State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Forecasting renewable energy efficiency significantly impacts system management and
operation because more precise forecasts mean reduced risk and improved stability and …
operation because more precise forecasts mean reduced risk and improved stability and …
COA-CNN-LSTM: Coati optimization algorithm-based hybrid deep learning model for PV/wind power forecasting in smart grid applications
Power prediction is now a crucial part of contemporary energy management systems, which
is important for the organization and administration of renewable resources. Solar and wind …
is important for the organization and administration of renewable resources. Solar and wind …
Review of strategies to mitigate dust deposition on solar photovoltaic systems
In recent years, there has been an increased focus on developing and utilizing renewable
energy resources due to several factors, including environmental concerns, rising fuel costs …
energy resources due to several factors, including environmental concerns, rising fuel costs …
Achieving wind power and photovoltaic power prediction: An intelligent prediction system based on a deep learning approach
Accurately predicting wind and photovoltaic power is one of the keys to improving the
economy of wind-solar complementary power generation system, reducing scheduling costs …
economy of wind-solar complementary power generation system, reducing scheduling costs …
[HTML][HTML] The usage of 10-fold cross-validation and grid search to enhance ML methods performance in solar farm power generation prediction
SM Malakouti, MB Menhaj, AA Suratgar - Cleaner Engineering and …, 2023 - Elsevier
It is essential to have accurate projections of the quantity of solar energy that will be
generated in the future to improve the competitiveness of solar power plants in the energy …
generated in the future to improve the competitiveness of solar power plants in the energy …
Solar and wind power data from the Chinese state grid renewable energy generation forecasting competition
Y Chen, J Xu - Scientific Data, 2022 - nature.com
Accurate solar and wind generation forecasting along with high renewable energy
penetration in power grids throughout the world are crucial to the days-ahead power …
penetration in power grids throughout the world are crucial to the days-ahead power …
Hybrid forecasting models for wind-PV systems in diverse geographical locations: performance and power potential analysis
In order to combat the global warming, much stress is put on integrating non-conventional
energy resources, such as wind power plants and solar energy systems, into standard …
energy resources, such as wind power plants and solar energy systems, into standard …
A novel network training approach for solving sample imbalance problem in wind power prediction
A Meng, Z Xian, H Yin, J Luo, X Wang, H Zhang… - Energy Conversion and …, 2023 - Elsevier
Randomness and intermittency are common challenges in wind power prediction. Most
studies focus on randomness but usually ignore the intermittency of wind power that leads to …
studies focus on randomness but usually ignore the intermittency of wind power that leads to …
Improved reptile search optimization algorithm: application on regression and classification problems
The reptile search algorithm is a newly developed optimization technique that can efficiently
solve various optimization problems. However, while solving high-dimensional nonconvex …
solve various optimization problems. However, while solving high-dimensional nonconvex …
A novel interval forecasting system based on multi-objective optimization and hybrid data reconstruct strategy
J Wang, Y Zhou, H Jiang - Expert Systems with Applications, 2023 - Elsevier
With the continuous increase in global photovoltaic installations, the importance of
photovoltaic power generation to the power industry has gradually increased, which means …
photovoltaic power generation to the power industry has gradually increased, which means …