Short-Term Load Foresting Using Combination of Linear and Non-linear Models

N Rani, SK Aggarwal, S Kumar - IEEE Access, 2024 - ieeexplore.ieee.org
Numerous short-term load forecasting models are available in the literature. However, the
improvement in forecast accuracy using the combination models has yet to be analyzed on a …

[PDF][PDF] Caractérisation électrique, thermique et comportementale hiérarchisée d'un agrégat de résidences en vue de la prévision énergétique à court terme

K Dab - 2024 - depot-e.uqtr.ca
Résumé L'efficacité de la gestion des réseaux électriques dépend grandement de la
capacité à anticiper de manière fiable et précise la consommation énergétique future. Cette …