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Ioannis Lestas

Publications and source records attributed to Ioannis Lestas.

At least 19 recordsLinked to original sources

Decentralised Plug-and-Play Stability Conditions for AC Grids-Part I

The rise of renewable generation in AC power systems calls for small-signal stability assessment methods that do not rely on centralised, system-wide models. In this two-part paper, we present a decentralised stability framework based on frequency-domain conditions imposed on local subsystems (many admitting equivalent graphical interpretations) which collectively imply the stability of the entire grid. The framework generalises many previously reported results, with added flexibility and plug-and-play compatibility provided by the additional degrees of freedom of the imposed conditions, the ability to mix conditions across frequency ranges, conditions on extended subsystems that couple buses to their connecting lines and loads, and a method to incorporate unstable subsystems. Detailed, heterogeneous device and line models are accommodated in the frequency domain using impedance, admittance, and power-flow models, making the framework suitable as a foundation for grid codes that enable plug-and-play functionality in inverter-dominated grids. Part I focuses on stable impedance and admittance representations and Part II extends the results to unstable subsystems, which are shown to be fundamentally present in many grid models. The results of Part I are validated on a modified 9-bus case study, demonstrating the reduced conservatism and significance of the proposed approach.

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Decentralised Plug-and-Play Stability Conditions for AC Grids-Part II: Unstable Subsystems

Part I of this paper presented a decentralised framework for certifying small-signal stability in AC grids using frequency-domain quadratic constraints on individual grid subsystems. Part II extends the framework to a broader class of networks that contain unstable subsystems. In particular, we show that such unstable subsystems arise in many common scenarios, even when the aggregate system is stable and well behaved. Such subsystems must be stabilised by the closed-loop network interconnection, which complicates decentralised stability analysis. A stable hybrid representation resembling the power (PQ) model at low frequencies and the impedance (IV) model at high frequencies is then defined, to which the stability framework of Part I can be applied, allowing plug-and-play compatible conditions to be formulated. Furthermore, we show that at low frequencies, the characteristic loci in the Nyquist plot of the return ratio in this hybrid representation decouple into unbounded and bounded branches along the classical $P$-$\delta$ / $Q$-$V$ separation, and give sufficient conditions on each branch for ensuring system stability. The results are validated on the Kundur two-area system, where stability is certified, with a decentralised, plug-and-play compatible grid code covering the frequency ranges in which electromagnetic interactions arise.

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Coordinated Primary Frequency Regulation and Grid-Forming Control for Wind Turbine Generators

Conventional grid-forming (GFM) control strategies often treat the DC source as an unconstrained link, creating mismatches when applied to the wind turbine generators (WTGs). Focusing on primary frequency regulation, this paper systematically investigates the mismatch between the GFM-WTGs behavior and the droop-based primary frequency regulation. To address this issue, a novel coordination strategy between WTG primary frequency regulation and GFM control is proposed. By establishing well-designed relationships among the power-tracking coefficient, power set-point, and frequency deviation, the proposed strategy enables GFM-WTGs to participate consistently in primary frequency regulation within predefined frequency limits while maintaining appropriate power points and effectively utilizing the allowable power reserve. Furthermore, the proposed method preserves the control structure and dynamic performance of conventional GFM control and inherently adapts to varying wind-speed conditions. Comparative case studies under different operating scenarios demonstrate the effectiveness and superiority of the proposed strategy.

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LiFT-MPC: Language-in-the-Loop Feedback Tuning of Cost Previews for MPC

