@misc{SyedMachadoSchiffer, author = {Syed, Wasif H. and Machado, Juan E. and Schiffer, Johannes}, title = {Distributed Adaptive Control for a DC Power Distribution System of a Series-Hybrid-Electric Propulsion System of a Commuter Aircraft}, series = {2024 American Control Conference (ACC)}, journal = {2024 American Control Conference (ACC)}, publisher = {IEEE}, doi = {10.23919/ACC60939.2024.10644618}, pages = {2598 -- 2603}, language = {en} } @misc{MathewRuedaEscobedoSchiffer, author = {Mathew, Riya and Rueda-Escobedo, Juan G. and Schiffer, Johannes}, title = {Robust Design of Phase-Locked Loops in Grid-Connected Power Converters}, series = {European Journal of Control}, journal = {European Journal of Control}, edition = {Volume 80}, doi = {10.1016/j.ejcon.2024.101055}, pages = {6}, language = {en} } @misc{LorenzMeyerWuerfelSchiffer, author = {Lorenz-Meyer, Nicolai and W{\"u}rfel, Hans and Schiffer, Johannes}, title = {Consensus + Innovations approach for online distributed multi-area inertia estimation}, series = {2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)}, journal = {2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)}, publisher = {IEEE}, address = {New York}, doi = {10.1109/ISGTEUROPE62998.2024.10863379}, pages = {1 -- 6}, abstract = {The reduction of overall system inertia in modern power systems due to the increasing deployment of distributed energy resources is generally recognized as a major issue for system stability. Consequently, real-time monitoring of system inertia is critical to ensure a reliable and cost-effective system operation. Large-scale power systems are typically managed by multiple transmission system operators, making it difficult to have a central entity with access to global measurement data, which is usually required for estimating the overall system inertia. We address this problem by proposing a fully distributed inertia estimation algorithm with rigorous analytical convergence guarantees. This method requires only peer-to-peer sharing of local parameter estimates between neighboring control areas, eliminating the need for a centralized collection of real-time measurements. We robustify the algorithm in the presence of typical power system disturbances and demonstrate its performance in simulations based on the well-known New England IEEE 39-bus system.}, language = {en} } @misc{MercadoUribeMendozaAvilaEfimovetal., author = {Mercado-Uribe, Angel and Mendoza-{\´A}vila, Jes{\´u}s and Efimov, Denis and Schiffer, Johannes}, title = {Sufficient conditions for global boundedness of solutions for two coupled synchronverters}, series = {2024 IEEE 63rd Conference on Decision and Control (CDC)}, journal = {2024 IEEE 63rd Conference on Decision and Control (CDC)}, publisher = {IEEE}, address = {New York}, doi = {10.1109/CDC56724.2024.10886006}, pages = {2785 -- 2790}, abstract = {This paper analyzes two synchronverters connected in parallel to a common capacitive-resistive load through resistive-inductive power lines. This system is conceptualized as a microgrid with two renewable energy sources controlled using the synchronverter algorithm. It is modeled as an interconnection of three port-Hamiltonian systems, and the dq-coordinates model is derived by averaging the frequencies. Applying the recent Leonov function theory, sufficient conditions to guarantee the global boundedness of the whole system's trajectories are provided. This is necessary to reach the global synchronization of microgrids. Additionally, a numerical example illustrates the potential resonance behavior of the microgrid.}, language = {en} } @book{ParisioSchifferHans, author = {Parisio, Alessandra and Schiffer, Johannes and Hans, Christian A.}, title = {System level control and optimisation of microgrids}, editor = {Parisio, Alessandra and Schiffer, Johannes and Hans, Christian A.}, publisher = {The Institution of Engineering and Technology}, address = {London}, isbn = {9781785618758}, doi = {10.1049/PBPO149E}, pages = {300}, abstract = {Microgrids are essential components of next-generation energy grids. A microgrid is a local, integrated energy system comprising interconnected loads and distributed energy resources; they can represent urban or rural districts, islands or local communities. Microgrids can operate in parallel with the main grid or independently in an intentional island mode. When on-site generation is included, intelligent buildings can also function as microgrids. Efficient optimization and control algorithms are crucial for ensuring optimal microgrid performance, making them a continuous focus of research and development in the field of power systems. The next-generation energy grid and urban environment need to be smart and sustainable to deal with the growing energy demand and achieve environmental goals. In this context, the role of local energy systems at the distribution level, which can represent urban or rural districts, islands or local communities, is crucial. System Level Control and Optimisation of Microgrids offers a comprehensive and systematic review of developments in this field. The chapters cover topics such as modelling of integrated energy systems and district heating systems, dynamics and control of grid-connected microgrids, frequency regulation, distributed optimization for energy grids, integration of distributed energy resources, transactive energy management for multi-energy microgrids, and laboratory validation. Real-world examples are provided through case studies based on the EUREF Energy Workshop and fog computing-based decentralized energy management. This book presents a wide range of perspectives from academia and industry on the challenges and solutions in microgrid optimization and control. It serves as a thorough resource for engineers and academics in the control and power systems fields, as well as for graduate students in related disciplines. Advanced control and optimization techniques for microgrids are discussed in depth, with examples and case studies demonstrating their practical application in shaping the future of energy systems.