This book offers a broad, in-depth overview that reflects the requirements, possibilities and limits of mathematical optimization and, especially, stochastic optimization in the energy industry.

Power and Energy Engineering are important and pressing topics globally, covering issues such as shifting paradigms of energy generation and consumption, intelligent grids, green energy and environmental protection. The 11th Asia-Pacific Power and Energy Engineering Conference (APPEEC 2019) was held in Xiamen, China from April 19 to 21, 2019. APPEEC has been an annual conference since 2009 and has been successfully held in Wuhan (2009 & 2011), Chengdu (2010 & 2017), Shanghai (2012 & 2014), Beijing (2013 & 2015), Suzhou (2016) and Guilin (2018), China. The objective of APPEEC 2019 was to provide scientific and professional interactions for the advancement of the fields of power and energy engineering. APPEEC 2019 facilitated the exchange of insights and innovations between industry and academia. A group of excellent speakers have delivered keynote speeches on emerging technologies in the field of power and energy engineering. Attendees were given the opportunity to give oral and poster presentations and to interface with invited experts.

AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties. ​Covers renewable energy sector fundamentals; Explains the application of big data in distributed energy domains; Discusses AI and IoT prediction methods and models.

Intelligent systems, powered by artificial intelligence (AI) and machine learning, offer transformative benefits across diverse sectors, from healthcare and finance to manufacturing and agriculture. By refining these systems to be more adaptable, scalable, and informative, industries can solve complex business problems and streamline operations. Effective research into technical challenges across intelligent system application is necessary to prioritize their development and impact in industries, such as crop analysis, disease diagnosis, or traffic management. Optimizing Intelligent Systems for Cross-Industry Application explores the challenges and opportunities associated with intelligent technology integration in various sectors, including agriculture, medicine, healthcare, computer engineering, business management, and environmental research. It presents solutions for the effective use of intelligent systems within their respective industries. This book covers topics such as human resources, smart cities, and crop productivity, and is a useful resource for computer engineers, agriculturalists, business owners, healthcare professionals, environmentalists, researchers, scientists, and academicians.

Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid is a comprehensive guide that delves into the intricate world of renewable energy integration and its impact on electrical systems. With the current global energy crisis and the urgent need to address climate change, this book explores the latest advancements and research surrounding optimization techniques in the realm of renewable energy. This book has a focus on nature-inspired and meta-heuristic optimization methods, and it demonstrates how these techniques have revolutionized renewable energy problem-solving and their application in real-world scenarios. It examines the challenges and opportunities in achieving a larger utilization of renewable energy sources to reduce carbon emissions and air pollutants while meeting renewable portfolio standards and enhancing energy efficiency. This book serves as a valuable resource for researchers, academicians, industry delegates, scientists, and final-year master's degree students. It covers a wide range of topics, including novel power generation technology, advanced energy conversion systems, low-carbon technology in power generation and smart grids, AI-based control strategies, data analytics, electrified transportation infrastructure, and grid-interactive building infrastructure.

Selected, peer reviewed papers from the 2014 International Conference on Energy Research and Power Engineering (ERPE'14), May 17-18, 2014, Dalian, China

Developing a system that can cope with variations of system or control parameters, measurement uncertainty, and complex, multi-objective optimization criteria is a frequent problem in engineering systems design. The need for a priori knowledge and the inability to learn from past experience make the design of robust, adaptive, and stable systems a difficult task. Innovation in Power, Control, and Optimization: Emerging Energy Technologies unites research on the development of techniques and methodologies to improve the performance of power systems, energy planning and environments, controllers and robotics, operation research, and modern artificial computational intelligent techniques. Containing research on power engineering, control systems, and methods of optimization, this book is written for professionals who want to improve their understanding of strategic developments in the area of power, control, and optimization.

Comprehensive Energy Systems, Seven Volume Set provides a unified source of information covering the entire spectrum of energy, one of the most significant issues humanity has to face. This comprehensive book describes traditional and novel energy systems, from single generation to multi-generation, also covering theory and applications. In addition, it also presents high-level coverage on energy policies, strategies, environmental impacts and sustainable development. No other published work covers such breadth of topics in similar depth. High-level sections include Energy Fundamentals, Energy Materials, Energy Production, Energy Conversion, and Energy Management. Offers the most comprehensive resource available on the topic of energy systems Presents an authoritative resource authored and edited by leading experts in the field Consolidates information currently scattered in publications from different research fields (engineering as well as physics, chemistry, environmental sciences and economics), thus ensuring a common standard and language

In the era of Industry 5.0, the world faces a critical juncture where technological advancement collides with escalating socio-environmental challenges. Climate change, energy consumption, and threats to public health are exacerbated by the rapid embrace of Industry 4.0 technologies. As businesses pursue efficiency, the compromise on human and social sustainability becomes inevitable. The need for a holistic approach to sustainable development is urgent, where economic growth aligns seamlessly with environmental, social, and human well-being. Eco-Innovation and Sustainable Development in Industry 5.0 serves as a guide in the pursuit of sustainable development within Industry 5.0. This book dissects the intricate challenges posed by socio-environmental issues and seamlessly offers a multidisciplinary approach to achieving sustainable development goals. The detrimental impact of Industry 4.0 on sustainable development necessitates the paradigm shift proposed within the book. Economic pursuits can no longer overshadow the crucial pillars of human, social, and environmental sustainability. The delicate balance required for a sustainable future is at risk, demanding a multidisciplinary approach to reconcile these seemingly conflicting objectives. This book is a call to action, to bridge the knowledge gap and provide tangible solutions for achieving sustainability in Industry 5.0.

Integration of AI-Based Manufacturing and Industrial Engineering Systems with the Internet of Things describes how AI techniques, such as deep learning, cognitive computing, and Machine Learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments. The potential benefits and challenges associated with the integration of AI and IoT in industrial environments are explored throughout the book as the authors delve into various aspects of the integration process. The role of IoT-enabled sensors, actuators, and smart devices in capturing real-time data from manufacturing processes, supply chains, and equipment is discussed along with how data can be processed and analyzed using AI algorithms to derive actionable insights, optimize production, improve quality control, and enhance overall operational efficiency. A valuable resource for researchers, practitioners, and professionals involved in the fields of AI, IoT, manufacturing systems, and industrial engineering, and combines theoretical foundations, practical applications, and case studies.