[HTML][HTML] Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review
The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial
Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to …
Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to …
[HTML][HTML] Artificial intelligence and machine learning in energy systems: A bibliographic perspective
Economic development and the comfort-loving nature of human beings in recent years have
resulted in increased energy demand. Since energy resources are scarce and should be …
resulted in increased energy demand. Since energy resources are scarce and should be …
Accurate one step and multistep forecasting of very short-term PV power using LSTM-TCN model
Accurate PV power forecasting is becoming a mandatory task to integrate the PV plant into
the electrical grid, scheduling and guaranteeing the safety of the power grid. In this paper, a …
the electrical grid, scheduling and guaranteeing the safety of the power grid. In this paper, a …
Prediction of solar energy guided by pearson correlation using machine learning
Solar energy forecasting represents a key element in increasing the competitiveness of solar
power plants in the energy market and reducing the dependence on fossil fuels in economic …
power plants in the energy market and reducing the dependence on fossil fuels in economic …
[HTML][HTML] Artificial intelligence in renewable energy: A comprehensive bibliometric analysis
L Zhang, J Ling, M Lin - Energy Reports, 2022 - Elsevier
In recent years, artificial intelligence methods have been widely applied to solve issues
related to renewable energy because of their ability to solve nonlinear and complex data …
related to renewable energy because of their ability to solve nonlinear and complex data …
A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda
Artificial intelligence (AI) will transform business practices and industries and has the
potential to address major societal problems, including sustainability. Degradation of the …
potential to address major societal problems, including sustainability. Degradation of the …
Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
[HTML][HTML] Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models
Short-term photovoltaic (PV) power forecasting is essential for integrating renewable energy
sources into the grid as it provides accurate and timely information on the expected output of …
sources into the grid as it provides accurate and timely information on the expected output of …
Building-Integrated Photovoltaic (BIPV) products and systems: A review of energy-related behavior
This paper reviews the main energy-related features of building-integrated photovoltaic
(BIPV) modules and systems, to serve as a reference for researchers, architects, BIPV …
(BIPV) modules and systems, to serve as a reference for researchers, architects, BIPV …