Multi-Objective Optimization of Industrial Power Generation Systems: Emerging Research and Opportunities

Multi-Objective Optimization of Industrial Power Generation Systems: Emerging Research and Opportunities

Timothy Ganesan (Royal Bank of Canada, Canada)
Release Date: December, 2019|Copyright: © 2020 |Pages: 233
ISBN13: 9781799817109|ISBN10: 1799817105|EISBN13: 9781799817123|DOI: 10.4018/978-1-7998-1710-9

Description

The increased complexity of the economy in recent years has led to the advancement of energy generation systems. Engineers in this industrial sector have been compelled to seek contemporary methods to keep pace with the rapid development of these systems. Computational intelligence has risen as a capable method that can effectively resolve complex scenarios within the power generation sector. In-depth research on the various applications of this technology is lacking, as engineering professionals need up-to-date information on how to successfully utilize computational intelligence in industrial systems.

Multi-Objective Optimization of Industrial Power Generation Systems: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of the application of intelligent optimization techniques within industrial energy systems. Featuring coverage on a broad range of topics such as swarm intelligence, renewable energy, and predictive modeling, this book is ideally designed for industrialists, engineers, industry professionals, researchers, students, and academics seeking current research on computational intelligence frameworks within the power generation sector.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Biofuel Supply Chain
  • Computational Intelligence
  • Distributed Generation
  • Energy Systems
  • Metaheuristics
  • Multi-Objective Optimization
  • Predictive Modeling
  • Renewable Energy
  • Swarm Intelligence
  • Waste Heat Recovery

Table of Contents and List of Contributors

Search this Book:
Reset