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Monitoring and control of electrical power systems using machine learning techniques /

"Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and re...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Espejo, Emilio Barocio (Editor), Sevilla, Felix Rafael Segundo (Editor), Korba, Petr (Editor)
Format: eBook
Language:English
Published: Amsterdam, Netherlands ; Oxford, United Kingdom ; Cambridge MA : Elsevier, [2023]
Subjects:
Electric power systems > Control.
Machine learning.
Réseaux électriques (Énergie) > Régulation.
Apprentissage automatique.
Electric power systems > Control
Machine learning
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • 1 Derivation of generic equivalent models for distribution network analysis using artificial intelligence techniques
  • l2 Disturbance dataset development for machine-learning-based power quality monitoring in distributed generation systems: a practical guide
  • l3 Advances in compression algorithms for PMU and Smart Meter data based on tensor decomposition
  • l4 Machine learning and digital twins: monitoring and control for dynamic security in power systems
  • l5 Synchrophasor applications in distribution systems: real-life experience
  • l6 A graph mapping based supervised machine learning strategy for PMU voltage anomalies' detection and classification in distribution networks
  • l7 Identification of source harmonics in electrical networks using spatiotemporal approaches
  • l8 Power quality harmonic monitoring by the O-splines-based multiresolution signal decomposition
  • l9 Monitoring system for identifying power quality issues in distribution networks using Petri nets and Prony method
  • l10 Dynamic voltage restorer controlled per independent phases for power quality sags-swells mitigation under unbalanced conditions
  • l11 AI application for load forecasting: a comparison of classical and deep learning methodologies
  • l12 Study of harmonics in linear, nonlinear nonsinusoidal electrical circuits by geometric algebra
  • l13 Harmonic sources estimation in distribution systems