Intelligent Data-Analytics for Condition Monitoring

Smart Grid Applications

Häftad, Engelska, 2021

1 589 kr

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Beskrivning

Intelligent Data-Analytics for Condition Monitoring: Smart Grid Applications looks at intelligent and meaningful uses of data required for an optimized, efficient engineering processes. In addition, the book provides application perspectives of various deep learning models for the condition monitoring of electrical equipment. With chapters discussing the fundamentals of machine learning and data analytics, the book is divided into two parts, including i) The application of intelligent data analytics in Solar PV fault diagnostics, transformer health monitoring and faults diagnostics, and induction motor faults and ii) Forecasting issues using data analytics which looks at global solar radiation forecasting, wind data forecasting, and more.

This reference is useful for all engineers and researchers who need preliminary knowledge on data analytics fundamentals and the working methodologies and architecture of smart grid systems.

Features deep learning methodologies in smart grid deployment and maintenance applications
Includes coding for intelligent data analytics for each application
Covers advanced problems and solutions of smart grids using advance data analytic techniques

Produktinformation

Utgivningsdatum:2021-03-01
Mått:152 x 229 x 14 mm
Vikt:520 g
Format:Häftad
Språk:Engelska
Antal sidor:268
Förlag:Elsevier Science
ISBN:9780323855105

Utforska kategorier

Energiteknik inom Naturvetenskap och teknik

Mer om författaren

Hasmat Malik is a Senior Lecturer in the Department of Electrical Power Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia. His research interests include artificial intelligence, machine learning, and big-data analytics applied to renewable energy, smart building automation, condition monitoring, and online fault detection and diagnosis (FDD).Dr Nuzhat Fatema has 10 years of experience in Intelligent data analytics using AI & Machine learning for hospital and health care management. Dr. Fatema is the founder of the Intelligent-Prognostic (iPrognostic) Pvt. Ltd. Her area of interest is AI, ML and intelligent data analytics application in healthcare, monitoring, prediction, forecasting, detection and diagnosis to optimize decision-making in diagnosis, management and industry care. Atif Iqbal, is a Professor in Electrical Engineering, Qatar University. He publishes widely in power electronics, variable speed drives and renewable energy sources. Dr. Iqbal has co-authored more than 400 research papers and two books. His principal area of research interest is smart grids, complex energy transitions, active distribution networks, electric vehicles drivetrains, sustainable development and energy security, and distributed energy generation.

Innehållsförteckning

1. Advances in Machine Learning and Data AnalyticsPART A: Intelligent Data Analytics for Classification in Smart Grid2. Intelligent Data Analytics for PV Fault diagnosis Using Deep Convolutional Neural Network (ConvNet/CNN)3. Intelligent Data Analytics for Power Transformer Health Monitoring Using Modified Fuzzy Q Learning (MFQL)4. Intelligent Data Analytics for Induction Motor Using Gene Expression Programming (GEP)5. Intelligent Data Analytics for Power Quality Disturbance Analysis Using Multi-Class ELM6. Intelligent Data Analytics for Transmission Line Fault Diagnosis Using EEMD Based Multiclass SVM and PSVMPART B: Intelligent Data Analytics for Forecasting in Smart Grid7. Intelligent Data Analytics for Global Solar Radiation Forecasting for Solar Power Production Using Deep Learning Neural Network (DLNN)8. Intelligent Data Analytics for Wind Speed Forecasting for Wind Power Production Using Long Short-Term memory (LSTM) Network9. Intelligent Data Analytics for Time-Series Load Forecasting Using Fuzzy Reinforcement Learning (FRL)10. Intelligent Data Analytics for Battery Charging/Discharging Forecasting Using Semi-supervised and Unsupervised Extreme Learning Machines