Description

Book Synopsis


Table of Contents
1. Introduction: Artificial intelligence and Smart Power Systems 2. Integrated Architecture of Machine Learning and Smart Power System 3. Challenges and issues in Power Systems 4. Load shedding and related techniques to solve the power crisis 5. ML in distributed energy resources and prosumers market 6. ML-based electricity demand prediction 7. Applying ML to determine the power outage 8. Predictive and Prescriptive analytics for component fault detection 9. Balancing demand and supply of electricity with machine learning 10. Preventive care of grid hardware with anomaly detection 11. AI-based Smart feeder monitoring system 12. Algorithms for buss loss and reliability indices calculations 13. ML-based security solutions to protect smart power systems 14. Cyber-attacks ,security data detection, and critical loads in the power systems 15. Integration of AI/ML into the energy sector: Case Studies

Smart Energy and Electric Power Systems

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    £86.25

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    RRP £115.00 – you save £28.75 (25%)

    Order before 4pm today for delivery by Thu 11 Jun 2026.

    A Paperback by Sanjeevikumar Padmanaban, Padmanaban Sanjeevikumar, Jens Bo Holm-Nielsen

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      View other formats and editions of Smart Energy and Electric Power Systems by Sanjeevikumar Padmanaban

      Publisher: Elsevier Science
      Publication Date: 9/23/2022 12:00:00 AM
      ISBN13: 9780323916646, 978-0323916646
      ISBN10: 0323916643
      Also in:
      Technology, Engineering & Agriculture Electric motors Electrical engineering

      Description

      Book Synopsis


      Table of Contents
      1. Introduction: Artificial intelligence and Smart Power Systems 2. Integrated Architecture of Machine Learning and Smart Power System 3. Challenges and issues in Power Systems 4. Load shedding and related techniques to solve the power crisis 5. ML in distributed energy resources and prosumers market 6. ML-based electricity demand prediction 7. Applying ML to determine the power outage 8. Predictive and Prescriptive analytics for component fault detection 9. Balancing demand and supply of electricity with machine learning 10. Preventive care of grid hardware with anomaly detection 11. AI-based Smart feeder monitoring system 12. Algorithms for buss loss and reliability indices calculations 13. ML-based security solutions to protect smart power systems 14. Cyber-attacks ,security data detection, and critical loads in the power systems 15. Integration of AI/ML into the energy sector: Case Studies

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