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Found 73 papers, 9 papers with code
The Continuous-Time Weighted-Median Opinion Dynamics
It turns out that the proof methods for the original discrete-time asynchronous model are no longer applicable to the analysis of the continuous-time model.
Cross-Forming Control and Fault Current Limiting for Grid-Forming Inverters
We propose two feasible control strategies to realize the cross-forming concept, enabling inverters to fast-limit the fault current at a prescribed level while preserving voltage angle forming for grid-forming-type synchronization and dynamic ancillary services provision during fault ride-through.
Stability Certificates for Receding Horizon Games
Game-theoretic MPC (or Receding Horizon Games) is an emerging control methodology for multi-agent systems that generates control actions by solving a dynamic game with coupling constraints in a receding-horizon fashion.
Dynamic Complex-Frequency Control of Grid-Forming Converters
Complex droop control, alternatively known as dispatchable virtual oscillator control (dVOC), stands out for its unique capabilities in synchronization and voltage stabilization among existing control strategies for grid-forming converters.
Saturation-Informed Current-Limiting Control for Grid-Forming Converters
In this paper, we investigate the transient stability of a state-of-the-art grid-forming complex-droop control (i. e., dispatchable virtual oscillator control, dVOC) under current saturation.
Karma: An Experimental Study
A system of non-tradable credits that flow between individuals like karma, hence proposed under that name, is a mechanism for repeated resource allocation that comes with attractive efficiency and fairness properties, in theory.
Bridging the Sim-to-Real Gap with Bayesian Inference
We present SIM-FSVGD for learning robot dynamics from data.
Decoupling parameter variation from noise: Biquadratic Lyapunov forms in data-driven LPV control
A promising step from linear towards nonlinear data-driven control is via the design of controllers for linear parameter-varying (LPV) systems, which are linear systems whose parameters are varying along a measurable scheduling signal.
Control Strategies for Recommendation Systems in Social Networks
A closed-loop control model to analyze the impact of recommendation systems on opinion dynamics within social networks is introduced.
Tuning and Testing an Online Feedback Optimization Controller to Provide Curative Distribution Grid Flexibility
A flexibility request from the transmission grid to a distribution grid then needs to be split up onto the different flexibility providing units (FPU) in the distribution grid.
Optimal Dynamic Ancillary Services Provision Based on Local Power Grid Perception
In this paper, we propose a systematic closed-loop approach to provide optimal dynamic ancillary services with converter-interfaced generation systems based on local power grid perception.
Towards a Systems Theory of Algorithms
Traditionally, numerical algorithms are seen as isolated pieces of code confined to an {\em in silico} existence.
Game-theoretic Model Predictive Control for Modelling Competitive Supply Chains
Supply chains transform raw materials into finished goods and distribute them to end consumers.
Power Grid Parameter Estimation Without Phase Measurements: Theory and Empirical Validation
The primary result of the paper is that, while the impedance of a line or a network can be estimated without synchronized phase angle measurements in a consistent way, the admittance cannot.
Advanced safety filter based on SOS Control Barrier and Lyapunov Functions
The second part of this work details the implementation of the safety filter as a Quadratically Constrained Quadratic Program (QCQP), whose constraints encode the CBF and CLF conditions as well as the input constraints.
Urban traffic congestion control: a DeePC change
Urban traffic congestion remains a pressing challenge in our rapidly expanding cities, despite the abundance of available data and the efforts of policymakers.
Quantitative Stability Conditions for Grid-Forming Converters With Complex Droop Control
In this paper, we study analytically the transient stability of grid-connected distributed generation systems with grid-forming (GFM) complex droop control, also known as dispatchable virtual oscillator control (dVOC).
Passivity and Decentralized Stability Conditions for Grid-Forming Converters
We prove that the popular grid-forming control, i. e., dispatchable virtual oscillator control (dVOC), also termed complex droop control, exhibits output-feedback passivity in its large-signal model, featuring an explicit and physically meaningful passivity index.