}, language = {en} } @misc{KrenzlinHagemannGernandtetal., author = {Krenzlin, Franziska and Hagemann, Willem and Gernandt, Hannes and Schiffer, Johannes}, title = {Data-driven modeling of borehole thermal energy storage (BTES) for operational optimization of renewable heat production systems}, series = {37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024)}, journal = {37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024)}, publisher = {ECOS 2024}, address = {Zografos, Greece}, doi = {10.52202/077185-0157}, pages = {1831 -- 1841}, abstract = {The utilization of underground thermal energy storage (UTES) systems, such as borehole thermal energy storage (BTES) systems plays a crucial role in the decarbonization of district heating. To ensure high performance and operation efficiency under the condition of a robust system operation, heat supply systems require advanced control and operation strategies including the operation of the thermal storage systems. The focus of our operational optimization lies on the heat production side, comprising a BTES and diverse heat sources, buffer storage systems and heat pumps. We utilize a nonlinear model of the heating network that explicitly integrates mass flows and temperatures instead of solely relying on heat flow considerations. The advantage of this more detailed consideration is that realistic constraints on temperatures and mass flows can be easily incorporated into the model. A major challenge in such realistic modeling is the correct representation of the temperature dynamics of thermal storage components, especially when the storage parameters are unknown and only limited input-output data are available. In this work, we propose a novel method leading to a reduced surrogate model of the BTES temperature dynamics that can be directly included in the optimization or control algorithms. The resulting data-based surrogate model captures the fundamental dynamics while being deployable to operational optimization and system control algorithms. In particular, we employ a Python-based operational optimization process of a theoretical system setup using Pyomo. In conclusion, the presented storage modeling approach is a first step towards a broad variety of system configurations including different UTES types.}, language = {en} } @incollection{SchifferSimpsonPorcoParisio, author = {Schiffer, Johannes and Simpson-Porco, John W. and Parisio, Alessandra}, title = {Control in Low-Inertia Power and Integrated Energy Systems}, series = {Reference Module in Materials Science and Materials Engineering}, booktitle = {Reference Module in Materials Science and Materials Engineering}, publisher = {Elsevier}, isbn = {9780128035818}, doi = {10.1016/B978-0-443-14081-5.00068-4}, pages = {20}, abstract = {Driven by global efforts to mitigate the climate crisis, power systems are undergoing unprecedented changes. An important factor in this energy transition is the replacement of large-scale conventional fossil fuel-driven synchronous generators by renewable-driven inverter-based generation. This substitution entails a large reduction of the overall power system inertia, leading to faster and more volatile dynamics. Such power systems are therefore termed low-inertia power systems. In the present chapter, key properties and aspects for modeling, control and operation of this kind of future power systems are introduced, with a focus on automatic frequency control, dynamic state estimation and grid-synchronization of inverter-based resources. As moving beyond decarbonization of only the electricity sector is viewed as essential for the successful development of climate-neutral societies, the exposition is complemented by identifying current trends in integrated energy systems. These novel energy system architectures are characterized by integration of diverse energy vectors, such as electricity, heat, transportation, and (hydrogen) gas, in a holistic manner. Overall, the chapter places a control-theoretic lens on these societal-scale sustainability challenges.}, language = {en} } @misc{JaramilloCajicaSchiffer, author = {Jaramillo-Cajica, Ismael and Schiffer, Johannes}, title = {A dwell-time approach for decentralized grid-aware operation of islanded DC microgrids}, series = {Automatica}, volume = {160}, journal = {Automatica}, publisher = {Elsevier BV}, issn = {0005-1098}, doi = {10.1016/j.automatica.2023.111461}, pages = {1 -- 11}, abstract = {In islanded microgrid (MG) applications, renewable-based distributed generation units (DGUs) are commonly operated in grid-feeding mode, while storage-based DGUs assume the grid-forming responsibilities. This results in limited controllable power reserves, which may pose severe threats to the overall system stability. Motivated by this, we consider the problem of designing a more flexible grid-aware control scheme for enlarging the actuation power of a DC MG. That is, existing DGUs are able to adopt different operation modes by switching among two decentralized passivity-based subsystem control laws in dependency of their node status. To this purpose, we design a time- and state-dependent switching logic that coordinates the DGU mode transitions and ensures that the closed-loop interconnected MG possesses a unique equilibrium point. Then, we derive sufficient tuning conditions on the control parameters that ensure global exponential stability of this equilibrium by adopting a multiple Lyapunov functions approach that exploits the passive interconnection properties of the MG together with dwell-time methods for switched systems. The advantageous performance of the proposed strategy is illustrated via a numerical example.