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 …

[HTML][HTML] A systematic review of machine learning techniques related to local energy communities

A Hernandez-Matheus, M Löschenbrand, K Berg… - … and Sustainable Energy …, 2022‏ - Elsevier
In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …

A systematic review of real-time detection and classification of power quality disturbances

JE Caicedo, D Agudelo-Martínez… - … and Control of …, 2023‏ - ieeexplore.ieee.org
This paper offers a systematic literature review of real-time detection and classification of
Power Quality Disturbances (PQDs). A particular focus is given to voltage sags and notches …

Deep learning methods and applications for electrical power systems: A comprehensive review

AK Ozcanli, F Yaprakdal… - International Journal of …, 2020‏ - Wiley Online Library
Over the past decades, electric power systems (EPSs) have undergone an evolution from an
ordinary bulk structure to intelligent flexible systems by way of advanced electronics and …

Review of AI applications in harmonic analysis in power systems

A Eslami, M Negnevitsky, E Franklin, S Lyden - Renewable and Sustainable …, 2022‏ - Elsevier
Harmonics and waveform distortion is a significant power quality problem in modern power
systems with high penetration of Renewable Energy Sources (RES). This problem has …

A critical analysis of methodologies for detection and classification of power quality events in smart grid

RK Beniwal, MK Saini, A Nayyar, B Qureshi… - IEEE …, 2021‏ - ieeexplore.ieee.org
Recently, power quality (PQ) issues have drawn considerable attention of the researchers
due to the increasing awareness of the customers towards power quality. The PQ issues …

Detection and classification of multiple power quality disturbances in Microgrid network using probabilistic based intelligent classifier

ST Suganthi, A Vinayagam, V Veerasamy… - Sustainable Energy …, 2021‏ - Elsevier
Microgrid (MG) networks have evolved as reliable power source for providing secure,
reliable, and low carbon emission of energy supply to the remote communities. Power …

Deep learning in electrical utility industry: A comprehensive review of a decade of research

M Mishra, J Nayak, B Naik, A Abraham - Engineering Applications of …, 2020‏ - Elsevier
Smart-grid (SG) is a new revolution in the electrical utility industry (EUI) over the past
decade. With each moving day, some new advanced technologies are coming into the …

A novel hybrid deep learning approach including combination of 1D power signals and 2D signal images for power quality disturbance classification

H Sindi, M Nour, M Rawa, Ş Öztürk, K Polat - Expert Systems with …, 2021‏ - Elsevier
As a result of the widespread use of power electronic equipment and the increase in
consumption, the importance of effective energy policies and the smart grid begins to …

[HTML][HTML] A comprehensive survey on load forecasting hybrid models: Navigating the Futuristic demand response patterns through experts and intelligent systems

K Fida, U Abbasi, M Adnan, S Iqbal… - Results in Engineering, 2024‏ - Elsevier
Load forecasting is a crucial task, which is carried out by utility companies for sake of power
grids' successful planning, optimized operation and control, enhanced performance, and …