TY - GEN A1 - Mercado-Uribe, Angel A1 - Mendoza-Ávila, Jesús A1 - Efimov, Denis A1 - Schiffer, Johannes T1 - A Control Leonov Function Guaranteeing Global ISS of Two Coupled Synchronverters T2 - 62nd IEEE Conference on Decision and Control (CDC), 2023 Y1 - 2023 SN - 979-8-3503-0124-3 SN - 979-8-3503-0123-6 U6 - https://doi.org/10.1109/CDC49753.2023.10383811 SN - 2576-2370 ER - TY - GEN A1 - Jaramillo-Cajica, Ismael A1 - Mercado-Uribe, Angel A1 - Schiffer, Johannes T1 - Coordinated Control of Load Tap Changer Transformers for Voltage Regulation and Voltage Hunting Prevention: A Switched Systems Approach T2 - 62nd IEEE Conference on Decision and Control (CDC), 2023 Y1 - 2023 SN - 979-8-3503-0124-3 SN - 979-8-3503-0123-6 U6 - https://doi.org/10.1109/CDC49753.2023.10383763 SN - 2576-2370 ER - TY - GEN A1 - Mathew, Riya A1 - Rueda-Escobedo, Juan G. A1 - Schiffer, Johannes T1 - Robust Design of Phase-Locked Loops in Grid-Connected Power Converters T2 - European Journal of Control Y1 - 2024 U6 - https://doi.org/10.1016/j.ejcon.2024.101055 ET - Volume 80 ER - TY - GEN A1 - Lorenz-Meyer, Nicolai A1 - Würfel, Hans A1 - Schiffer, Johannes T1 - Consensus + Innovations approach for online distributed multi-area inertia estimation T2 - 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE) N2 - 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. Y1 - 2024 U6 - https://doi.org/10.1109/ISGTEUROPE62998.2024.10863379 SP - 1 EP - 6 PB - IEEE CY - New York ER - TY - GEN A1 - Mercado-Uribe, Angel A1 - Mendoza-Ávila, Jesús A1 - Efimov, Denis A1 - Schiffer, Johannes T1 - Sufficient conditions for global boundedness of solutions for two coupled synchronverters T2 - 2024 IEEE 63rd Conference on Decision and Control (CDC) N2 - 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. Y1 - 2024 U6 - https://doi.org/10.1109/CDC56724.2024.10886006 SP - 2785 EP - 2790 PB - IEEE CY - New York ER - TY - BOOK A1 - Parisio, Alessandra A1 - Schiffer, Johannes A1 - Hans, Christian A. ED - Parisio, Alessandra ED - Schiffer, Johannes ED - Hans, Christian A. T1 - System level control and optimisation of microgrids N2 - 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. Y1 - 2024 SN - 9781785618758 U6 - https://doi.org/10.1049/PBPO149E PB - The Institution of Engineering and Technology CY - London ER - TY - GEN A1 - Krenzlin, Franziska A1 - Hagemann, Willem A1 - Gernandt, Hannes A1 - Schiffer, Johannes T1 - Data-driven modeling of borehole thermal energy storage (BTES) for operational optimization of renewable heat production systems T2 - 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024) N2 - 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. Y1 - 2024 U6 - https://doi.org/10.52202/077185-0157 SP - 1831 EP - 1841 PB - ECOS 2024 CY - Zografos, Greece ER - TY - GEN A1 - Mercado-Uribe, Angel A1 - Mendoza-Avila, Jesus A1 - Efimov, Denis A1 - Schiffer, Johannes T1 - Conditions for global synchronization in networks of heterogeneous Kuramoto oscillators T2 - Automatica N2 - The Kuramoto model is essential for studying synchronization. In this work, we present sufficient conditions for global synchronization in networks of heterogeneous Kuramoto oscillators in the absence of homoclinic and heteroclinic cycles. The result is established by constructing a suitable Leonov function candidate for the Kuramoto model, which provides sufficient conditions for almost global synchronization in networks with acyclic and meshed topologies. The synchronization property is accompanied by necessary and sufficient conditions to guarantee the existence of equilibria, which are satisfied if the conditions for synchronization hold. The implications of the main conditions and their relationship with the network topology and parameters are discussed. Finally, the results are illustrated via a numerical example. Y1 - 2025 U6 - https://doi.org/10.1016/j.automatica.2025.112180 SN - 0005-1098 VL - 175 SP - 1 EP - 11 PB - Elsevier BV CY - Amsterdam ER - TY - CHAP A1 - Schiffer, Johannes A1 - Simpson-Porco, John W. A1 - Parisio, Alessandra T1 - Control in Low-Inertia Power and Integrated Energy Systems T2 - Reference Module in Materials Science and Materials Engineering N2 - 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. Y1 - 2024 SN - 9780128035818 U6 - https://doi.org/10.1016/B978-0-443-14081-5.00068-4 N1 - Kostenpflichtiger Zugang. PB - Elsevier ER - TY - GEN A1 - Jaramillo-Cajica, Ismael A1 - Schiffer, Johannes T1 - A dwell-time approach for decentralized grid-aware operation of islanded DC microgrids T2 - Automatica N2 - 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. Y1 - 2024 U6 - https://doi.org/10.1016/j.automatica.2023.111461 SN - 0005-1098 VL - 160 SP - 1 EP - 11 PB - Elsevier BV ER - TY - GEN A1 - Reimann, Ansgar A1 - Rose, Max A1 - Küpper, Jan A1 - Schiffer, Johannes T1 - Nonlinear system identification and predictive control for waste heat recovery with heat pumps T2 - IFAC-PapersOnLine N2 - 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. Y1 - 2024 U6 - https://doi.org/10.1016/j.ifacol.2024.07.103 SN - 2405-8963 VL - 58 IS - 2 SP - 130 EP - 135 PB - Elsevier BV ER - TY - GEN A1 - Herrmann, Ulrike A1 - Plietzsch, Anton A1 - Rose, Max A1 - Gernandt, Hannes A1 - Schiffer, Johannes T1 - A predictive operation management scheme for hydrogen networks based on the method of characteristics T2 - 2024 European Control Conference (ECC) N2 - 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. Y1 - 2024 U6 - https://doi.org/10.23919/ECC64448.2024.10591107 SP - 1084 EP - 1089 PB - IEEE ER - TY - GEN A1 - Texis-Loaiza, Oscar A1 - Zurita-Bustamante, Eric W. A1 - Schiffer, Johannes T1 - A BL-homogeneous observer for inter-turn short-circuit fault detection in PMSMs T2 - 2024 IEEE Conference on Control Technology and Applications (CCTA) N2 - 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. Y1 - 2024 U6 - https://doi.org/10.1109/CCTA60707.2024.10666505 SP - 248 EP - 253 PB - IEEE ER - TY - GEN A1 - Lorenz-Meyer, Nicolai A1 - Suchantke, René A1 - Schiffer, Johannes T1 - Dynamic state and parameter estimation in multi-machine power systems—Experimental demonstration using real-world PMU-measurements T2 - Control Engineering Practice N2 - Dynamic state and parameter estimation (DSE) plays a key role for reliably monitoring and operating future, power-electronics-dominated power systems. While DSE is a very active research field, experimental applications of proposed algorithms to real-world systems remain scarce. This motivates the present paper, in which we demonstrate the effectiveness of a DSE algorithm previously presented by parts of the authors with real-world data collected by a Phasor Measurement Unit (PMU) at a substation close to a power plant within the extra-high voltage grid of Germany. To this end, at first we derive a suitable mapping of the real-world PMU-measurements recorded at a substation close to the power plant to the terminal bus of the power plants’ synchronous generator. This mapping considers the high-voltage transmission line, the tap-changing transformer and the auxiliary system of the power plant. Next, we introduce several practically motivated extensions to the estimation algorithm, which significantly improve its practical performance with real-world measurements. Finally, we successfully validate the algorithm experimentally in an auto- as well as a cross-validation. Y1 - 2023 U6 - https://doi.org/10.1016/j.conengprac.2023.105491 SN - 0967-0661 VL - 135 ER - TY - GEN A1 - Rose, Max A1 - Hans, Christian A. A1 - Schiffer, Johannes T1 - A Predictive Operation Controller for an Electro-Thermal Microgrid Utilizing Variable Flow Temperatures T2 - IFAC-PapersOnLine N2 - We propose an optimal operation controller for an electro-thermal microgrid. Compared to existing work, our approach increases flexibility by operating the thermal network with variable flow temperatures and in that way explicitly exploits its inherent storage capacities. To this end, the microgrid is represented by a multi-layer network composed of an electrical and a thermal layer. We show that the system behavior can be represented by a discrete-time state model derived from DC power flow approximations and 1d Euler equations. Both layers are interconnected via heat pumps. By combining this model with desired operating objectives and constraints, we obtain a constrained convex optimization problem. This is used to derive a model predictive control scheme for the optimal operation of electro-thermal microgrids. The performance of the proposed operation control algorithm is demonstrated in a case study. Y1 - 2023 U6 - https://doi.org/10.1016/j.ifacol.2023.10.195 