Dynamic Ancillary Services: From Grid Codes to Transfer Function-Based Converter Control
Namely, we translate the piece-wise linear time-domain curves for active and reactive power provision in response to a frequency and voltage step change into a desired rational parametric transfer function in the frequency domain, which defines a dynamic response behavior to be realized by the converter.
Gain and Phase: Decentralized Stability Conditions for Power Electronics-Dominated Power Systems
This paper proposes decentralized stability conditions for multi-converter systems based on the combination of the small gain theorem and the small phase theorem.
Joint Oscillation Damping and Inertia Provision Service for Converter-Interfaced Generation
To address this gap, this paper defines the joint oscillation damping and inertia provision services at the system level, seeking to encourage converter-interfaced generation to provide enhanced damping and fast frequency response capabilities.
Experimental Validation of a Dynamic Virtual Power Plant Concept Based on Multiple-Converter Power Hardware-In-the-Loop Test Bench
Recently, the concept of dynamic virtual power plants (DVPP) has been proposed to collectively provide desired dynamic ancillary services such as fast frequency and voltage control by a heterogeneous ensemble of distributed energy resources (DER).
Providing Curative Distribution Grid Flexibility Using Online Feedback Optimization
Distribution grid flexibility is discussed as a possible measure in curative system operation, yielding a need for an efficient and robust coordination mechanism for the joint flexibility provision by individual units to the transmission grid.
On the Guarantees of Minimizing Regret in Receding Horizon
Towards bridging classical optimal control and online learning, regret minimization has recently been proposed as a control design criterion.
Deployment of an Online Feedback Optimization Controller for Reactive Power Flow Optimization in a Distribution Grid
Optimization is an essential part of power grid operation and lately, Online Optimization methods have gained traction.
Power Distribution Grid Enhancement via Online Feedback Optimization
In this paper, we use real consumption and generation data on a low-voltage CIGR\'E grid model and an experiment on a real distribution grid feeder to analyze how different Volt/VAr methods can enhance grid capacity, i. e., by how much they can improve the grid's capability to transmit active power without building new lines.
Distributed State Estimation for Linear Time-Varying Systems with Sensor Network Delays
We provide comparisons between the estimation performance of our proposed algorithm and a greedy algorithm that exhaustively selects an optimal subset of nodes.
MIMO Grid Impedance Identification of Three-Phase Power Systems: Parametric vs. Nonparametric Approaches
A fast and accurate grid impedance measurement of three-phase power systems is crucial for online assessment of power system stability and adaptive control of grid-connected converters.
Regret Optimal Control for Uncertain Stochastic Systems
Specifically, we focus on the problem of designing a feedback controller that minimizes the loss relative to a clairvoyant optimal policy that has foreknowledge of both the system dynamics and the exogenous disturbances.
Designing Optimal Personalized Incentive for Traffic Routing using BIG Hype algorithm
We study the problem of optimally routing plug-in electric and conventional fuel vehicles on a city level.
Regularization for distributionally robust state estimation and prediction
We provide a direct method using samples of the noise to create a moving horizon observer for linear time-varying and nonlinear systems, which is optimal under the empirical noise distribution.
New Perspectives on Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization
We study optimal transport-based distributionally robust optimization problems where a fictitious adversary, often envisioned as nature, can choose the distribution of the uncertain problem parameters by reshaping a prescribed reference distribution at a finite transportation cost.
Designing Fairness in Autonomous Peer-to-peer Energy Trading
Several autonomous energy management and peer-to-peer trading mechanisms for future energy markets have been recently proposed based on optimization and game theory.
Stochastic Wasserstein Gradient Flows using Streaming Data with an Application in Predictive Maintenance
Since estimation problems can be posed as optimization problems in the probability space, we devise a stochastic projected Wasserstein gradient flow that keeps track of the belief of the estimated quantity and can consume samples from online data.
Convergence, Consensus and Dissensus in the Weighted-Median Opinion Dynamics
Moreover, we prove a necessary and sufficient graph-theoretic condition for the almost-sure convergence to consensus, as well as a sufficient graph-theoretic condition for almost-sure persistent dissensus.
Real-time Curative Actions for Power Systems via Online Feedback Optimization
Instead of pre-planning, we propose to calculate these complex curative actions in real-time after the occurrence of a contingency.
