Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities

T Ahmad, D Zhang, C Huang, H Zhang, N Dai… - Journal of Cleaner …, 2021 - Elsevier
The energy industry is at a crossroads. Digital technological developments have the
potential to change our energy supply, trade, and consumption dramatically. The new …

Electricity load forecasting: a systematic review

IK Nti, M Teimeh, O Nyarko-Boateng… - Journal of Electrical …, 2020 - Springer
The economic growth of every nation is highly related to its electricity infrastructure, network,
and availability since electricity has become the central part of everyday life in this modern …

Applications of random forest in multivariable response surface for short-term load forecasting

GF Fan, LZ Zhang, M Yu, WC Hong, SQ Dong - International Journal of …, 2022 - Elsevier
Accurate load forecasting is helpful for optimizing the use of power resources. To this end,
this investigation proposes a hybrid model for short-term load forecasting, namely the RF …

A transformer-based method of multienergy load forecasting in integrated energy system

C Wang, Y Wang, Z Ding, T Zheng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Multienergy load forecasting technique is the basis for the operation and scheduling of
integrated energy system. Different types of loads in an integrated energy system, ie …

[HTML][HTML] A review of the use of artificial intelligence methods in infrastructure systems

L McMillan, L Varga - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
The artificial intelligence (AI) revolution offers significant opportunities to capitalise on the
growth of digitalisation and has the potential to enable the 'system of systems' approach …

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 …

Short-term load forecasting using channel and temporal attention based temporal convolutional network

X Tang, H Chen, W **ang, J Yang, M Zou - Electric Power Systems …, 2022 - Elsevier
Load forecasting is the foundation of power system operation and planning. Accurate load
forecasting can secure the safe and reliable operation of the power system, cut power …

Short-term electricity load forecasting with machine learning

E Aguilar Madrid, N Antonio - Information, 2021 - mdpi.com
An accurate short-term load forecasting (STLF) is one of the most critical inputs for power
plant units' planning commitment. STLF reduces the overall planning uncertainty added by …

Uncovering the impact of the COVID-19 pandemic on energy consumption: New insight from difference between pandemic-free scenario and actual electricity …

Q Wang, S Li, F Jiang - Journal of Cleaner Production, 2021 - Elsevier
The existing measurement of the impact of the COVID-19 pandemic on energy consumption
is based on changes between the years, which demonstrates the changes in energy …

Electrical load forecasting: A deep learning approach based on K-nearest neighbors

Y Dong, X Ma, T Fu - Applied Soft Computing, 2021 - Elsevier
Deep learning approaches have shown superior advantages than shallow techniques in the
field of electrical load forecasting; however, their applications in existing studies encounter …