Deep Neural Networks in Power Systems: A Review

M Khodayar, J Regan - Energies, 2023 - mdpi.com
Identifying statistical trends for a wide range of practical power system applications,
including sustainable energy forecasting, demand response, energy decomposition, and …

Energy 4.0: AI-enabled digital transformation for sustainable power networks

M Khalid - Computers & Industrial Engineering, 2024 - Elsevier
The exponential rise of green technology has changed several industries, including the
energy business, especially the power sector. These advances have transformed power …

Advances in Deep Learning Techniques for Short-term Energy Load Forecasting Applications: A Review

R Chandrasekaran, SK Paramasivan - Archives of Computational Methods …, 2024 - Springer
Today, the majority of the leading power companies place a significant emphasis on
forecasting the electricity load in the balance of power and administration. Meanwhile, since …

Machine-learning-based electric power forecasting

G Chen, Q Hu, J Wang, X Wang, Y Zhu - Sustainability, 2023 - mdpi.com
The regional demand for electric power is influenced by a variety of factors, such as
fluctuations in business cycles, dynamic linkages among regional development, and climate …

AnIO: anchored input–output learning for time-series forecasting

O Stentoumi, P Nousi, M Tzelepi, A Tefas - Neural Computing and …, 2024 - Springer
In this work, the short-term electric load demand forecasting problem is addressed,
proposing a method inspired by the use of anchors in object detection methods. Specifically …

Electricity Consumption Prediction in an Electronic System Using Artificial Neural Networks

MA Stošović, N Radivojević, M Ivanova - Electronics, 2022 - mdpi.com
The tremendous rise of electrical energy demand worldwide has led to many problems
related to efficient use of electrical energy, consequently posing difficult challenges to …

Utilize the Prediction Results from the Neural Network Gate Recurrent Unit (GRU) Model to Optimize Reactive Power Usage in High-Rise Buildings

A Rofii, B Soerowirdjo, R Irawan… - International Journal of …, 2024 - pubs2.ascee.org
The growing urbanization and the construction sector, efficient use of electric energy
becomes important, especially the use of reactive power. If excessive use causes decreased …

Short-term electric load demand forecasting on Greek energy market using deep learning: a comparative study

G Emmanouilidis, M Tzelepi… - … Conference on Electronics …, 2022 - ieeexplore.ieee.org
In this paper, we deal with the short-term Electric Load Demand Forecasting problem,
considering the Greek Energy Market. Particularly, we focus on two short-term cases …

Time Series Forecasting of Electricity Load Using Hybrid CNN-BiLSTM with an Attention Approach: A Case Study in Bali, Indonesia

BS Prasetyo, D Adytia, IA Aditya - … International Conference on …, 2023 - ieeexplore.ieee.org
The use of electrical energy continues to increase from time to time, in line with the
promotion of green energy. Prediction of the use of electricity load is crucial for increasing …

Analysis and Functioning of Smart Grid for Enhancing Energy Efficiency Using OptimizationTechniques with IoT

S Pradeep, S Krishna, MS Reddy… - 2023 IEEE 5th …, 2023 - ieeexplore.ieee.org
The implementation of smart grids has emerged as a promising solution to enhance energy
efficiency and address the challenges posed by the growing energy demands and …