arXiv subjects

Orcun Karaca

Publications and source records attributed to Orcun Karaca.

At least 19 recordsLinked to original sources

arXiv2026

Disturbance-Observer-Based Grid-Forming Control for Unbalanced Grids

This article proposes a grid-forming control method for operation under unbalanced grid-voltage conditions. The method regulates the positive-sequence active power delivered to the grid and actively suppresses the negative-sequence converter voltage, controlling the voltage magnitude to be constant also during unbalanced faults when within the physical limits of the converter. Only the converter current is measured on the AC side, and a disturbance observer is used for synchronization as well as providing integral and resonant action. Estimates for the positive- and negative-sequence grid voltage are obtained from the disturbance observer. A current-limitation scheme for both balanced and unbalanced faults is integrated. Comprehensive stability analysis and tuning guidelines are provided. Experimental results using a 12.5-kVA converter demonstrate that the proposed method can operate during severe balanced and unbalanced faults.

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arXiv2026

A Feedback Stability Theorem for Frequency-dependent Compensation of Excess and Lack of Passivity

This article studies the stability of feedback interconnections of linear time-invariant systems based on frequency-dependent passivity indices. Using these frequency-dependent passivity indices, we show that the feedback interconnection of two systems can be certified to be stable even if both systems have a lack of passivity in terms of their scalar passivity indices. The main contribution of this paper is a new stability theorem based on frequency-dependent passivity indices. Moreover, we discuss the connection of the proposed feedback stability theorem to prior results based on scalar passivity indices. A numerical case study showcases the advantages of frequency-dependent passivity indices over scalar indices for feedback interconnections of linear systems.

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arXiv2026

Exploring Converter Control Duality in Microgrids: AC Grid-Forming vs DC Droop Control

Power electronic converters are fundamental building blocks of both AC and DC microgrids, enabling the integration of renewable energy sources, energy storage systems, electronic loads, and electric vehicles. In contrast, converter control in DC microgrids has developed along the path of droop control, which is widely adopted for decentralized DC-bus voltage regulation and power sharing. Although these control strategies share certain characteristics, their similarities remain largely unexplored due to the distinct physical domains in which they operate. To bridge this gap, we introduce a novel perspective based on the concept of duality to reveal the underlying isomorphism between the two control approaches. We show that AC grid-forming and DC I--V droop control are duals of each other in several aspects, including: (i) the small-signal model of the converter; (ii) the inner current control structure; (iii) power-sharing mechanisms based on the AC swing equation and DC capacitor power balance; and (iv) disturbance signals and dynamic response. Theoretical analysis, validated through simulations on simple converter setups, illustrates these dualities and provides new insights towards a unified control design.

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arXiv2026

Grid-Forming Characterization in DC Microgrids

DC microgrids are converter-based electrical networks that are increasingly being used in various applications, including data centers and industrial distribution systems. A central challenge in their operation is maintaining the DC-bus voltage within predefined limits while ensuring overall system stability. Although a wide variety of converter control algorithms has been proposed to achieve these objectives, the literature lacks a clear and physically interpretable framework for evaluating their effectiveness and for classifying and comparing them. Moreover, the grid-forming versus grid-following distinction that exists in AC systems has largely been unexplored in DC microgrids. To address this gap, this paper introduces three novel impedance-based indices that can be used to quantify the voltage-forming and current-forming behavior of a converter. The indices also provide a basis for defining the desired converter behavior that yields superior DC-bus voltage regulation performance. Simulation results illustrate the application of the framework to several representative control strategies and highlight the strengths and limitations of these control algorithms.

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arXiv2026

The role of VSG parameters in shaping small-signal SG dynamics

We derive a small-signal transfer function for a system comprising a virtual synchronous generator (VSG), a synchronous generator (SG), and a load, capturing voltage and frequency dynamics. Using this model, we analyze the sensitivity of SG dynamics to VSG parameters, highlighting trade-offs in choosing virtual inertia and governor lag, the limited effect of damper-winding emulation, and several others.

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arXiv2025

Grid-Forming Vector Current Control FRT Modes Under Symmetrical and Asymmetrical Faults

Recent research has shown that operating grid-connected converters using the grid-forming vector current control (GFVCC) scheme offers significant benefits, including the simplicity and modularity of the control architecture, as well as enabling a seamless transition from PLL-based grid-following control to grid-forming. An important aspect of any grid-connected converter control strategy is the handling of grid-fault scenarios such as symmetrical and asymmetrical short-circuit faults. This paper presents several fault ride-through (FRT) strategies for GFVCC that enable the converter to provide fault current and stay synchronized to the grid while respecting the converter hardware limitations and retaining grid-forming behavior. The converter control scheme is extended in a modular manner to include negative-sequence loops, and the proposed FRT strategies address both symmetrical and asymmetrical faults. The proposed FRT strategies are analyzed through case studies, including infinite-bus setups and multi-unit grids.

