Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
The energy industry is at a crossroads. Digital technological developments have the
potential to change our energy supply, trade, and consumption dramatically. The new …
potential to change our energy supply, trade, and consumption dramatically. The new …
Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives
Y Hu, Y Man - Renewable and Sustainable Energy Reviews, 2023 - Elsevier
The industrial process consumes substantial energy and emits large amounts of carbon
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …
PV power forecasting based on data-driven models: a review
Accurate PV power forecasting techniques are a prerequisite for the optimal management of
the grid and its stability. This paper presents a review of the recent developments in the field …
the grid and its stability. This paper presents a review of the recent developments in the field …
Ultra-short-term exogenous forecasting of photovoltaic power production using genetically optimized non-linear auto-regressive recurrent neural networks
Accurate and credible ultra-short-term photovoltaic (PV) power production prediction is very
important in short-term resource planning, electric power dispatching, and operational …
important in short-term resource planning, electric power dispatching, and operational …
Hour-ahead photovoltaic generation forecasting method based on machine learning and multi objective optimization algorithm
J Wang, Y Zhou, Z Li - Applied Energy, 2022 - Elsevier
As the penetration rate of solar energy in the grid continues to enhance, solar power
photovoltaic generation forecasts have become an indispensable aspect of mechanism …
photovoltaic generation forecasts have become an indispensable aspect of mechanism …
Method and evaluations of the effective gain of artificial intelligence models for reducing CO2 emissions
P Delanoë, D Tchuente, G Colin - Journal of environmental management, 2023 - Elsevier
Nowadays, there is an increasing use of digital technologies and Artificial Intelligence (AI)
such as Machine Learning (ML) models that leverage data to optimize the performances of …
such as Machine Learning (ML) models that leverage data to optimize the performances of …
Contribution of ChatGPT and other generative artificial intelligence (AI) in renewable and sustainable energy
N Rane - Available at SSRN 4597674, 2023 - papers.ssrn.com
In the dynamic field of renewable and sustainable energy, Artificial Intelligence (AI)
integration has emerged as a crucial catalyst for enhancing efficiency, cost reduction, and …
integration has emerged as a crucial catalyst for enhancing efficiency, cost reduction, and …
[HTML][HTML] Artificial intelligent control of energy management PV system
Renewable energy systems, such as photovoltaic (PV) systems, have become increasingly
significant in response to the pressing concerns of climate change and the imperative to …
significant in response to the pressing concerns of climate change and the imperative to …
Thermoelectric energy harvesting for internet of things devices using machine learning: A review
Initiatives to minimise battery use, address sustainability, and reduce regular maintenance
have driven the challenge to use alternative power sources to supply energy to devices …
have driven the challenge to use alternative power sources to supply energy to devices …
Novel and practical photovoltaic applications
Solar energy has witnessed a rapid development during the past three decades. However
not all solar technologies have reached the same level of maturity. Photovoltaic (PV) …
not all solar technologies have reached the same level of maturity. Photovoltaic (PV) …