In model predictive control (MPC) with time-varying objectives, predicted signals need to be often incorporated in the cost function, such as prices in energy system operation. These are, however, often difficult to predict from the historical trajectory of these signals alone, as they may depend on other contextual events. We propose LiFT-MPC, an MPC framework that integrates a LiFT (Language-in-the-Loop Feedback Tuning) correction scheme to refine such predictions within the MPC loop. The prediction mechanism is updated online via a control-performance loss function, and we establish a performance guarantee for the resulting closed loop system. Numerical experiments using a realistic example of energy-storage management with real prices and news context to improve predictions, demonstrate an improved economic performance

math.OC

Unstable Poles Arising in AC Power Grid Subsystem Representations

Recent small-signal stability studies of AC grids have shifted towards analysing power systems as interconnections of subsystems and leveraging their input-output properties to derive scalable stability certificates. Two subsystem representations appear frequently in the literature: the PQ model, coupling powers to phase angle and voltage magnitude, and the IV model, coupling currents to voltages. In this paper, we derive both models without simplifying the bus or line dynamics and show that a loop transformation relates the two. One of the main results in the paper is to then show analytically that each representation may exhibit unstable poles depending primarily on the operating point (IV model) or the presence of high-frequency passive dynamics (PQ model). In particular, such unstable poles in the subsystems can occur even when the aggregate interconnection is stable and well-behaved. These effects are validated numerically, including a case study using the full-order dynamics of a synchronous generator with an exciter and transformer. Our results highlight that care must be taken when choosing a subsystem representation, as neglecting high-frequency dynamics or device operating points may obscure unstable poles that must be stabilised by the network interconnection and must be accounted for in system identification.

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Data-driven online control for real-time optimal economic dispatch and temperature regulation in district heating systems

District heating systems (DHSs) require coordinated economic dispatch and temperature regulation under uncertain operating conditions. Existing DHS operation strategies often rely on disturbance forecasts and nominal models, so their economic and thermal performance may degrade when predictive information or model knowledge is inaccurate. This paper develops a data-driven online control framework for DHS operation by embedding steady-state economic optimality conditions into the temperature dynamics, so that the closed-loop system converges to the economically optimal operating point without relying on disturbance forecasts. Based on this formulation, we develop a Data-Enabled Policy Optimization (DeePO)-based online learning controller and incorporate Adaptive Moment Estimation (ADAM) to improve closed-loop performance. We further establish convergence and performance guarantees for the resulting closed-loop system. Simulations on an industrial-park DHS in Northern China show that the proposed method achieves stable near-optimal operation and strong empirical robustness to both static and time-varying model mismatch under practical disturbance conditions.

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A mixed Hinfty-Passivity approach for Leveraging District Heating Systems as Frequency Ancillary Service in Electric Power Systems

This paper introduces a mixed H-infinity-passivity framework that enables district heating systems (DHSs) with heat pumps to support electric-grid frequency regulation. The analysis illustrates how the DHS regulator influences coupled electro-thermal frequency dynamics and provides LMI conditions for efficient controller design. We also present a disturbance-independent temperature regulator that ensures stability and robustness against heat-demand uncertainty. Simulations demonstrate improved frequency-control dynamics in the electrical power grid while maintaining good thermal performance in the DHS.

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Frequency Control and Optimal Power Sharing in Combined Power and Heating Networks with Heat Pumps

Heat pumps have the capability for fast adjustments in power consumption with potential connections to large heating-inertia district heating networks, and are thus a very important resource for providing frequency support in low-inertia power systems. Nevertheless, the coupling of power networks with district heating systems renders the underlying dynamics much more involved. It is therefore important to ensure that system stability and appropriate power sharing are maintained. In this paper, we consider the problem of leveraging district heating systems as ancillary services for primary frequency control in power networks via heat pumps. We propose a novel power sharing scheme for heating systems based on the average temperature. This enables an optimal power allocation among diverse energy sources without requiring load disturbances information. We then discuss two approaches for heating systems to contribute to frequency regulation in power networks. We show that both approaches ensure stability in the combined heat and power network and facilitate optimal power allocation among the different energy sources. We also discuss how various generation dynamics can be incorporated into our framework with guaranteed stability and optimality. Finally, we conduct simulations that demonstrate various tradeoffs in the transient response and the practical potential of the proposed approaches.