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arXiv2025

On the input admittance of a universal power synchronization controller with droop controllers

Recent work has proposed a universal framework that integrates the well-established power synchronization control into vector current control. Using this controller for the parallel operation of grid-forming converters, and/or with loads that have strong voltage magnitude sensitivity, requires additional loops manipulating the voltage magnitude, e.g., $QV$ and $PV$ voltage-power droop controllers. This paper derives the input admittance of the resulting overall scheme. Sensitivity analyses based on the passivity index demonstrate the benefits of the proportional components of $QV$ and $PV$ control. A case study is presented where a grid-forming converter is operated in parallel with a generator.

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arXiv2025

Robust black start of an offshore wind farm with DRU based HVDC link using power synchronization control

This paper introduces a universal power synchronization controller for grid-side control of the wind turbine conversion systems in an offshore wind farm with a diode rectifier in the offshore substation of the HVDC link. The controller incorporates voltage-power droop controllers in the outer loop to enable the operation of this setup. To effectively handle the impact of large delays during black start and power ramp phases, virtual active and reactive power quantities are defined. These quantities are computed based on the current references prior to any modifications that might be needed to meet converter current and voltage limits or source constraints. Utilizing them in the outer loop ensures a balanced power sharing and a stable operation whenever the original (unmodified) current references are not realized. Case studies confirm the robustness of the proposed controller.

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arXiv2024

On the SDP Relaxation of Direct Torque Finite Control Set Model Predictive Control

This paper formulates a semidefinite programming relaxation for a long horizon direct-torque finite-control-set model predictive control problem. In parallel with this relaxation, a conventional branch-and-bound algorithm tailored for the original problem, but with an iteration limit to restrict its computational burden, is also solved. An input sequence candidate is extracted from the solution of the semidefinite program in the lifted space. This sequence is then compared with the so-called early-stopping branch-and-bound solution, and the best of the two is applied in a receding horizon fashion. In simulated case studies, the proposed approach exhibits significant improvements in torque transients, as the branch-and-bound alone struggles to find a meaningful solution due to the imposed limit.

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arXiv2024

Frequency Constrained MPC for Efficient Grid Side Operation of Wind Power Conversion Systems

Model predictive control (MPC) has proven its applicability in power conversion control with its fast dynamic response to reference changes while ensuring critical system constraints are satisfied. Even then, the computational burden still remains a challenge for many MPC variants. In this regard, this paper formulates an indirect MPC scheme for grid-side wind converters. A quadratic program with linear constraints is solved in a receding horizon fashion with a subsequent PWM modulator. To facilitate its solution within a few hundreds of microseconds, its decision variables (modulating signals) are restricted to a specific frequency content. This approach limits the increase in problem size due to horizon length. In case studies, the proposed MPC exhibits fast response in faults and operates the converter within its safety limits.

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arXiv2024

Damping Wind Farm Resonances with Current Based Model Predictive Pulse Pattern Control

It is well-established that a proportional current control gain emulates a resistor in the converter output impedance. Even though this resistance can provide additional damping to grid resonances, its effect for traditional linear current controllers is known to be rather limited. Moreover, for medium-voltage systems, high switching frequencies are not an option due to the high switching losses. To meet the harmonic standards, it is expedient to use optimized pulse patterns. This further exacerbates the problems with the resistance of classical controllers, since an additional filtering would be required so that the current controller acts only on the fundamental component (and not on the ripple component). Such a design limits the damping effect not only in its amplitude but also in the frequency range where it is active. This paper shows that a high-bandwidth current-based model predictive pulse pattern controller can alleviate these limitations. The pulse pattern control approach can achieve a high gain even at low switching frequencies, while controlling directly the instantaneous currents (i.e., the fundamental component and the ripple together). With a fast implementation cycle, the frequency range where this damping effect is active can be further extended. Numerical studies showcase these benefits for a multi-phase medium-voltage wind power conversion system.

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arXiv2024

Switching Frequency Limitation with Finite Control Set Model Predictive Control via Slack Variables

Past work proposed an extension to finite control set model predictive control to track both a current reference and a switching frequency reference, simultaneously. Such an objective can jeopardize the current tracking performance, and this can potentially be alleviated by instead limiting the switching frequency. To this end, we propose to limit the switching frequency in finite control set model predictive control. The switching frequency is captured with an infinite impulse response filter and bounded by an inequality constraint; its corresponding slack variable is penalized in the cost function. To solve the resulting problem efficiently, a sphere decoder with a computational speed-up is presented.

