Load forecasting models in smart grid using smart meter information: a review

F Dewangan, AY Abdelaziz, M Biswal - Energies, 2023 - mdpi.com
The smart grid concept is introduced to accelerate the operational efficiency and enhance
the reliability and sustainability of power supply by operating in self-control mode to find and …

Load forecasting techniques for power system: Research challenges and survey

N Ahmad, Y Ghadi, M Adnan, M Ali - IEEE Access, 2022 - ieeexplore.ieee.org
The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …

Short-term load forecasting based on LSTM networks considering attention mechanism

J Lin, J Ma, J Zhu, Y Cui - International Journal of Electrical Power & Energy …, 2022 - Elsevier
Reliable and accurate zonal electricity load forecasting is essential for power system
operation and planning. Probabilistic load forecasts can present more comprehensive …

Review of smart meter data analytics: Applications, methodologies, and challenges

Y Wang, Q Chen, T Hong… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
The widespread popularity of smart meters enables an immense amount of fine-grained
electricity consumption data to be collected. Meanwhile, the deregulation of the power …

Probabilistic electric load forecasting: A tutorial review

T Hong, S Fan - International Journal of Forecasting, 2016 - Elsevier
Load forecasting has been a fundamental business problem since the inception of the
electric power industry. Over the past 100 plus years, both research efforts and industry …

Big data driven smart energy management: From big data to big insights

K Zhou, C Fu, S Yang - Renewable and sustainable energy reviews, 2016 - Elsevier
Large amounts of data are increasingly accumulated in the energy sector with the
continuous application of sensors, wireless transmission, network communication, and cloud …

[CITAZIONE][C] Forecasting: principles and practice

RJ Hyndman - 2018 - books.google.com
Forecasting is required in many situations. Stocking an inventory may require forecasts of
demand months in advance. Telecommunication routing requires traffic forecasts a few …

Deep learning for estimating building energy consumption

E Mocanu, PH Nguyen, M Gibescu, WL Kling - Sustainable Energy, Grids …, 2016 - Elsevier
To improve the design of the electricity infrastructure and the efficient deployment of
distributed and renewable energy sources, a new paradigm for the energy supply chain is …

Convolutional and recurrent neural network based model for short-term load forecasting

H Eskandari, M Imani, MP Moghaddam - Electric Power Systems Research, 2021 - Elsevier
The consumed electrical load is affected by many external factors such as weather, season
of the year, weekday or weekend and holiday. In this paper, it is tried to provide a high …

Two stage forecast engine with feature selection technique and improved meta-heuristic algorithm for electricity load forecasting

N Ghadimi, A Akbarimajd, H Shayeghi, O Abedinia - Energy, 2018 - Elsevier
Short-term load forecasting is of major interest for the restructured environment of the
electricity market. Accurate load forecasting is essential for effective power system operation …