SN - 2405-8963 VL - 56 IS - 2 SP - 5444 EP - 5450 ER - TY - GEN A1 - Mendoza‐Avila, Jesus A1 - Efimov, Denis A1 - Angel Mercado‐Uribe, Jose A1 - Schiffer, Johannes T1 - Design of control laws for robust global stabilization of multistable state periodic systems T2 - International journal of robust and nonlinear control N2 - This paper continues with the development of the input‐to‐state stability (ISS)‐control Leonov function (CLeF) approach. The definitions of practical ISS and integral ISS (iISS)–CLeFs are refined, and the proposed methodology for control synthesis is improved to simplify the final control law. Then, it is shown that the existence of practical ISS‐ and iISS–CLeFs is a sufficient condition to guarantee the existence of a controller that endows multistable state periodic systems with the ISS and iISS properties, respectively. Furthermore, a methodology for the design of such a controller is provided via the well‐known Sontag's universal formula. Besides, an extension of the main result is presented to connect the ISS–CLeF approach with the standard Leonov function method such that the maximal invariant set of the closed‐loop system is compact on a manifold. Finally, the proposed approach is applied to the design of an excitation controller for a synchronous generator, which guarantees global ISS properties for the closed‐loop system, unlike the usual local results reported in the literature. The obtained control is also independent of the load angle. The effectiveness of the designed controller is demonstrated in simulations. KW - Global stabilization KW - Input-to-state stability KW - Multistability KW - Nonlinear control KW - Power systems KW - State periodic systems Y1 - 2025 U6 - https://doi.org/10.1002/rnc.70206 SN - 1049-8923 SN - 1099-1239 SP - 1 EP - 20 PB - Wiley CY - New York, NY ER - TY - GEN A1 - Şen, Gökçen Devlet A1 - Machado, Juan E. A1 - Schiffer, Johannes T1 - A cost-optimal predictive operation scheme for sector-coupled energy plants with start-up delays and start-up costs T2 - IFAC-PapersOnLine N2 - In this work we present a cost-optimal energy management scheme for sector-coupled energy plants, focusing on systems that enable gas-to-electricity, gas-to-heat, and power-to-heat conversions. To capture realistic operational challenges, the considered system model incorporates dynamic constraints, including start-up delays and off-time-dependent start-up costs. By accounting for the impact of these factors, we demonstrate on a case study that they can significantly reduce overall operational costs. The energy management problem is cast as a mixed-integer nonlinear programming (MINLP) problem, which is then solved within a model predictive control (MPC) framework. The proposed approach provides a structured methodology for real-time energy management, enhancing energy efficiency while minimizing costs. KW - Sector-coupling KW - Energy management KW - Mixed integer nonlinear programming KW - Model predictive control Y1 - 2025 U6 - https://doi.org/10.1016/j.ifacol.2025.08.143 SN - 2405-8963 VL - 59 IS - 9 SP - 241 EP - 246 PB - Elsevier BV CY - Amsterdam ER - TY - GEN A1 - Rose, Max A1 - Gernandt, Hannes A1 - Faulwasser, Timm A1 - Schiffer, Johannes T1 - Exact time-varying turnpikes for dynamic operation of district heating networks T2 - IEEE control systems letters N2 - District heating networks (DHNs) are crucial for decarbonizing the heating sector. Yet, their efficient and reliable operation requires the coordination of multiple heat producers and the consideration of future demands. Predictive and optimization-based control is commonly used to address this task, but existing results for DHNs do not account for time-varying problem aspects. Since the turnpike phenomenon can serve as a basis for model predictive control design and analysis, this letter examines its role in DHN optimization by analyzing the underlying optimal control problem with time-varying prices and demands. That is, we derive conditions for the existence of a unique time-varying singular arc, which constitutes the time varying turnpike, and we provide its closed-form expression. Additionally, we present converse turnpike results showing a exact time-varying case implies strict dissipativity of the optimal control problem. A numerical example illustrates our