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arXiv2022

Multi-robot task allocation for safe planning against stochastic hazard dynamics

We address multi-robot safe mission planning in uncertain dynamic environments. This problem arises in several applications including safety-critical exploration, surveillance, and emergency rescue missions. Computation of a multi-robot optimal control policy is challenging not only because of the complexity of incorporating dynamic uncertainties while planning, but also because of the exponential growth in problem size as a function of number of robots. Leveraging recent works obtaining a tractable safety maximizing plan for a single robot, we propose a scalable two-stage framework to solve the problem at hand. Specifically, the problem is split into a low-level single-agent control problem and a high-level task allocation problem. The low-level problem uses an efficient approximation of stochastic reachability for a Markov decision process to derive the optimal control policy under dynamic uncertainty. The task allocation is solved using polynomial-time forward and reverse greedy heuristics and in a distributed auction-based manner. By leveraging the properties of our safety objective function, we provide provable performance bounds on the safety of the approximate solutions proposed by these two heuristics. We evaluate the theory with extensive numerical case studies.

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arXiv2021

Actuator Placement for Structural Controllability beyond Strong Connectivity and towards Robustness

Actuator placement is a fundamental problem in control design for large-scale networks. In this paper, we study the problem of finding a set of actuator positions by minimizing a given metric, while satisfying a structural controllability requirement and a constraint on the number of actuators. We first extend the classical forward greedy algorithm for applications to graphs that are not necessarily strongly connected. We then improve this greedy algorithm by extending its horizon. This is done by evaluating the actuator position set expansions at the further steps of the classical greedy algorithm. We prove that this new method attains a better performance, when this evaluation considers the final actuator position set. Moreover, we study the problem of minimal backup placements. The goal is to ensure that the system stays structurally controllable even when any of the selected actuators goes offline, with minimum number of backup actuators. We show that this problem is equivalent to the well-studied NP-hard hitting set problem. Our results are verified by a numerical case study.

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arXiv2021

Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid

This letter studies the problem of minimizing increasing set functions, or equivalently, maximizing decreasing set functions, over the base of a matroid. This setting has received great interest, since it generalizes several applied problems including actuator and sensor placement problems in control theory, multi-robot task allocation problems, video summarization, and many others. We study two greedy heuristics, namely, the forward and the reverse greedy algorithms. We provide two novel performance guarantees for the approximate solutions obtained by these heuristics depending on both the submodularity ratio and the curvature.

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arXiv2021

A market-based approach for enabling inter-area reserve exchange

Considering the sequential clearing of energy and reserves in Europe, enabling inter-area reserve exchange requires optimally allocating inter-area transmission capacities between these two markets. To achieve this, we provide a market-based allocation framework and derive payments with desirable properties. The proposed min-max least core selecting payments achieve individual rationality, budget balance, and approximate incentive compatibility and coalitional stability. The results extend the works on private discrete items to a network of continuous public choices.

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arXiv2020

On the theory and applications of mechanism design and coalitional games in electricity markets

Although the specific structures of electricity markets are diverse around the world, they were all conceived on the premise of predictable, controllable generation with nonnegligible marginal costs. Recent changes, specifically, the increasing renewable integration, have challenged such assumptions. In light of this shift, this thesis intends to devise new frameworks and advance our understanding of the future markets. The first part focuses on mechanism design when the model fully reflects the physics of the grid and the participants. We consider a market that involves continuous goods, general nonconvex constraints, and second stage costs. We then design the payments and conditions under which coalitions cannot influence the outcome. Under the incentive-compatible VCG mechanism, we prove that coalition-proof outcomes are achieved if bids are convex and constraints are polymatroids. By relaxing incentive-compatibility, we investigate core-selecting mechanisms that are coalition-proof without conditions. We show that they generalize the economic rationale of the LMP mechanism, and can approximate truthfulness without the price-taking assumption. Finally, they are budget-balanced. The second part coordinates regional markets to exploit the geographic diversification of renewables. In Europe, reserves remain an exclusive responsibility of regional operators. This limited coordination and the sequential structure hinder the utilization of generation and transmission. To promote reserve exchange, a preemptive model can optimally withdraw inter-area transmission capacity from day-ahead energy for reserves. This bilevel program however does not suggest costs that guarantee coordination. We formulate a new preemptive model that allows us to obtain stable benefits immune to deviations. Our proposal, least-core benefits, achieves minimal stability violation with a tractable computation.

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arXiv2020

Actuator Placement under Structural Controllability using Forward and Reverse Greedy Algorithms

Actuator placement is an active field of research which has received significant attention for its applications in complex dynamical networks. In this paper, we study the problem of finding a set of actuator placements minimizing the metric that measures the average energy consumed for state transfer by the controller, while satisfying a structural controllability requirement and a cardinality constraint on the number of actuators allowed. As no computationally efficient methods are known to solve such combinatorial set function optimization problems, two greedy algorithms, forward and reverse, are proposed to obtain approximate solutions. We first show that the constraint sets these algorithms explore can be characterized by matroids. We then obtain performance guarantees for the forward and reverse greedy algorithms applied to the general class of matroid optimization problems by exploiting properties of the objective function such as the submodularity ratio and the curvature. Finally, we propose feasibility check methods for both algorithms based on maximum flow problems on certain auxiliary graphs originating from the network graph. Our results are verified with case studies over large networks.

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