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Identification of Power systems with Droop-Controlled Units Using Neural Ordinary Differential Equations

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arXiv 2024年

作者： Wolf, Hannes M.H. Hans, Christian A. The Automation and Sensorics in Networked Systems Group University of Kassel Germany

In future power systems, the detailed structure and dynamics may not always be fully known. This is due to an increasing number of distributed energy resources, such as photovoltaic generators, battery storage systems, heat pumps and electric vehicles, as well as a shift towards active distribution grids. Obtaining physically-based models for simulation and control synthesis can therefore become challenging. Differential equations, where the right-hand side is represented by a neural network, i.e., neural ordinary differential equations (NODEs), have a great potential to serve as a data-driven black-box model to overcome this challenge. This paper explores their use in identifying the dynamics of droop-controlled grid-forming units based on inputs and state measurements. In numerical studies, various NODEs structures used with different numerical solvers are trained and evaluated. Moreover, they are compared to the sparse identification of nonlinear dynamics (SINDy) method. The results demonstrate that even though SINDy yields more accurate models, NODEs achieve good prediction performance without prior knowledge about the system’s nonlinearities which SINDy requires to work best. Copyright © 2024, The Authors. All rights reserved.

关键词： DC distribution systems

Hierarchical Distributed Scenario-Based Model Predictive Control of Interconnected Microgrids

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Hierarchical Distributed Scenario-Based Model Predictive Con...

European Control Conference (ECC)

作者： T. Alissa Schenck Christian A. Hans Technische Universitat Berlin Germany Automation and Sensorics in Networked Systems Group University of Kassel Germany

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Microgrids are autonomous clusters of generators, storage units and loads. Special requirements arise in interconnected operation: control schemes that do not require individual microgrids to disclose information about their internal structure and operating objectives are preferred for privacy reasons. Moreover, a safe and economically meaningful operation shall be achieved in presence of uncertain load and weather-dependent availability of renewable infeed. In this paper, we propose a hierarchical distributed model predictive control approach that satisfies these requirements. Specifically, we demonstrate that costs and safety of supply can be improved through a scenario-based stochastic control scheme. In a numerical case study, our approach is compared to a certainty equivalence and a prescient scheme. The results illustrate good performance as well as sufficiently fast convergence.

关键词： Privacy Renewable energy sources Costs Scalability Stochastic processes Microgrids Prediction algorithms

Microgrid Operation Control with State-of-Charge-Dependent Storage Power Constraints

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arXiv 2025年

作者： Anccas, Edgar Diego Gomez Hans, Christian A. Schulz, Detlef Chair of Electrical Power Systems Helmut Schmidt University Hamburg Germany Automation and Sensorics in Networked Systems Group University of Kassel Kassel Germany

The microgrid concept offers high flexibility and resilience due to the possibility of switching between grid-connected and stand-alone operation. This renders microgrids an auspicious solution for rural areas and critical infrastructure. In standalone or islanded mode, the main objective is cost minimization while ensuring a safe and reliable operation. Optimal operation schemes for microgrids usually assume fixed power limits for energy storage units. This, however, is not sufficient for lithium-ion energy storage systems, which often come with dynamic power limits that depend on the state of charge. These limits are especially prominent when the state of charge is close to its boundaries. In this paper, dynamic constraints for energy storages are modelled using convex polytopes and fitted to experimental data acquired from an 11.6 kWh lithium-ion energy storage system. The polytopic constraints are integrated in a model predictive control scheme that was designed for a standalone microgrid composed of a fuel cell, a photovoltaic generator and a lithium-ion energy storage system. To evaluate the advantages, a case study with two configurations is performed. The model predictive controller without polytopic constraints led to constraint violations in 11.77 % of the simulation time steps with a maximum deviation of 118 % above the power limits. The configuration with polytopic constraints in contrary led to no violations over the entire simulation horizon. Copyright © 2025, The Authors. All rights reserved.

关键词： State of charge

H∞ Loop-shaping for Power Tracking Control of Wind Turbines

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arXiv 2025年

作者： Grapentin, Aaron Hans, Christian A. Raisch, Jörg Control Systems Group Technische Universität Berlin Germany Automation and Sensorics in Networked Systems Group University of Kassel Germany Research Cluster of Excellence Berlin Germany

In this paper, we present an advanced wind turbine control scheme for power maximization as well as for active power control, which is designed using H∞ loop-shaping. Our approach involves the synthesis of two separate controllers for two different operating modes. To ensure smooth transitions between these modes, we implement a bumpless transfer strategy that reduces transient effects. A comprehensive case study demonstrates the efficacy of our control scheme, showing significant improvements in power tracking accuracy and a reduction in mechanical wear. Moreover, our control strategy comes with robust stability guarantees. Copyright © 2025, The Authors. All rights reserved.