Online Feedback Optimization for Subtransmission Grid Control
The increasing electric power consumption and the shift towards renewable energy resources demand for new ways to operate transmission and subtransmission grids.
Minimal regret state estimation of time-varying systems
Kalman and H-infinity filters, the most popular paradigms for linear state estimation, are designed for very specific specific noise and disturbance patterns, which may not appear in practice.
Stability and Robustness of Distributed Suboptimal Model Predictive Control
In distributed model predictive control (MPC), the control input at each sampling time is computed by solving a large-scale optimal control problem (OCP) over a finite horizon using distributed algorithms.
Real-time Projected Gradient-based Nonlinear Model Predictive Control with an Application to Anesthesia Control
Medical drug infusion problems pose a combination of challenges such as nonlinearities from physiological models, model uncertainty due to inter- and intra-patient variability, as well as strict safety specifications.
Follow the Clairvoyant: an Imitation Learning Approach to Optimal Control
We consider control of dynamical systems through the lens of competitive analysis.
Nonlinear Stability of Complex Droop Control in Converter-Based Power Systems
In previous work, the global stability of dVOC (i. e., complex droop control) has been proven by prespecifying a nominal synchronous steady state.
Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions
In this paper, we explore optimal transport discrepancies (which include the Wasserstein distance) to define trust regions, and we propose a novel algorithm - Optimal Transport Trust Region Policy Optimization (OT-TRPO) - for continuous state-action spaces.
On Power Control of Grid-Forming Converters: Modeling, Controllability, and Full-State Feedback Design
A step-by-step construction and design procedure of the power control of grid-forming converters is also given.
Modeling of Political Systems using Wasserstein Gradient Flows
The study of complex political phenomena such as parties' polarization calls for mathematical models of political systems.
Complex-Frequency Synchronization of Converter-Based Power Systems
In this paper, we study phase-amplitude multivariable dynamics in converter-based power systems from a complex-frequency perspective.
CARMA: Fair and efficient bottleneck congestion management via non-tradable karma credits
In our CARMA scheme, the bottleneck is divided into a fast lane that is kept in free flow and a slow lane that is subject to congestion.
Approximation by Simple Poles -- Part I: Density and Geometric Convergence Rate in Hardy Space
The goal of this two-part article is to introduce a new Galerkin-type method based on approximation by transfer functions with a selection of simple poles, and to apply this simple pole approximation for optimal control design.
A self-contained karma economy for the dynamic allocation of common resources
This paper presents karma mechanisms, a novel approach to the repeated allocation of a scarce resource among competing agents over an infinite time.
Wasserstein Distributionally Robust Estimation in High Dimensions: Performance Analysis and Optimal Hyperparameter Tuning
Wasserstein distributionally robust optimization has recently emerged as a powerful framework for robust estimation, enjoying good out-of-sample performance guarantees, well-understood regularization effects, and computationally tractable reformulations.
Robust and Kernelized Data-Enabled Predictive Control for Nonlinear Systems
This paper presents a robust and kernelized data-enabled predictive control (RoKDeePC) algorithm to perform model-free optimal control for nonlinear systems using only input and output data.
Receding Horizon Games with Coupling Constraints for Demand-Side Management
Distributed energy storage and flexible loads are essential tools for ensuring stable and robust operation of the power grid in spite of the challenges arising from the integration of volatile renewable energy generation and increasing peak loads due to widespread electrification.
Robust online joint state/input/parameter estimation of linear systems
This paper presents a method for jointly estimating the state, input, and parameters of linear systems in an online fashion.
Approximation by Simple Poles -- Part II: System Level Synthesis Beyond Finite Impulse Response
In Part II, this approximation is applied to system level synthesis, a recent approach based on a clever reparameterization, to develop a new technique for optimal control design.
Safe Control with Minimal Regret
As we move towards safety-critical cyber-physical systems that operate in non-stationary and uncertain environments, it becomes crucial to close the gap between classical optimal control algorithms and adaptive learning-based methods.
