Data-Driven Energy Management and Tariff Optimization in Power Systems
eBook - ePub

Data-Driven Energy Management and Tariff Optimization in Power Systems

Shaping the Future of Electricity Distribution through Analytics

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Data-Driven Energy Management and Tariff Optimization in Power Systems

Shaping the Future of Electricity Distribution through Analytics

About this book

Presents a comprehensive guide to transforming power systems through data

Data-Driven Energy Management and Tariff Optimization in Power Systems offers an authoritative examination of how data science is reshaping the energy landscape. As the electricity sector grapples with increasing complexity, this timely volume responds to a growing demand for adaptive strategies that enable accurate forecasting, intelligent tariff design, and optimized resource allocation, underpinned by advanced analytics and machine learning.

Drawing on global expertise and real-world case studies, the book bridges the theoretical and practical dimensions of energy systems management, providing deep insight into how data collected from smart meters, SCADA systems, and IoT devices can be mined for predictive modeling, demand response, and peak load management. The book's accessible structure and didactic approach make it suitable for a wide readership, while its breadth of topics ensures relevance across the spectrum of energy challenges.

Integrating rigorous analysis with application-oriented strategies, this book:

  • Presents advanced techniques in machine learning, predictive modeling, and pattern recognition tailored to energy management and tariff design
  • Provides accessible explanations of complex algorithms through a didactic and visual teaching style, including informative tables and illustrations
  • Highlights tools for grid stability, demand forecasting, and peak load management using high-resolution energy data
  • Addresses the integration of renewable energy sources into existing infrastructures through data-driven optimization

Designed for a broad audience, Data-Driven Energy Management and Tariff Optimization in Power Systems is ideal for upper-level undergraduate and graduate courses in energy management, power systems analytics, and smart grids as part of electrical engineering or energy policy programs. It is also an essential reference for power system engineers, energy analysts, researchers, and policymakers involved in grid planning and optimization.

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Yes, you can access Data-Driven Energy Management and Tariff Optimization in Power Systems by Hamidreza Arasteh,Pierluigi Siano,Niki Moslemi,Josep M. Guerrero in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Data Modelling & Design. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Table of Contents
  3. Title Page
  4. Copyright
  5. Dedication
  6. About the Editors
  7. List of Contributors
  8. Preface
  9. 1 Fundamentals of Power System Data and Analytics
  10. 2 Advanced Predictive Modeling for Energy Consumption and Demand
  11. 3 Demand Response and Customer-Centric Energy Management
  12. 4 Applications of Data Mining in Industrial Tariff Design and Energy Management
  13. 5 Data-Driven Tariff Design for Equitable Energy Distribution
  14. 6 Applying Artificial Intelligence to Improve the Penetration of Renewable Energy in Power Systems
  15. 7 Machine Learning-Based Solutions for Renewable Energy Integration
  16. 8 Application of Artificial Neural Networks in Solar Photovoltaic Power Forecasting
  17. 9 Power System Resilience Evaluation
  18. 10 Nonintrusive Load Monitoring in Smart Grids Using Deep Learning Approach
  19. 11 Power System Cyber-Physical Security and Resiliency Based on Data-Driven Methods
  20. 12 Application of Artificial Intelligence in Undervoltage Load Shedding in Digitalized Power Systems
  21. Index
  22. End User License Agreement