Proceedings of the 1st Electrical Artificial Intelligence Conference, Volume 4 : EAIC 2024, 6-8 December, Nanjing, China / edited by Ronghai Qu, Zhengxiang Song, Zhiming Ding, Gang Mu, Rui Xiong, Li Han.

Format:

Book

Contributor:

Qu, Ronghai., Editor.

Song, Zhengxiang., Editor.

Ding, Zhiming, Editor.

Mu, Gang., Editor.

Xiong, Rui, Editor.

Han, Li, Editor.

Series:

Lecture Notes in Electrical Engineering, 1876-1119 ; 1397

Language:

English

Subjects (All):

Electrical engineering.

Artificial intelligence.

Electric power production.

Electric power distribution.

Electrical and Electronic Engineering.

Artificial Intelligence.

Mechanical Power Engineering.

Energy Grids and Networks.

Local Subjects:

Electrical and Electronic Engineering.

Artificial Intelligence.

Mechanical Power Engineering.

Energy Grids and Networks.

Physical Description:

1 online resource (IX, 481 p. 236 illus., 190 illus. in color.)

Edition:

1st ed. 2025.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2025.

Summary:

This book is the fourth volume of proceedings of the 1st Electrical Artificial Intelligence Conference (EAIC 2024). Artificial intelligence and low-carbon economy are two vibrant research fields in the world today. To achieve the goal of carbon neutrality not only signifies a significant transformation in the economic growth mode and a profound adjustment of energy systems but also has equally significant implications for the global economic and social transformation. In the wave of the rapid development of digital economy, artificial intelligence has become an important driving force for promoting high-quality economic and social development. In the path to the “Dual Carbon” goals, which are the “Peak Carbon Dioxide Emissions” goal and the “Carbon Neutrality” goal, artificial intelligence will play an important role especially in energy conservation and carbon reduction in the electrical field, which is worthy of in-depth exploration and research. In order to promote the deep integration of the electrical engineering and artificial intelligence, successfully achieve the "dual carbon" goals, and promote green, low-carbon, and high-quality development, the China Electrotechnical Society and relevant units jointly held the 1st Electrical Artificial Intelligence Conference in Nanjing, China during the 6th~8th December, 2024. The conference invited well-known experts with significant influence in the fields of electrical engineering and artificial intelligence to jointly explore the application of artificial intelligence in the optimization design, fault diagnosis, intelligent control, and optimized operation of electrical equipment, promote the integration of artificial intelligence innovations and various application scenarios, and actively lead the trend of technological innovation.

Contents:

Chapter 1. Improved Integrated Energy Systems Multi-Energy Load Deep Learning Joint Prediction Method Based On CEEMDAN

Chapter 2. An Evaluation Method for Micro-Energy Networks Participating in the Electricity-Hydrogen Market Based on Cloud Model

Chapter 3. Robust Optimisation Strategy For Distribution Of Integrated Energy Systems Considering Multiple Stakeholders

Chapter 4. New Energy Power System Security and Stability Assessment Based on Apirori and Dynamic Weighted Cloud Model

Chapter 5. A Review of Cluster Electric Vehicle Charging Scheduling Based on Multi-agent Deep Reinforcement Learning

Chapter 6. Multi-Objective Optimization of Integrated Energy System Considering Double Uncertainty Of source and Load

Chapter 7. False Data Injection Method Design for Power Sensors Based on Robust Principal Component Analysis

Chapter 8. Key Technology of Joint Analysis of Cross-Modal Data for Integrated Service of Railroad Passenger Stations

Chapter 9. A Two-step Soft Open Point Location And Capacity Determination Method Based On Power Flow Betweenness

Chapter 10. Research on Intelligent Prediction Model of Ultra Short term Photovoltaic Power Generation Based on W-DA BiLSTM

Chapter 11. Fault detection method of transmission sections based on GRU deep network

Chapter 12. Construction and application of a grey prediction model based on periodical aggregation and periodical component factor

Chapter 13. Research status and intelligent application of renewable energy hydrogen production and hydrogenation integrated station

Chapter 14. Intelligent carbon emission accounting method based on deep learning algorithm

Chapter 15. Remaining life prediction of motor bearing based on fusion degradation indicator

Chapter 16. TD3 Deep Reinforcement Learning-Based Improved Sensorless MRAS Control Strategy for Multi-Electric Aircraft PMSM

Chapter 17. Diagnosis of Interturn Short Circuit Faults in Switched Reluctance Machines Based on Parameter Optimized VMD and CNN-BiLST

Chapter 18. YOLOv9-based Detection Method for Pyrotechnic Operations and Protective Equipment

Chapter 19. Verification Method for Arc Suppression Coil Tracking Compensation Performance

Chapter 20. Lithium battery SOC estimation based on BiLSTM MHSA

Chapter 21. Neural Network-Based Adaptive Sliding Mode Control for Wheel Slip Ratio Control System

Chapter 22. Comprehensive Decision-Making of Large-scale Rooftop Photovoltaic Access to Power Supply-guaranteed Microgrid

Chapter 23. Trajectory planning of digital ray detection system for welding seam of double robot rocket tank based on MATLAB

Chapter 24. Controllable Image Editing for Insulator Defect Generation and Detection

Chapter 25. Topology Optimization of Offshore Wind Farm Collection System Based on Priority Queue Esau- Williams Algorith

Chapter 26. Tabular image content reconstruction model for two- branch network design. Chapter 27. Volume Measurement Technology for Irregular Shaped Ice Cover Based on Multi-view 3D Reconstruction.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

981-9640-59-8

OCLC:

1524421878