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 …
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques
The modernisation of the world has significantly reduced the prime sources of energy such
as coal, diesel and gas. Thus, alternative energy sources based on renewable energy have …
as coal, diesel and gas. Thus, alternative energy sources based on renewable energy have …
Taxonomy research of artificial intelligence for deterministic solar power forecasting
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …
stochastic and volatile nature of solar power pose significant challenges to the reliable …
Predictive modeling of compressive strength of sustainable rice husk ash concrete: Ensemble learner optimization and comparison
One of the largest sources of greenhouse gas (GHG) emissions is the construction concrete
industry which has alone 50% of the world's emissions. One possible remedy to mitigate the …
industry which has alone 50% of the world's emissions. One possible remedy to mitigate the …
A survey of machine learning models in renewable energy predictions
The use of renewable energy to reduce the effects of climate change and global warming
has become an increasing trend. In order to improve the prediction ability of renewable …
has become an increasing trend. In order to improve the prediction ability of renewable …
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 …
Short-term photovoltaic power point-interval forecasting based on double-layer decomposition and WOA-BiLSTM-Attention and considering weather classification
M Yu, D Niu, K Wang, R Du, X Yu, L Sun, F Wang - Energy, 2023 - Elsevier
A reliable short-term forecast of photovoltaic power (PVPF) is essential to maintaining stable
power systems and optimizing power grid dispatch. A hybrid prediction framework of PVPF …
power systems and optimizing power grid dispatch. A hybrid prediction framework of PVPF …
Revolutionizing solar energy with ai-driven enhancements in photovoltaic technology
A Mohammad, F Mahjabeen - … Jurnal Multidisiplin Ilmu, 2023 - journal.mediapublikasi.id
The important contribution of artificial intelligence (AI) to improving solar cell performance
and its effects on sustainability and the integration of renewable energy. The article covers a …
and its effects on sustainability and the integration of renewable energy. The article covers a …
A hybrid photovoltaic/wind power prediction model based on Time2Vec, WDCNN and BiLSTM
D Geng, B Wang, Q Gao - Energy conversion and management, 2023 - Elsevier
Accurate prediction of photovoltaic (PV)/wind power is an effective solution for the grid
stability, reasonable dispatching and power supply reliability. Nowadays, various deep …
stability, reasonable dispatching and power supply reliability. Nowadays, various deep …