Augmentation of Generalized Multivariable Grid-Forming Control for Power Converters with Cascaded Controllers
The classic design of grid-forming control strategies for power converters rely on the stringent assumption of the timescale separation between DC and AC states and their corresponding control loops, e. g., AC and DC loops, power and cascaded voltage and current loops, etc.
Grid-Forming and Spatially Distributed Control Design of Dynamic Virtual Power Plants
We present a novel grid-forming control design approach for dynamic virtual power plants (DVPP).
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems
To this end, neural ODEs regularized with neural Lyapunov functions are a promising approach when states are fully observed.
Adaptive Real-Time Grid Operation via Online Feedback Optimization with Sensitivity Estimation
In this paper we propose an approach based on an Online Feedback Optimization (OFO) controller with grid input-output sensitivity estimation for real-time grid operation, e. g., at subsecond time scales.
Cross-layer Design for Real-Time Grid Operation: Estimation, Optimization and Power Flow
In this paper, we propose a combined Online Feedback Optimization (OFO) and dynamic estimation approach for a real-time power grid operation under time-varying conditions.
Generalized Multivariable Grid-Forming Control Design for Power Converters
The grid-forming converter is an important unit in the future power system with more inverter-interfaced generators.
Control Design of Dynamic Virtual Power Plants: An Adaptive Divide-and-Conquer Approach
Our control approach relies on an adaptive divide-and-conquer strategy: first, we disaggregate the desired frequency and voltage control specifications of the aggregate DVPP via adaptive dynamic participation matrices (ADPMs) to obtain the desired local behavior for each device.
Bayesian Error-in-Variables Models for the Identification of Power Networks
The increasing integration of intermittent renewable generation, especially at the distribution level, necessitates advanced planning and optimisation methodologies contingent on the knowledge of thegrid, specifically the admittance matrix capturing the topology and line parameters of an electricnetwork.
Dynamic Virtual Power Plant Design for Fast Frequency Reserves: Coordinating Hydro and Wind
To ensure frequency stability in future low-inertia power grids, fast ancillary services such as fast frequency reserves (FFR) have been proposed.
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models
Differential equations in general and neural ODEs in particular are an essential technique in continuous-time system identification.
Robust Data-Enabled Predictive Control: Tractable Formulations and Performance Guarantees
The proposed framework enables us to obtain model-free optimal control for LTI systems based on noisy input/output data.
Structural Balance and Interpersonal Appraisals Dynamics: Beyond All-to-All and Two-Faction Networks
structural balance configurations of the appraisal networks.
Social and Information Networks Discrete Mathematics Systems and Control Systems and Control 93-10, 91D30, 68R10
Quadratic Regularization of Data-Enabled Predictive Control: Theory and Application to Power Converter Experiments
Moreover, when the input/output constraints are inactive, the quadratic regularization leads to a closed-form solution of the DeePC algorithm and thus enables fast calculations.
Decentralized Data-Enabled Predictive Control for Power System Oscillation Damping
Further, we discuss how to relieve the computational burden of the Min-Max DeePC by reducing the dimension of prediction uncertainty and how to leverage disturbance feedback to reduce the conservativeness of robustification.
Experimental Validation of Feedback Optimization in Power Distribution Grids
On a real distribution grid, we compare the local Volt/VAr droop control recommended in recent grid codes, a centralized dispatch based on optimal power flow (OPF) programming, and a feedback optimization (FO) controller that we propose.
Closing the Loop: Dynamic State Estimation and Feedback Optimization of Power Grids
This consists in continuously driving the controllable power injections and loads towards the optimal set-points in time-varying conditions based on real-time measurements performed on the grid.
Interactions of Grid-Forming Power Converters and Synchronous Machines -- A Comparative Study
An inevitable consequence of the global power system transition towards nearly 100% renewable-based generation is the loss of conventional bulk generation by synchronous machines, their inertia, and accompanying frequency and voltage control mechanisms.
Optimization and Control
Generic Existence of Unique Lagrange Multipliers in AC Optimal Power Flow
Even if the KKT conditions are applicable, the multipliers may not be unique.
Optimization and Control
