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Dual-stage ensemble approach using online knowledge distillation for forecasting carbon emissions in the electric power industry

Lin, Ruibin; Lv, Xing; Hu, Huanling; Ling, Liwen; Yu, Zehui - In: Data science and management : DSM 6 (2023) 4, pp. 227-238

The electric power industry is the key to achieving the goals of carbon peak and neutrality. Accurate forecasting of carbon emissions in the electric power industry can aid in the prompt adjustment of power generation policies and the early achievement of carbon reduction targets. This study...

Persistent link: https://www.econbiz.de/10014518024

Exponential smoothing with covariates applied to electricity demand forecast

Bermúdez, José D. - In: European journal of industrial engineering : EJIE 7 (2013) 3, pp. 333-349

Persistent link: https://www.econbiz.de/10010200309

Electrical load forecasting to plan the increase in renewable energy sources and electricity demand : a CNN-QR-RTCF and deep learning approach

Jiotsop-Foze, Wellcome Peujio; Hernández-del-Valle, Adrián - In: International Journal of Energy Economics and Policy : IJEEP 14 (2024) 4, pp. 186-194

Persistent link: https://www.econbiz.de/10014635888

Assessing the effectiveness of the policies to boost hydropower consumption

Solarin Sakiru Adebola - In: International journal of energy sector management : IJESM 9 (2015) 2, pp. 136-155

Persistent link: https://www.econbiz.de/10011349015

Forecasting Long-Term Electricity Demand Time Series Using Artificial Neural Networks

Behm, Christian; Nolting, Lars; Praktiknjo, Aaron - 2020

Accurate forecast of electricity load are increasingly important. We present a method to forecast long-term weather …-dependent hourly electricity load using artificial neural networks. The fully connected dense artificial neural networks with 5 hidden … prediction accuracy of future electricity loads …

Persistent link: https://www.econbiz.de/10014102164

Forecast of Iran's electricity consumption using a combined approach of neural networks and econometrics

Aghaeifar, Roya; Pourkazemi, Mohammad Hossein - In: Iranian economic review : journal of University of Tehran 17 (2013) 3, pp. 139-159

Persistent link: https://www.econbiz.de/10010347503

A comparison of univariate methods for forecasting electricity demand up to a day ahead

Taylor, James W.; De Menezes, Lilian M.; McSharry, … - In: International journal of forecasting 22 (2006) 1, pp. 1-16

Persistent link: https://www.econbiz.de/10003283925

Modelling and forecasting India's electricity consumption using artificial neural networks

Bandyopadhyay, Arunava; Sarkar, Bishal Dey; Hossain, … - In: OPEC energy review 48 (2024) 2, pp. 65-77

Persistent link: https://www.econbiz.de/10014577442

Electricity consumption prediction using artificial intelligence

Čegovnik, Tomaž; Dobrovoljc, Andrej; Povh, Janez; … - In: Central European journal of operations research 31 (2023) 3, pp. 833-851

Persistent link: https://www.econbiz.de/10014326562

Artificial neural networks for spot electricity price forecasting : a review

Vijayalakshmi, Sedidi; Girish, Godekere Panchakshara Murthy - In: International Journal of Energy Economics and Policy : IJEEP 5 (2015) 4, pp. 1092-1097

Persistent link: https://www.econbiz.de/10011456481