findings. KW - Energy systems KW - Optimal control KW - Predictive control for linear systems Y1 - 2025 U6 - https://doi.org/10.1109/LCSYS.2025.3582614 SN - 2475-1456 VL - 9 SP - 1706 EP - 1711 PB - IEEE CY - New York, NY ER - TY - GEN A1 - Büttner, Anna A1 - Würfel, Hans A1 - Liemann, Sebastian A1 - Schiffer, Johannes A1 - Hellman, Frank T1 - Complex-phase, data-driven identification of grid-forming inverter dynamics T2 - IEEE transactions on smart grid N2 - The increasing integration of renewable energy sources (RESs) into power systems requires the deployment of grid-forming inverters to ensure a stable operation. Accurate modeling of these devices is necessary. In this paper, a system identification approach to obtain low-dimensional models of gridforming inverters is presented. The proposed approach is based on a Hammerstein-Wiener parametrization of the normal-form model. The normal-form is a gray-box model that utilizes complex frequency and phase to capture non-linear inverter dynamics. The model is validated on two well-known control strategies: droop-control and dispatchable virtual oscillators. Simulations and hardware-in-the-loop experiments demonstrate that the normalform accurately models inverter dynamics across various operating conditions. The approach shows great potential for enhancing the modeling of RES-dominated power systems, especially when component models are unavailable or computationally expensive. Y1 - 2025 U6 - https://doi.org/10.1109/TSG.2025.3591891 SN - 1949-3053 VL - 9 IS - 6 SP - 4854 EP - 4864 PB - IEEE CY - New York, NY ER - TY - GEN A1 - Lorenz-Meyer, Nicolai A1 - Rueda-Escobedo, Juan G. A1 - Moreno, Jaime A. A1 - Schiffer, Johannes T1 - A robust consensus + innovations-based distributed parameter estimator T2 - IEEE transactions on automatic control N2 - While distributed parameter estimation has been extensively studied in the literature, little has been achieved in terms of robust analysis and tuning methods in the presence of disturbances. However, disturbances such as measurement noise and model mismatches occur in any real-world setting. Therefore, providing tuning methods with specific robustness guarantees would greatly benefit the practical application. To address these issues, we recast the error dynamics of a continuous-time version of the widely used consensus + innovations-based distributed parameter estimator to reflect the error dynamics induced by the classical gradient descent algorithm. This paves the way for the construction of a strong Lyapunov function. Based on this result, we derive linear matrix inequality-based tools for tuning the algorithm gains such that a guaranteed upper bound on the L2-gain with respect to parameter variations, measurement noise, and disturbances in the communication channels is achieved. An application example illustrates the efficiency of the method. KW - Distributed parameter estimation KW - Sensor networks KW - System identification KW - Time-varying systems Y1 - 2025 U6 - https://doi.org/10.1109/TAC.2025.3597563 SN - 0018-9286 SN - 1558-2523 SP - 1 EP - 15 PB - IEEE CY - New York, NY ER - TY - GEN A1 - Estrada, Manuel A. A1 - Rueda-Escobedo, Juan G. A1 - Moreno, Jaime A. A1 - Schiffer, Johannes T1 - Systematic and robust tuning of proportional-resonant controllers for current and voltage tracking T2 - 2025 IEEE Conference on Control Technology and Applications (CCTA), August 25-27, 2025, San Diego, CA, USA N2 - In the control and operation of power inverters, proportional-resonant (PR) controllers are used to track references and reject disturbances that can be described by a sum of sinusoidal signals of known frequency. The relevance of these controllers is increasing due to the increase in distortion and volatility of three-phase signals in the grid. However, as reported in the literature, the tuning of PR controllers is far from trivial due to their large number of parameters and the presence of pure imaginary poles in the associated transfer function. To address these issues, a time-domain framework based on linear matrix inequalities (LMIs) is presented for the tuning of PR controllers with applications to voltage and current tracking. The advantage of this approach is the straightforward combination with other techniques such as H∞ control. The effectiveness of the