Predictive Modelling for Energy Management and Power Systems Engineering

Ravinesh Deo, Pijush Samui, Sanjiban Sekhar Roy

• Publisher: Elsevier
• Year: 2020
• ISBN:
  9780128177730
• Topic: Technology & Engineering
• Subtopic: Power Resources
• Index: Technology & Engineering

Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets.

• Presents advanced optimization techniques to improve existing energy demand system
• Provides data-analytic models and their practical relevance in proven case studies
• Explores novel developments in machine-learning and artificial intelligence applied in energy management
• Provides modeling theory in an easy-to-read format

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of Contributors
• About the editors
• Foreword
• Preface
• Chapter 1. A Multiobjective optimal VAR dispatch using FACTS devices considering voltage stability and contingency analysis
• Chapter 2. Photovoltaic panels life span increase by control
• Chapter 3. Community-scale rural energy systems: General planning algorithms and methods for developing countries
• Chapter 4. Proven energy storage system applications for power systems stability and transition issues
• Chapter 5. Design and performance of two decomposition paradigms in forecasting daily solar radiation with evolutionary polynomial regression: wavelet transform versus ensemble empirical mode decomposition
• Chapter 6. Development of data-driven models for wind speed forecasting in Australia
• Chapter 7. Hybrid multilayer perceptron-firefly optimizer algorithm for modelling photosynthetic active solar radiation for biofuel energy exploration
• Chapter 8. Predictive modeling of oscillating plasma energy release for clean combustion engines
• Chapter 9. Nowcasting solar irradiance for effective solar power plants operation and smart grid management
• Chapter 10. Short-term electrical energy demand prediction under heat island effects using emotional neural network integrated with genetic algorithm
• Chapter 11. Artificial neural networks and adaptive neuro-fuzzy inference system in energy modeling of agricultural products
• Chapter 12. Support vector machine model for multistep wind speed forecasting
• Chapter 13. MARS model for prediction of short- and long-term global solar radiation
• Chapter 14. Wind speed forecasting in Nepal using self-organizing map-based online sequential extreme learning machine
• Chapter 15. Potential growth in small-scale distributed generation systems in Brazilian capitals
• Chapter 16. Trend of energy consumption in developing nations in the last two decades: a case study from a statistical perspective
• Index