Advanced Technologies in Power Grids Optimization using IoT and AI | Energy efficiency using the Internet of Things and the Artificial Intelligence

Kitmo (u. a.)

ISBN 10: 6208456738 / ISBN 13: 9786208456733

Published by LAP LAMBERT Academic Publishing, 2025

About this Item

Advanced Technologies in Power Grids Optimization using IoT and AI | Energy efficiency using the Internet of Things and the Artificial Intelligence | Kitmo (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208456733 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

Seller Inventory # 134066503

Bibliographic Details

• Title: Advanced Technologies in Power Grids Optimization using IoT and AI | Energy efficiency using the Internet of Things and the Artificial Intelligence
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2025
• Language: English
• ISBN 10: 6208456738
• ISBN 13: 9786208456733
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 125 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This work presents a method for optimizing the performance of energy systems using the Internet of Things and artificial intelligence. The method automatically detects voltage dips. Fault correction is performed automatically in real time by reconfiguring and automatically recombining switches across the entire system. This technique provides an easy way to supervise power networks using SCADA devices. Adaptive particle swarm optimization (APSO) algorithms are proposed to evaluate power losses and voltage dips (PLVD) on the radial distribution system (RDS). The IEEE 33 bus standard test is used to study the power quality of the proposed system. Three suitable locations for the injection of photovoltaic distributed sources (PDS) are determined based on the reduction in power loss and the voltage index. The system rectifies faults such as power factor deviation (PFD) or partial shading of solar cells by reconfiguring and automatically recombining the 33-bus radial system branches. An Adaptive particle swarm optimization (APSO) has enabled the power profile to be improved and demonstrated the reliability of the proposed method.