Purpose of the Book:

The book serves as a vital resource for understanding and applying operations research and machine intelligence to design, analyze, and optimize sustainable energy systems. It employs renewable energy integration, energy storage optimization, carbon footprint reduction, smart grid systems, and decision-making under uncertainty as its main focus areas. Moreover, the book demonstrates how advanced machine learning methods have changed predictive modeling processes, improved operational efficiency, and helped innovations in energy management.

 

 

The Needs it Will Address:

 

1. Demonstrate the usage of advanced mathematics and computation in solving real-world energy challenges, aiming to render the concept understandable and useful to researchers and industry.
2. Equips with practical strategies for minimising carbon footprints, improving efficiency of energy consumption and containing carbon neutrality by using optimised energy infrastructures.
3. Introduction and systematic review of contemporary energy solutions based on systems of machine intelligence, such as machine learning and nature-inspired algorithms, and their potential to address contemporary sustainability challenges.
4. Equip policymakers’ engineers and researchers with tools methodology to perform energy related analysis for planning allocation balance and sustainable development strategies.
5. It promotes cross-disciplinary collaboration through engineering, computer science, economics and environment science to address the multifaceted challenge of sustainable energy systems.

 

 

Distinctive or Innovative Treatments:

1. The main emphasis is on the integration of operations research techniques and machine intelligence approaches.
2. The main emphasis of this book is on the methodological implications, real-world case studies, and applications that focus on renewable energy systems and approaches utilizing operations research-based machine intelligence techniques.
3. Future-focused perspectives based on intelligent decision-support systems for energy planning.
4. Emphasizes balancing competing priorities such as cost, efficiency, environmental impact, and energy security.
5. Leverages insights from multiple disciplines to provide a holistic view of sustainable energy systems and their optimization.

 

Objective of the Book

 

The primary objective of this book is to provide a comprehensive exploration of how advanced operations research methodologies and machine intelligence techniques can address the critical challenges of achieving a sustainable energy future. The book aims to bridge the gap between theoretical research and practical applications, equipping academics, researchers, and practitioners with innovative tools, methodologies, and insights to optimize renewable energy systems, reduce carbon footprints, and support the global energy transition.

 

Target Audience

The primary audience is the professionals & researchers working in the areas of intelligent techniques and renewable energy. The target audience are the professionals and researchers involved in the specification and application of renewable and alternative energy with the technological aspect for the assessment and development for the same.

 

Reference book for the University and Institutes for their master degree courses and short-term diploma courses related to renewable energy.

 

Post graduate students having the major with renewable energy with sustainability, energy engineering, role of technology in renewable energy, technological applicability and resources in renewable energy, energy future etc. Research scholars working in the same domain.

 

Reference book for the industry for the purpose of understating the technological aspect in renewable energy. R & D Engineers in the same field. Reference book for Government Energy department specially for the counties like USA, China, UK, Germany and India. As according to the current ranking these countries are in top ten list based on their renewable energy power capacity or electricity generation. These countries are also ready for the new adoption with the current technologies.