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An Optimal Control Interpretation of Augmented Distributed Optimization Algorithms

Distributed optimization algorithms are used in a wide variety of problems involving complex network systems where the goal is for a set of agents in the network to solve a network-wide optimization problem via distributed update rules. In many applications, such as communication networks and power systems, transient performance of the algorithms is just as critical as convergence, as the algorithms link to physical processes which must behave well. Primal-dual algorithms have a long history in solving distributed optimization problems, with augmented Lagrangian methods leading to important classes of widely used algorithms, which have been observed in simulations to improve transient performance. Here we show that such algorithms can be seen as being the optimal solution to an appropriately formulated optimal control problem, i.e., a cost functional associated with the transient behavior of the algorithm is minimized, penalizing deviations from optimality during algorithm transients. This is shown for broad classes of algorithm dynamics, including the more involved setting where inequality constraints are present. The results presented improve our understanding of the performance of distributed optimization algorithms and can be used as a basis for improved formulations.

math.OC

On-Policy Reinforcement-Learning Control for Optimal Energy Sharing and Temperature Regulation in District Heating Systems

We address the problem of temperature regulation and optimal energy sharing in district heating systems (DHSs) where the demand and system parameters are unknown. We propose a temperature regulation scheme that employs data-driven on-policy updates that achieve these objectives. In particular, we show that the proposed control scheme converges to an optimal equilibrium point of the system, while also having guaranteed convergence to an optimal LQR control policy, thus providing good transient performance. The efficiency of our approach is also demonstrated through extensive simulations.

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Fundamental limits on taming infectious disease epidemics

Epidemic control frequently relies on adjusting interventions based on prevalence. But designing such policies is a highly non-trivial problem due to uncertain intervention effects, costs and the difficulty of quantifying key transmission mechanisms and parameters. Here, using exact mathematical and computational methods, we reveal a fundamental limit in epidemic control in that prevalence feedback policies are outperformed by a single optimally chosen constant control level. Specifically, we find no incentive to use prevalence based control under a wide class of cost functions that depend arbitrarily on interventions and scale with infections. We also identify regimes where prevalence feedback is beneficial. Our results challenge the current understanding that prevalence based interventions are required for epidemic control and suggest that, for many classes of epidemics, interventions should not be varied unless the epidemic is near the herd immunity threshold.

q-bio.PE

Optimal control of stochastic networks of $M/M/\infty$ queues with linear costs

We consider an arbitrary network of $M/M/\infty$ queues with controlled transitions between queues. We consider optimal control problems where the costs are linear functions of the state and inputs over a finite or infinite horizon. We provide in both cases an explicit characterization of the optimal control policies. We also show that these do not involve state feedback, but they depend on the network topology and system parameters. The results are also illustrated with various examples.

math.OC

Comparison of Droop-Based Single-Loop Grid-Forming Wind Turbines: High-Frequency Open-Loop Unstable Behavior and Damping

The integration of inverter-interfaced generators introduces new instability phenomena into modern power systems. This paper conducts a comparative analysis of two widely used droop-based grid-forming controls, namely droop control and droop-I control, in wind turbines. Although both approaches provide steady-state reactive power-voltage droop characteristics, their impacts on high-frequency (HF) stability differ significantly. Firstly, on open-loop (OL) comparison reveals that droop-I control alters HF pole locations. The application of Routh's Stability Criterion further analytically demonstrates that such pole shifts inevitably lead to OL instability. This HF OL instability is identified as a structural phenomenon in purely inductive grids and cannot be mitigated through control parameter tuning. As a result, droop-I control significantly degrades HF stability, making conventional gain and phase margins insufficient for evaluating robustness against parameter variations. Then, the performance of established active damping (AD) is assessed for both control schemes. The finding indicates that AD designs effective for droop control may fail to suppress HF resonance under droop-I control due to the presence of unstable OL poles. Case studies performed on the IEEE 14-Bus Test System validate the analysis and emphasize the critical role of HF OL instability in determining the overall power system stability.

