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Load forecasting techniques for power system: Research challenges and survey
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 …
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
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 …
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
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 …
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
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 …
ordinary bulk structure to intelligent flexible systems by way of advanced electronics and …
Review of AI applications in harmonic analysis in power systems
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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
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 …
grids' successful planning, optimized operation and control, enhanced performance, and …