Der Entwurf von Ansätzen zur marktbasierten Betriebsführung zukünftiger Energienetze steht vor der technischen Herausforderung, eine enorme Anzahl von Netzteilnehmern zeitlich und örtlich zu koordinieren, um Erzeugung und Verbrauch auszugleichen und einen sicheren Netzbetrieb zu ermöglichen. Um dieser Herausforderung zu begegnen entstand das Forschungsfeld der Transactive Control Ansätze. In dieser Arbeit wird ein neuer Transactive Control Ansatz für gekoppelte Strom- und Wärmenetze vorgestellt. - The design of approaches for future market-based energy network operation faces the technical challenge of needing to coordinate a vast number of network participants spatially and temporally, in order to balance energy supply and demand, while achieving secure network operation. To meet this challenge, the research field of transactive control emerged. Within this work a new transactive control approach for coupled electric power and district heating networks is presented.

This work focuses on the Limited Information Shared Control and its controller design using potential games. Through the developed systematic controller design, the experiments demonstrate the effectiveness and superiority of this concept compared to traditional manual and non-cooperative control approaches in the application of large vehicle manipulators.

Reinforcement Learning is a promising tool to automate controller tuning. However, significant extensions are required for real-world applications to enable fast and robust learning. This work proposes several additions to the state of the art and proves their capability in a series of real world experiments.

Emerging Transactive Energy Technology for the Future Modern Energy Networks looks at the importance of transactive energy technology in modern multi-carrier energy networks, exploring modeling and optimization and analyzing the necessity of transactive energy technology for future modern energy networks. Along with energy technology, the book covers applications of transactive energy technology, strategies in optimal operation of the hybrid energy networks, reliable and sustainable development of the modern energy networks, and design, integration and operation of a full level of renewable energy resources. This reference is intended for energy, power, mechanical and environmental engineers, researchers and postgraduate students who work in various types of energy systems. - Discusses the application of transactive energy technology in modernizing future energy networks - Investigates the optimal integration of 100% renewable energy resources in modern hybrid energy networks - Provides a holistic, transactive energy-based framework for creating interoperability between multi-carrier energy networks

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.

Explore the prospective developments in energy systems and transportation through an in-depth examination of Distributed Energy Resources and Electric Vehicle: Analysis and Optimisation of Network Operations . This innovative publication explores the realm of renewable energy, electric vehicles, and their in uence on network operations, offering valuable perspectives for readers from diverse disciplines. This extensive publication delves into the complex interplay between distributed energy resources (DERs) and electric vehicles (EVs), as well as their incorporation into established power grids. The subject matter encompasses a diverse array of topics, encompassing the attributes and advantages of distributed energy resources (DERs) and electric vehicles (EVs), obstacles related to grid integration, efficient allocation of resources, and strategies pertaining to demand response. The book offers a comprehensive exploration of system analysis and optimisation techniques, emphasising the effective utilisation of distributed energy resources (DERs) and electric vehicles (EVs) in energy networks. It aims to equip readers with a robust comprehension of strategies to optimise the performance and potential of DERs and EVs in this context. The book focuses on pioneering research and innovative solutions that are at the forefront of enhancing network operations. The authors demonstrate the novelty and applicability of their findings through the examination of real-world case studies and the utilisation of sophisticated mathematical models. This book serves as a highly valuable resource for individuals engaged in research, engineering, policy-making, and industry-related activities who are interested in effectively navigating the dynamic realm of energy systems and transportation. It equips them with the necessary knowledge and insights to make well-informed decisions that contribute to the attainment of a sustainable future.

Optimal Operation of Integrated Energy Systems Under Uncertainties: Distributionally Robust and Stochastic Models discusses new solutions to the rapidly emerging concerns surrounding energy usage and environmental deterioration. Integrated energy systems (IESs) are acknowledged to be a promising approach to increasing the efficiency of energy utilization by exploiting complementary (alternative) energy sources and storages. IESs show favorable performance for improving the penetration of renewable energy sources (RESs) and accelerating low-carbon transition. However, as more renewables penetrate the energy system, their highly uncertain characteristics challenge the system, with significant impacts on safety and economic issues. To this end, this book provides systematic methods to address the aggravating uncertainties in IESs from two aspects: distributionally robust optimization and online operation. - Presents energy scheduling, considering power, gas, and carbon markets concurrently based on distributionally robust optimization methods - Helps readers design day-ahead scheduling schemes, considering both decision-dependent uncertainties and decision-independent uncertainties for IES - Covers online scheduling and energy auctions by stochastic optimization methods - Includes analytic results given to measure the performance gap between real performance and ideal performance