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LCL Resonance Analysis and Damping in Single-Loop Grid-Forming Wind Turbines

A common assumption in both grid-following (GFL) and grid-forming (GFM) control systems is that they are open-loop (OL) stable in the vicinity of high-frequency resonances. Hence classical loop-shaping approaches are often used for establishing stability margins and designing active damping (AD) strategies. This paper shows that single-loop GFM (SL-GFM) control schemes incorporating a widely used class of reactive power (RAP) control, referred to as droop-I control, can lead to OL unstable poles. This finding reveals a novel instability mechanism resulting in a reduced stability margin and robustness at high frequencies. The sensitivity of this phenomenon to both RAP and electrical parameters is analyzed in detail. An AD design that explicitly accounts for the newly identified instability mechanism is proposed. We also provide a comparison between such SL-GFM and well-studied GFL control schemes, highlighting quite different resonance features between them. Validation is performed through experiments.

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First-Order Projected Algorithms With the Same Linear Convergence Rate Bounds as Their Unconstrained Counterparts

In this paper, we propose a systematic approach for extending first-order optimization algorithms, originally designed for unconstrained strongly convex problems, to handle closed convex set constraints. We show that the resulting projected algorithms retain the same linear convergence rate bounds, provided that the underlying unconstrained optimization algorithms admit a quadratic Lyapunov function obtained from integral quadratic constraint (IQC) analysis. The projected algorithms are constructed by applying a projection in the norm induced by the Lyapunov matrix, ensuring both constraint satisfaction and optimality at the fixed point. Furthermore, under a linear transformation associated with this matrix, the projection becomes non-expansive in the Euclidean norm, thereby preserving the convergence rate bounds under the composition of the linearly convergent algorithmic operator and the projection. Our results indicate that, when analyzing worst-case convergence rates or when synthesizing first-order optimization algorithms with potentially higher-order dynamics, it suffices to focus solely on the unconstrained dynamics, since the same parameters or stepsizes can be employed without retuning.

math.OC

Frequency Control and Power Sharing in Combined Heat and Power Networks

We consider the problem of using district heating systems as ancillary services for primary frequency control in power networks. We propose a novel power sharing scheme for heating systems based on the average temperature, which enables an optimal power allocation among the diverse heat sources without having a prior knowledge of the disturbances. We then discuss two approaches for heating systems to contribute to frequency regulation in power networks. We show that both approaches ensure stability in the combined heat and power network and facilitate optimal power allocation among the different energy sources.

eess.SY

Economic Capacity Withholding Bounds of Competitive Energy Storage Bidders

Economic withholding in electricity markets refers to generators bidding higher than their true marginal fuel cost, and is a typical approach to exercising market power. However, existing market designs require storage to design bids strategically based on their own future price predictions, motivating storage to conduct economic withholding without assuming market power. As energy storage takes up more significant roles in wholesale electricity markets, understanding its motivations for economic withholding and the consequent effects on social welfare becomes increasingly vital. This paper derives a theoretical framework to study the economic capacity withholding behavior of storage participating in competitive electricity markets and validate our results in simulations based on the ISO New England system. We demonstrate that storage bids can reach unbounded high levels under conditions where future price predictions show bounded expectations but unbounded deviations. Conversely, in scenarios with peak price limitations, we show the upper bounds of storage bids are grounded in bounded price expectations. Most importantly, we show that storage capacity withholding can potentially lower the overall system cost when price models account for system uncertainties. Our paper reveals energy storage is not a market manipulator but an honest player contributing to the social welfare. It helps electricity market researchers and operators better understand the economic withholding behavior of storage and reform market policies to maximize storage contributing to a cost-efficient decolonization.

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Control of AC-AC interlinking converters for multi-grids

This paper considers the control of AC-AC inter-linking converters (ILCs) in a multi-grid network. We overview the control schemes in the literature and propose a passivity framework for the stabilization of multi-grid networks, considering both AC grid-following and AC grid-forming behavior for the ILC connections. We then analyze a range of AC/AC interlinking converter control methods derived from the literature and propose suitable controllers for this purpose including both AC grid-forming and grid-following behavior. The controller we propose is partially grid-forming; in particular, it is based on a combination of a grid-following and a grid-forming converter to improve the stability properties of the network. Simulation results and theoretical analysis confirm that the proposed ILC control designs are appropriate for the multi-grid network.

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