Artificial intelligence (AI) development in the Vietnam's energy and economic systems: A critical review
Vietnam plans to develop artificial intelligence (AI) markets but is still at the early
development stages of investment, regulation and research development. A critical review of …
development stages of investment, regulation and research development. A critical review of …
[HTML][HTML] Machine learning assisted prediction of solar to liquid fuel production: a case study
In this era of heightened environmental awareness, the global community faces the critical
challenge of climate change. Renewable energy (RE) emerges as a vital contender to …
challenge of climate change. Renewable energy (RE) emerges as a vital contender to …
Carbon Dioxide-focused Greenhouse Gas Emissions from Petrochemical Plants and Associated Industries: Critical Overview, Recent Advances and Future Prospects …
Petrochemical production, a resource-and energy-intensive industry, is a major cause of
greenhouse gas emissions. As part of the low-carbon transition to net-zero emissions …
greenhouse gas emissions. As part of the low-carbon transition to net-zero emissions …
[HTML][HTML] Data analytics for prediction of solar PV power generation and system performance: A real case of Bui Solar Generating Station, Ghana
The grid-connected solar power generated by the Bui Power Authority is sold to Ghana Grid
Company Limited (GRIDCo) and other customers through bilateral contracts. However, there …
Company Limited (GRIDCo) and other customers through bilateral contracts. However, there …
[HTML][HTML] Refining Long Short-Term Memory Neural Network Input Parameters for Enhanced Solar Power Forecasting
L Bui Duy, N Nguyen Quang, B Doan Van… - Energies, 2024 - mdpi.com
This article presents a research approach to enhancing the quality of short-term power
output forecasting models for photovoltaic plants using a Long Short-Term Memory (LSTM) …
output forecasting models for photovoltaic plants using a Long Short-Term Memory (LSTM) …
Key players in renewable energy and artificial intelligence research
R Eslava-Zapata, V Sánchez-Castillo… - … on Energy Web, 2024 - publications.eai.eu
INTRODUCTION: As countries work on the transition towards renewable energies that
comply with the 2030 Agenda and the sustainable development goals, Artificial Intelligence …
comply with the 2030 Agenda and the sustainable development goals, Artificial Intelligence …
A recent invasion wave of deep learning in solar power forecasting techniques using ANN
Since 2000, solar power has grown rapidly to meet the electricity demand for daily life,
industry, agriculture, service… In the development of solar energy, forecasting the …
industry, agriculture, service… In the development of solar energy, forecasting the …
Forecasting of solar power generation in Vietnam deploying a simple GRU model
Solar energy is a renewable energy source that is widely used in the world. It is
characterized by its instability and susceptibility to weather changes. Forecasting the power …
characterized by its instability and susceptibility to weather changes. Forecasting the power …
Enhancing the Photovoltaic Power Forecasting of Lstm Models Using Clear Sky Solar Irradiance as Input
N Nguyen Quang, LD Bui, B Doan Van… - Linh Duy and Doan … - papers.ssrn.com
This article presents a research idea aimed at enhancing the quality of short-term power
output forecasting models for photovoltaic plants using the Long Short-Term Memory (LSTM) …
output forecasting models for photovoltaic plants using the Long Short-Term Memory (LSTM) …
[PDF][PDF] Enhancing the photovoltaic power forecasting of LSTM models using clear sky solar irradiance as input
LD Buib, NQ Nguyena, D Van Binha, ER Sanseverinoc… - academia.edu
This article presents a research idea aimed at enhancing the quality of short-term power
output forecasting models for photovoltaic plants using the Long Short-Term Memory (LSTM) …
output forecasting models for photovoltaic plants using the Long Short-Term Memory (LSTM) …