Intelligent Integrated Energy Systems

This book presents research results of PowerWeb, TU Delft’s consortium for interdisciplinary research on intelligent, integrated energy systems and their role in markets and institutions. In operation since 2012, it acts as a host and information platform for a growing number of projects, ranging from single PhD student projects up to large integrated and international research programs. The group acts in an inter-faculty fashion and brings together experts from electrical engineering, computer science, mathematics, mechanical engineering, technology and policy management, control engineering, civil engineering, architecture, aerospace engineering, and industrial design. The interdisciplinary projects of PowerWeb are typically associated with either of three problem domains: Grid Technology, Intelligence and Society. PowerWeb is not limited to electricity: it bridges heat, gas, and other types of energy with markets, industrial processes, transport, and the built environment, serving as a singular entry point for industry to the University’s knowledge. Via its Industry Advisory Board, a steady link to business owners, manufacturers, and energy system operators is provided.

INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.

Technologies for Integrated Energy Systems and Networks Explore emerging technologies that will play a central role in humanity’s transition to a low-carbon future In Technologies for Integrated Energy Systems and Networks, a team of distinguished authors delivers a detailed discussion of integrated energy systems and networks, including a comprehensive overview of emerging technologies. The book focuses on the technologies and systems that play a major role in integrated energy systems, like renewable and distributed energy resources, power conversion technologies, hydrogen, storage technologies, electric mobility, zero- and positive-energy buildings, and local energy communities. A one-of-a-kind and holistic treatment of integrated energy systems, this book explores power conversion, including power-to-gas, power-to-liquid, and power- to-heat technologies, as well as other issues of interest to a broad range of students, professionals, and academicians involved in energy transition. It also covers: A thorough introduction to the digitalization of the energy sector and local market development enabling citizen involvement Comprehensive explorations of integrated energy systems as an engine of energy transition Practical discussions of renewable and distributed energy resources for sustainable economic development In-depth examinations of the role of hydrogen in a low-carbon energy future and the storage technologies of different energy carriers Perfect for electrical, construction, power and energy engineers, Technologies for Integrated Energy Systems and Networks will also earn a place in the libraries of electrochemists and environmental consultants.

Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy.The book begins by introducing the intelligent learning approaches, and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. The second section of the book provides detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, and optimization, supported by case studies, figures, schematics, and references.This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence. Explores cutting-edge intelligent techniques and their implications for future energy systems development Opens the door to a range of applications across forecasting, supply and demand, energy management, optimization, and more Includes a range of case studies that provide insights into the challenges and solutions in real-world applications

Distributed Energy Resources in Local Integrated Energy Systems: Optimal Operation and Planning reviews research and policy developments surrounding the optimal operation and planning of DER in the context of local integrated energy systems in the presence of multiple energy carriers, vectors and multi-objective requirements. This assessment is carried out by analyzing impacts and benefits at local levels, and in distribution networks and larger systems. These frameworks represent valid tools to provide support in the decision-making process for DER operation and planning. Uncertainties of RES generation and loads in optimal DER scheduling are addressed, along with energy trading and blockchain technologies. Interactions among various energy carriers in local energy systems are investigated in scalable and flexible optimization models for adaptation to a number of real contexts thanks to the wide variety of generation, conversion and storage technologies considered, the exploitation of demand side flexibility, emerging technologies, and through the general mathematical formulations established. Integrates multi-energy DER, including electrical and thermal distributed generation, demand response, electric vehicles, storage and RES in the context of local integrated energy systems Fosters the integration of DER in the electricity markets through the concepts of DER aggregation Addresses the challenges of emerging paradigms as energy communities and energy blockchain applications in the current and future energy landscape Proposes operation optimization models and methods through multi-objective approaches for fostering short- and long-run sustainability of local energy systems Assesses and models the uncertainties of renewable resources and intermittent loads in the short-term decision-making process for smart decentralized energy systems