approach is illustrated through numerical simulations, where the injection of a constant active power is achieved in the presence of distorted voltages. Y1 - 2025 SN - 979-8-3315-3908-5 U6 - https://doi.org/10.1109/CCTA53793.2025.11151423 SN - 0018-9286 SN - 2768-0770 SP - 768 EP - 773 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Ortega, Romeo A1 - Bobtsov, Alexey A1 - Fang, Leyan A1 - Texis-Loaiza, Oscar A1 - Schiffer, Johannes T1 - Interturn fault detection in PMSMs : two adaptive observer-based noise insensitive solutions T2 - IEEE transactions on control systems technology N2 - In this article, we address the problem of online detection of interturn short-circuit faults (ITSCFs) that occur in interior- and surface-mounted permanent magnet synchronous motors (PMSMs). We propose two solutions to this problem: 1)a very simple linear observer and 2) a generalized parameter estimation-based observer, that incorporates a high performance estimator—with both observers detecting the short-circuit current and the fault intensity. Although the first solution guarantees the detection of the fault exponentially fast, the rate of convergence is fully determined by the motor parameters that, in some cases, may be too slow. The second observer, on the other hand, ensures finite convergence time (FCT) under the weakest assumption of interval excitation (IE). To make the observers adaptive, we develop a parameter estimator that, in the case of surface-mounted motors, estimates online (exponentially fast) the resistance and inductance of the motor. It should be underscored that, in contrast with existing observers (including the widely popular Kalman filter) that provide indirect information of the fault current, our observers provide an explicit one—namely the amplitude of the fault current. An additional advantage of the observers is that they do not require the knowledge of the motor currents, making them insensitive to current measurement noise. The performance of both observers, in their linear and generalized parameter estimation-based versions, is illustrated with realistic simulation studies. KW - Adaptive observer KW - Generalized parameter estimation-based observer (GPEBO) KW - Interturn short-circuit faults (ITSCFs) KW - Linear observer Y1 - 2025 U6 - https://doi.org/10.1109/TCST.2025.3612450 SN - 1063-6536 SN - 1558-0865 SP - 1 EP - 12 PB - IEEE CY - New York, NY ER - TY - GEN A1 - Hagemann, Willem A1 - Weichmann, Jaßper A1 - Gernandt, Hannes A1 - Krenzlin, Franziska A1 - Schiffer, Johannes T1 - Modeling and optimization of borehole thermal energy storage systems using physics-based neural networks T2 - Renewable energy : an international journal N2 - Borehole thermal energy storage (BTES) systems are critical components in the decarbonization of district heating networks as they enhance operational flexibility by seasonally storing thermal energy. While various modeling approaches for BTES exist, they are typically unsuitable for optimization problems and model-based control design. In this work, we propose a novel modeling approach that leads to a physics-based neural network surrogate model of the BTES temperature dynamics, capturing the fundamental dynamics with sufficient accuracy, while maintaining a relatively low complexity that makes it suitable for deployment in operational optimization or control algorithms. Specifically, we examine a standard BTES system that combines multiple heat sources, heat pumps, and storage buffers, detailing the associated mass flows and temperatures. We utilize a Python-based operational optimization process for the theoretical system setup using Pyomo and demonstrate that our modeling approach enables accurate optimizations over planning horizons of up to one year with a sample time of one hour. The new modeling approach significantly improves prediction accuracy across the relevant system states, with mean absolute errors reduced by approximately one-third compared to a single-capacitance model identified with the sparse identification framework SINDy. KW - Physics-based neural networks KW - Reduced order models KW - Borehole thermal energy storage KW - Operational optimization Y1 - 2026 U6 - https://doi.org/10.1016/j.renene.2025.123753 SN - 0960-1481 VL - 256, Part A SP - 1 EP - 14 PB - Elsevier BV CY - Amsterdam ER -