Subject: Call for Book Chapters – Scopus-Indexed Elsevier Book on Nature-Inspired Optimization Algorithms for Renewable Energy Systems

30 views

Skip to first unread message

Moolchand Sharma

unread,

Feb 26, 2026, 10:53:27 AM (3 days ago) Feb 26

to ranarese...@googlegroups.com

📢 Call for Book Chapters

We are pleased to invite high-quality original book chapter proposals for the upcoming edited volume to be published by Elsevier titled:

Nature-Inspired Optimization Algorithms for Renewable Energy Systems

📖 About the Book

This edited volume aims to bring together cutting-edge research and practical advancements at the intersection of:

Renewable Energy Systems
Computational Intelligence
Nature-Inspired Optimization Techniques

With the rapid global transition toward clean energy adoption and Net-Zero targets, there is an urgent need for intelligent optimization frameworks capable of addressing:

Uncertainty and intermittency
Renewable energy forecasting
Smart grid stability and control
Electric Vehicle (EV) integration (G2V/V2G)
Energy storage management
Cyber-physical and IoT-enabled energy infrastructures

This volume will provide a focused, application-driven resource for researchers, engineers, policymakers, and graduate students working in sustainable and intelligent energy systems.

📌 Indexing Information

📚 The book will be indexed in Scopus after publication.

All accepted and published chapters will be part of a Scopus-indexed volume (subject to publisher indexing policies).

Important Note:
All submissions must be original, unpublished, and not under consideration for any conference, journal, or other book project.

📑 Tentative Table of Contents (TOC)

Nature-Inspired Intelligence – Foundations and Future Prospects
Optimization Trends in Sustainable Energy Systems: Challenges and Opportunities
Smart Grids and Metaheuristic-Based Energy Forecasting Models
Adaptive Load Dispatch and Fault Detection in Renewable Microgrids
Power Electronics Control Using Swarm Intelligence in PV and Wind Systems
Nature-Inspired Optimization for Energy Storage and Electric Vehicle Systems
Renewable Energy Forecasting with Hybrid Metaheuristics
Multi-Objective Optimization in Renewable Energy Systems
Nature-Inspired Algorithms for Grid Stability and Control
Optimization for Energy-Aware IoT and Cyber-Physical Energy Systems
Simulation Platforms and Benchmarking Protocols for Renewable Energy Optimization
The Role of Nature-Inspired Algorithms in Industry 5.0 Energy Systems
Future Research Directions and Cross-Disciplinary Opportunities

🎯 Suggested Topics (but not limited to)

Genetic Algorithms, PSO, ACO, DE, Firefly, Grey Wolf, Bat Algorithms in renewable systems
Smart grid optimization and stability control
Renewable energy forecasting using hybrid AI models
EV charging optimization (G2V/V2G frameworks)
Microgrid energy management and resilience
Energy storage optimization and battery health prediction
AI-driven power electronics control
Multi-objective renewable energy optimization
Edge AI and IoT for sustainable energy systems
Industry 5.0 and intelligent energy infrastructures

👨‍🏫 Editors

Dr. Moolchand Sharma
Assistant Professor, Department of CSE
Maharaja Agrasen Institute of Technology, Delhi, India
Email: mool...@mait.ac.in

Dr. Bhavnesh Kumar
Associate Professor, Electrical Engineering Department
Netaji Subhas University of Technology, New Delhi, India

Prof. Tarik Ahmed Rashid
Professor, Department of Computer Science & Engineering
University of Kurdistan Hewlêr (UKH), Iraq

Dr. Deevyankar Agarwal
Lectures & Program Director (Computer Engineering)
University of Technology and Applied Sciences, Muscat, Oman

📅 Important Dates

Abstract Submission Deadline: April 30, 2026
Full Chapter Submission: July 30, 2026
Final Manuscript Submission: August 20, 2026

📤 Submission Portal

Authors are requested to submit their chapters via:

🔗 https://cmt3.research.microsoft.com/NIORES2026/Submission/Manage

For queries regarding scope, submission guidelines, or suitability of topics, please contact:

📧 Dr. Moolchand Sharma
mool...@mait.ac.in

We look forward to your valuable contributions to make this Scopus-indexed volume a leading scholarly reference in intelligent renewable energy optimization systems.