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Algorithms for Intelligent Systems

Nature Inspired Optimization for Electrical Power System

Editors: Pandit, Manjaree, Dubey, Hari Mohan, Bansal, Jagdish Chand (Eds.)

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  • Presents a wide range of optimization methods and their applications  
  • Discusses the merits of nature inspired optimization algorithms compared to traditional optimization methods
  • Offers a valuable reference guide for researchers in their advanced studies
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About this book

This book presents a wide range of optimization methods and their applications to various electrical power system problems such as economical load dispatch, demand supply management in microgrids, levelized energy pricing, load frequency control and congestion management, and reactive power management in radial distribution systems. Problems related to electrical power systems are often highly complex due to the massive dimensions, nonlinearity, non-convexity and discontinuity associated with objective functions. These systems also have a large number of equality and inequality constraints, which give rise to optimization problems that are difficult to solve using classical numerical methods. In this regard, nature inspired optimization algorithms offer an effective alternative, due to their ease of use, population-based parallel search mechanism, non-dependence on the nature of the problem, and ability to accommodate non-differentiable, non-convex problems. The analytical model of nature inspired techniques mimics the natural behaviors and intelligence of life forms. These techniques are mainly based on evolution, swarm intelligence, ecology, human intelligence and physical science.

 


About the authors

Prof. Manjaree Pandit received her M.Tech. degree in Electrical Engineering from Maulana Azad College of Technology, Bhopal, India, in 1989 and her Ph.D. degree from Jiwaji University Gwalior, India, in 2001. She is currently working as a Professor and Dean of Academics at the Department of Electrical Engineering, M.I.T.S., Gwalior, India. She is a senior member of the IEEE, a reviewer for several journals, and has published more than 60 papers in respected international journals. Her research interests include the integration of hybrid renewable energy sources with power grids, nature inspired algorithms, ANN and fuzzy neural network applications to electrical power systems.

Dr. Hari Mohan Dubey is an Associate Professor at Madhav Institute of Technology & Science, Gwalior, India. Dr. Dubey received his Ph.D. degree in Electrical Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India. He is associated with various SCI journals as reviewer, and has published more than 70 research papers in various international journals/conference proceedings. His main research interests are in bio-inspired algorithms and their applications to electrical engineering, particularly, power system planning and operation with the integration of renewable energy sources.

Dr. Jagdish Chand Bansal is an Associate Professor at South Asian University New Delhi and Visiting Faculty at the Department of Maths and Computer Science, Liverpool Hope University, UK. Dr. Bansal received his Ph.D. in Mathematics from the IIT Roorkee. Before joining SAU New Delhi, he worked as an Assistant Professor at ABV-Indian Institute of Information Technology and Management, Gwalior, and at BITS Pilani. He is the series editor of Algorithms for Intelligent Systems (AIS), published by Springer; the Editor-in-Chief of International Journal of Swarm Intelligence (IJSI), published by Inderscience; and an Associate Editor of IEEE ACCESS, published by the IEEE. He is the general secretary of the Soft Computing Research Society (SCRS). His main research interests are in swarm intelligence and nature inspired optimization techniques. Recently, he proposed a fission–fusion social structure-based optimization algorithm, Spider Monkey Optimization (SMO), which is currently being applied to various problems in the engineering domain. He has published more than 60 research papers in various international journals/conference proceedings.

 


Table of contents (9 chapters)

Table of contents (9 chapters)
  • Teaching-Learning-Based Optimization for Static and Dynamic Load Dispatch

    Pages 1-12

    Sharma, Kavita (et al.)

  • Application of Elitist Teacher–Learner-Based Optimization Algorithm for Congestion Management

    Pages 13-29

    Parmar, Rupali (et al.)

  • PSO-Based Optimization of Levelized Cost of Energy for Hybrid Renewable Energy System

    Pages 31-42

    Singh, Poonam (et al.)

  • PSO-Based PID Controller Designing for LFC of Single Area Electrical Power Network

    Pages 43-54

    Paliwal, Nikhil (et al.)

  • Combined Economic Emission Dispatch of Hybrid Thermal PV System Using Artificial Bee Colony Optimization

    Pages 55-67

    Dubey, Salil Madhav (et al.)

Buy this book

eBook $119.00
price for USA in USD (gross)
  • ISBN 978-981-15-4004-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $159.99
price for USA in USD
  • ISBN 978-981-15-4003-5
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Nature Inspired Optimization for Electrical Power System
Editors
  • Manjaree Pandit
  • Hari Mohan Dubey
  • Jagdish Chand Bansal
Series Title
Algorithms for Intelligent Systems
Copyright
2020
Publisher
Springer Singapore
Copyright Holder
The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-15-4004-2
DOI
10.1007/978-981-15-4004-2
Hardcover ISBN
978-981-15-4003-5
Series ISSN
2524-7565
Edition Number
1
Number of Pages
XIV, 129
Number of Illustrations
14 b/w illustrations, 35 illustrations in colour
Topics

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