Deep learning for renewable energy forecasting: A taxonomy, and systematic literature review
C Ying, W Wang, J Yu, Q Li, D Yu, J Liu - Journal of Cleaner Production, 2023 - Elsevier
In order to identify power production and demand in realtime for efficient and dependable
management for diverse renewable energy systems, precise and intuitive renewable energy …
management for diverse renewable energy systems, precise and intuitive renewable energy …
Weather forecasting for renewable energy system: a review
Energy crisis and climate change are the major concerns which has led to a significant
growth in the renewable energy resources which includes mainly the solar and wind power …
growth in the renewable energy resources which includes mainly the solar and wind power …
[HTML][HTML] Time-series analysis with smoothed Convolutional Neural Network
CNN originates from image processing and is not commonly known as a forecasting
technique in time-series analysis which depends on the quality of input data. One of the …
technique in time-series analysis which depends on the quality of input data. One of the …
[HTML][HTML] Trends and gaps in photovoltaic power forecasting with machine learning
The share of solar energy in the electricity mix increases year after year. Knowing the
production of photovoltaic (PV) power at each instant of time is crucial for its integration into …
production of photovoltaic (PV) power at each instant of time is crucial for its integration into …
[HTML][HTML] A state-of-art-review on machine-learning based methods for PV
In the current era, Artificial Intelligence (AI) is becoming increasingly pervasive with
applications in several applicative fields effectively changing our daily life. In this scenario …
applications in several applicative fields effectively changing our daily life. In this scenario …
[HTML][HTML] A review on artificial intelligence applications for grid-connected solar photovoltaic systems
The use of artificial intelligence (AI) is increasing in various sectors of photovoltaic (PV)
systems, due to the increasing computational power, tools and data generation. The …
systems, due to the increasing computational power, tools and data generation. The …
Integrated multiple directed attention-based deep learning for improved air pollution forecasting
In recent years, human health across the world is becoming concerned by a constant threat
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …
Comparison of physical and machine learning models for estimating solar irradiance and photovoltaic power
RAA Ramadhan, YRJ Heatubun, SF Tan, HJ Lee - Renewable Energy, 2021 - Elsevier
Conventional models to estimate solar irradiance and photovoltaic power rely on physics
and use empirical correlations to handle regional climate and complex physics. Recently …
and use empirical correlations to handle regional climate and complex physics. Recently …
A review: State estimation based on hybrid models of Kalman filter and neural network
S Feng, X Li, S Zhang, Z Jian, H Duan… - Systems Science & …, 2023 - Taylor & Francis
In this paper, hybrid models of Kalman filter and neural network for state estimation are
reviewed of their corresponding academic achievements, the creation of which is a …
reviewed of their corresponding academic achievements, the creation of which is a …
[HTML][HTML] A comparative analysis to forecast carbon dioxide emissions
Despite the growing knowledge and commitment to climate change, carbon dioxide (CO 2)
emissions continue to rise dramatically throughout the planet. In recent years, the …
emissions continue to rise dramatically throughout the planet. In recent years, the …