Application of artificial intelligence for prediction, optimization, and control of thermal energy storage systems

AG Olabi, AA Abdelghafar, HM Maghrabie… - Thermal Science and …, 2023 - Elsevier
Energy storage is one of the core concepts demonstrated incredibly remarkable
effectiveness in various energy systems. Energy storage systems are vital for maximizing the …

[HTML][HTML] Modelling community-scale renewable energy and electric vehicle management for cold-climate regions using machine learning

R Zahedi, M hasan Ghodusinejad, A Aslani… - Energy Strategy …, 2022 - Elsevier
With increasing environmental problems of fossil fuel-based devices and systems in
societies, diffusion and adoption of sustainability solutions such as renewable energy …

Building energy load forecasting using deep neural networks

DL Marino, K Amarasinghe… - IECON 2016-42nd annual …, 2016 - ieeexplore.ieee.org
Ensuring sustainability demands more efficient energy management with minimized energy
wastage. Therefore, the power grid of the future should provide an unprecedented level of …

Deep neural networks for energy load forecasting

K Amarasinghe, DL Marino… - 2017 IEEE 26th …, 2017 - ieeexplore.ieee.org
Smartgrids of the future promise unprecedented flexibility in energy management. Therefore,
accurate predictions/forecasts of energy demands (loads) at individual site and aggregate …

Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods

Z He, W Guo, P Zhang - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Capable of storing and redistributing energy, thermal energy storage (TES) shows a
promising applicability in energy systems. Recently, artificial intelligence (AI) technique is …

Towards efficient electricity forecasting in residential and commercial buildings: A novel hybrid CNN with a LSTM-AE based framework

ZA Khan, T Hussain, A Ullah, S Rho, M Lee, SW Baik - Sensors, 2020 - mdpi.com
Due to industrialization and the rising demand for energy, global energy consumption has
been rapidly increasing. Recent studies show that the biggest portion of energy is consumed …

[HTML][HTML] Smart design and control of thermal energy storage in low-temperature heating and high-temperature cooling systems: A comprehensive review

A Behzadi, S Holmberg, C Duwig, F Haghighat… - … and Sustainable Energy …, 2022 - Elsevier
Thermal energy storage (TES) is recognized as a well-established technology added to the
smart energy systems to support the immediate increase in energy demand, flatten the rapid …

Building energy management systems: The age of intelligent and adaptive buildings

M Manic, D Wijayasekara… - IEEE Industrial …, 2016 - ieeexplore.ieee.org
Building automation systems (BAS), or building control systems (BCS), typically consist of
building energy management systems (BEMSs), physical security and access control …

Electrical energy prediction in residential buildings for short-term horizons using hybrid deep learning strategy

ZA Khan, A Ullah, W Ullah, S Rho, M Lee, SW Baik - Applied Sciences, 2020 - mdpi.com
Smart grid technology based on renewable energy and energy storage systems are
attracting considerable attention towards energy crises. Accurate and reliable model for …

Evolutionary deep learning-based energy consumption prediction for buildings

A Almalaq, JJ Zhang - ieee access, 2018 - ieeexplore.ieee.org
Today's energy resources are closer to consumers due to sustainable energy and advanced
technology. To that end, ensuring a precise prediction of energy consumption at the …