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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.
This book presents a comprehensive definition of smart grids and their benefits, and compares smart and traditional grids. It also introduces a design methodology for stand-alone hybrid renewable energy system with and without applying the smart grid concepts for comparison purposes. It discusses using renewable energy power plants to feed loads in remote areas as well as in central power plants connected to electric utilities. Smart grid concepts used in the design of the hybrid renewable power systems can reduce the size of components, which can be translated to a reduction in the cost of generated energy. The proposed hybrid renewable energy system includes wind, photovoltaic, battery, and diesel, and is used initially to feed certain loads, covering the load required completely. The book introduces a novel methodology taking the smart grid concept into account by dividing the loads into high and low priority parts. The high priority part should be supplied at any generated conditions. However, the low priority loads can be shifted to the time when the generated energy from renewable energy sources is greater than the high priority loads requirements. The results show that the use of this smart grid concept reduces the component size and the cost of generated energy compared to that without dividing the loads. The book also describes the use of smart optimization techniques like particle swarm optimization (PSO) and genetic algorithm (GA) to optimally design the hybrid renewable energy system. This book provides an excellent background to renewable energy sources, optimal sizing and locating of hybrid renewable energy sources, the best optimization methodologies for sizing and designing the components of hybrid renewable energy systems, and offers insights into using smart grid concepts in the system’s design and sizing. It also helps readers understand the dispatch methodology and how to connect the system’s different components, their modeling, and the cost analysis of the system.
This book focuses on the interaction between different energy vectors, that is, between electrical, thermal, gas, and transportation systems, with the purpose of optimizing the planning and operation of future energy systems. More and more renewable energy is integrated into the electrical system, and to optimize its usage and ensure that its full production can be hosted and utilized, the power system has to be controlled in a more flexible manner. In order not to overload the electrical distribution grids, the new large loads have to be controlled using demand response, perchance through a hierarchical control set-up where some controls are dependent on price signals from the spot and balancing markets. In addition, by performing local real-time control and coordination based on local voltage or system frequency measurements, the grid hosting limits are not violated.
This three-volume set LNCS 13338-13340 constitutes the thoroughly refereed proceedings of the 8th International Conference on Artificial Intelligence and Security, ICAIS 2022, which was held in Qinghai, China, in July 2022. The total of 166 papers included in the 3 volumes were carefully reviewed and selected from 1124 submissions. The papers present research, development, and applications in the fields of artificial intelligence and information security
Optimal Operation of Integrated Multi-Energy Systems Under Uncertainty discusses core concepts, advanced modeling and key operation strategies for integrated multi-energy systems geared for use in optimal operation. The book particularly focuses on reviewing novel operating strategies supported by relevant code in MATLAB and GAMS. It covers foundational concepts, key challenges and opportunities in operational implementation, followed by discussions of conventional approaches to modeling electricity, heat and gas networks. This modeling is the base for more detailed operation strategies for optimal operation of integrated multi-energy systems under uncertainty covered in the latter part of the work. - Reviews advanced modeling approaches relevant to the integration of electricity, heat and gas systems in operation studies - Covers stochastic and robust optimal operation of integrated multi-energy systems - Evaluates MPC based, real-time dispatch of integrated multi-energy systems - Considers uncertainty modeling for stochastic and robust optimization - Assesses optimal operation and real-time dispatch for multi-energy building complexes
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
Focusing on energy, transportation, information, and economic networks and flows, Integration of Energy, Information,Transportation and Humanity uniquely examines the interconnection, interaction, and integration across these multiple sectors. It helps readers understand the correlation of energy, transportation, and information via the integration of humanity world, cyber world and physical world. It clearly explains the objectives of the integration of energy network, transportation network, information network, humanity network, as well as the integration of energy flow, information flow, material flow and value flow (4N4F); the philosophy, science, and engineering of the integration of 4N4F; the mechanism, keys and benefits of the integration of 4N4F; the carriers of the integration of 4N4F; and the framework of the integration of 4N4F. - Synthesizes the newest developments in digital technologies and digital economy - Includes case studies and examples that illustrate the application of methodologies and technologies employed - Useful for both theoretically and technically oriented researchers
The editors of this Special Issue titled “Intelligent Control in Energy Systems” have attempted to create a book containing original technical articles addressing various elements of intelligent control in energy systems. In response to our call for papers, we received 60 submissions. Of those submissions, 27 were published and 33 were rejected. In this book, we offer the 27 accepted technical articles as well as one editorial. Authors from 15 countries (China, Netherlands, Spain, Tunisia, United Sates of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and the Czech Republic) elaborate on several aspects of intelligent control in energy systems. The book covers a broad range of topics including fuzzy PID in automotive fuel cell and MPPT tracking, neural networks for fuel cell control and dynamic optimization of energy management, adaptive control on power systems, hierarchical Petri Nets in microgrid management, model predictive control for electric vehicle battery and frequency regulation in HVAC systems, deep learning for power consumption forecasting, decision trees for wind systems, risk analysis for demand side management, finite state automata for HVAC control, robust μ-synthesis for microgrids, and neuro-fuzzy systems in energy storage.