Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives

Y Hu, Y Man - Renewable and Sustainable Energy Reviews, 2023 - Elsevier
The industrial process consumes substantial energy and emits large amounts of carbon
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …

[HTML][HTML] Transfer learning in demand response: A review of algorithms for data-efficient modelling and control

T Peirelinck, H Kazmi, BV Mbuwir, C Hermans… - Energy and AI, 2022 - Elsevier
A number of decarbonization scenarios for the energy sector are built on simultaneous
electrification of energy demand, and decarbonization of electricity generation through …

A hybrid RF-LSTM based on CEEMDAN for improving the accuracy of building energy consumption prediction

I Karijadi, SY Chou - Energy and Buildings, 2022 - Elsevier
An accurate method for building energy consumption prediction is important for building
energy management systems. However, building energy consumption data often exhibits …

[HTML][HTML] Artificial intelligence in renewable systems for transformation towards intelligent buildings

Y Zhou - Energy and AI, 2022 - Elsevier
Carbon-neutrality transition in building sectors requires combinations of renewable systems
and artificial intelligence (AI) for robustness, reliability, automation, and flexibility. In this …

Mid-term electricity demand forecasting using improved variational mode decomposition and extreme learning machine optimized by sparrow search algorithm

T Gao, D Niu, Z Ji, L Sun - Energy, 2022 - Elsevier
Mid-term electricity demand forecasting plays an important role in ensuring the operational
safety of the power system and the economic efficiency of grid companies. Most studies …

[PDF][PDF] A comprehensive review of artificial intelligence and machine learning applications in energy sector

A Raihan - Journal of Technology Innovations and Energy, 2023 - researchgate.net
The energy industry worldwide is today confronted with several challenges, including
heightened levels of consumption and inefficiency, volatile patterns in demand and supply …

Short-term load forecasting of multi-energy in integrated energy system based on multivariate phase space reconstruction and support vector regression mode

H Liu, Y Tang, Y Pu, F Mei, D Sidorov - Electric Power Systems Research, 2022 - Elsevier
In order to alleviate the energy crisis and improve the energy utilization rate, the integrated
energy system (IES) has become an important way of energy utilization. IES integrates …

Individual household demand response potential evaluation and identification based on machine learning algorithms

R Shi, Z Jiao - Energy, 2023 - Elsevier
Modern power systems are facing an increase in the penetration of renewables to achieve
carbon neutrality targets in the future. Individual household demand response (DR) is a …

[HTML][HTML] Electrical demand aggregation effects on the performance of deep learning-based short-term load forecasting of a residential building

A Shaqour, T Ono, A Hagishima, H Farzaneh - Energy and AI, 2022 - Elsevier
Modern power grids face the challenge of increasing renewable energy penetration that is
stochastic in nature and calls for accurate demand predictions to provide the optimized …

[HTML][HTML] An ontology-based innovative energy modeling framework for scalable and adaptable building digital twins

J Bjørnskov, M Jradi - Energy and Buildings, 2023 - Elsevier
Digitalization of buildings and the use of IoT sensing and metering devices are steadily
increasing, offering new opportunities for more autonomous, efficient, and flexible buildings …