}, language = {en} } @misc{ReimannRoseKuepperetal., author = {Reimann, Ansgar and Rose, Max and K{\"u}pper, Jan and Schiffer, Johannes}, title = {Nonlinear system identification and predictive control for waste heat recovery with heat pumps}, series = {IFAC-PapersOnLine}, volume = {58}, journal = {IFAC-PapersOnLine}, number = {2}, publisher = {Elsevier BV}, issn = {2405-8963}, doi = {10.1016/j.ifacol.2024.07.103}, pages = {130 -- 135}, abstract = {The utilization of low-temperature waste heat, particularly from electrolyzers, in district heating networks via heat pumps presents a promising approach to accelerate the decarbonization of the heat sector. However, managing the electrolyzer's specific temperature requirements and dynamic waste heat output, while simultaneously meeting the district heating network's variable temperature demands, requires the implementation of an advanced control system for the heat pump cycle. For this, model predictive control is a promising approach since it not only ensures the satisfaction of constraints, but also facilitates a direct optimization of the heat pump's operational efficiency. Nevertheless, model predictive control requires a dynamic heat pump model. In this context, first-principles models are often used. However, they are very complex and difficult to parameterize for real heat pumps. Therefore, in the present paper, a data-based system identification is carried out to obtain a reduced-order heat pump model from a high-fidelity first-principles simulation model. Based on the identified model, a predictive controller is implemented. The effectiveness of the obtained controller for operating the first-principles model is demonstrated in a numerical case study.}, language = {en} } @misc{HerrmannPlietzschRoseetal., author = {Herrmann, Ulrike and Plietzsch, Anton and Rose, Max and Gernandt, Hannes and Schiffer, Johannes}, title = {A predictive operation management scheme for hydrogen networks based on the method of characteristics}, series = {2024 European Control Conference (ECC)}, journal = {2024 European Control Conference (ECC)}, publisher = {IEEE}, doi = {10.23919/ECC64448.2024.10591107}, pages = {1084 -- 1089}, abstract = {As future hydrogen networks will be strongly linked to the electricity system via electrolysers and hydrogen power plants, challenges will arise for their operation. A suitable response to phenomena, such as rapidly changing boundary conditions and unbalanced supply and demand, requires the implementation of operational concepts based on transient pipe models. The transient pipe flow can be described by the isothermal Euler equations, which we discretize using an explicit Method Of Characteristics. Based on this, we develop a nonlinear space-time discretized network model that incorporates various other components, including hydrogen storage facilities, active elements such as valves and compressor stations, as well as electrolyzers and fuel cells. This network model serves as the foundation for the development of a tailored economic model predictive control algorithm designed for fast timescales. The algorithm enables controlled pressure changes within specified bounds in response to changes in supply and demand while simultaneously minimizing fast pressure fluctuations in the pipelines. Through a detailed case study, we demonstrate the algorithm's proficiency in addressing these transient operation challenges.}, language = {en} } @misc{TexisLoaizaZuritaBustamanteSchiffer, author = {Texis-Loaiza, Oscar and Zurita-Bustamante, Eric W. and Schiffer, Johannes}, title = {A BL-homogeneous observer for inter-turn short-circuit fault detection in PMSMs}, series = {2024 IEEE Conference on Control Technology and Applications (CCTA)}, journal = {2024 IEEE Conference on Control Technology and Applications (CCTA)}, publisher = {IEEE}, doi = {10.1109/CCTA60707.2024.10666505}, pages = {248 -- 253}, abstract = {Electric vehicle propulsion systems heavily depend on the reliable operation of permanent magnet synchronous motors (PMSMs). However, the susceptibility of PMSMs to electrical faults, particularly inter-turn short circuit (ITSC) faults, poses a significant threat to their overall reliability. With the purpose of enabling an immanent fault detection, we design a fault detection observer using the recently developed bi-limit-homogeneous sliding mode observer (BL-H SMO) technique. The BL-H SMO has the ability to offer zero error estimates within finite or fixed-time intervals even in the presence of unknown inputs, which is a distinctive advantage enhancing its efficacy in fault detection for PMSMs compared to standard Kalman filter schemes. These advantages are illustrated via a simulation study that validates and compares the proposed BL-H SMO's performance with that of a Kalman filter.}, language = {en} }