关键词： Wind turbines

Hierarchical distributed scenario-based model predictive control of interconnected microgrids

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arXiv 2023年

作者： Schenck, T. Alissa Hans, Christian A. Technische Universität Berlin Germany The Automation and Sensorics in Networked Systems Group University of Kassel Germany

关键词： Predictive control systems

Model predictive control of wakes for wind farm power tracking

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arXiv 2024年

作者： Sterle, Arnold Hans, Christian A. Raisch, Jörg Technische Universität Berlin Control Systems Group Germany Science of Intelligence Research Cluster of Excellence The University of Kassel Automation and Sensorics in Networked Systems Group Germany

In this paper, a model predictive control scheme for wind farms is presented. Our approach considers wake dynamics including their influence on local wind conditions and allows the tracking of a given power reference. In detail, a Gaussian wake model is used in combination with observation points that carry wind condition information. This allows the estimation of the rotor effective wind speeds at downstream turbines, based on which we deduce their power output. Through different approximation methods, the associated finite horizon nonlinear optimization problem is reformulated in a mixed-integer quadratically-constrained quadratic program fashion. By solving the reformulated problem online, optimal yaw angles and axial induction factors are found. Closed-loop simulations indicate good power tracking capabilities over a wide range of power setpoints while distributing wind turbine infeed evenly among all units. Additionally, the simulation results underline real time capabilities of our approach. Copyright © 2024, The Authors. All rights reserved.

关键词： Model predictive control

Robust LQ Optimal Control for Wind Turbine Power Tracking Operation

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Robust LQ Optimal Control for Wind Turbine Power Tracking Op...

IEEE Conference on Decision and Control

作者： Aaron Grapentin Christian A. Hans Jörg Raisch Control Systems Group Technische Universität Berlin Germany Automation and Sensorics in Networked Systems Group University of Kassel Germany Science of Intelligence Research Cluster of Excellence Berlin Germany

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

关键词： Shafts Accuracy Robust stability Wind tunnels Poles and towers Optimal control Bending Wind turbines Standards Optimization

LQ Optimal Control for Power Tracking Operation of Wind Turbines

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IFAC-PapersOnLine 2023年第2期56卷 2759-2766页

作者： Aaron Grapentin Arnold Sterle Jörg Raisch Christian A. Hans Control Systems Group Technische Universität Berlin Germany Science of Intelligence Research Cluster of Excellence Berlin Germany Automation and Sensorics in Networked Systems University of Kassel Germany

In this paper, an approach for active power control of individual wind turbines is presented. State-of-the-art controllers typically employ separate control loops for torque and pitch control. In contrast, we use a multivariable control approach. In detail, active power control is achieved by using reference trajectories for generator speed, generator torque, and pitch angle such that a desired power demand is met if weather conditions allow. Then, a linear quadratic (LQ) optimal controller is used for reference tracking. In an OpenFAST simulation environment, the controller is compared to a state-of-the-art approach. The simulations show a similar active power tracking performance, while the LQ optimal controller results in lower mechanical wear. Moreover, the presented approach exhibits good reference tracking and by improving the reference trajectory generation further performance increases can be expected.

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Robust LQ Optimal Control for Wind Turbine Power Tracking Operation

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arXiv 2024年

作者： Grapentin, Aaron Hans, Christian A. Raisch, Jörg The Control Systems Group Technische Universität Berlin Germany The Automation and Sensorics in Networked Systems Group University of Kassel Germany The Control Systems Group Technische Universität Berlin Germany Science of Intelligence Research Cluster of Excellence Berlin Germany

In this paper, a robust linear quadratic optimal control approach for accurate active power tracking of wind turbines is presented. For control synthesis, linear matrix inequalities are employed using an augmented wind turbine state model with uncertain parameters. The resulting controller ensures robust stability in different operating regions. In a case study, the novel approach is compared to existing controllers from literature. Simulations indicate that the controller improves power tracking accuracy while leading to similar mechanical wear as existing approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Wind turbines