About

Alejandro Domínguez-García is a Professor of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. He has been recognized for his contributions to distributed control and uncertainty analysis of electrical energy systems. His research areas include control of distributed energy resources, power system health monitoring, reliability analysis, and quantifying and mitigating the impact of renewable-based generation. Additionally, he is a research professor in the Coordinated Science Laboratory and the Information Trust Institute, focusing on advancing the understanding and management of complex electrical energy systems.

Research topics

• Computer Science
• Mathematics
• Theoretical computer science
• Computer network
• Algorithm
• Mathematical optimization
• Combinatorics

Selected publications

• Distance characteristics for incremental quantities

  arXiv (Cornell University) · 2026-04-17

  preprintOpen accessSenior author

  We derive distance relay characteristics in terms of incremental quantities. The characteristics are operating-point independent in that they depend on the network structure and types of sources, but not their real-time voltages or current injections.

  PublisherDOI

• Distance characteristics for incremental quantities

  ArXiv.org · 2026-04-17

  articleOpen accessSenior author

  We derive distance relay characteristics in terms of incremental quantities. The characteristics are operating-point independent in that they depend on the network structure and types of sources, but not their real-time voltages or current injections.

  PublisherOA PDF

• Phase Difference Control of Single-Phase Grid Forming Inverters for Fault Detection

  2025-10-26

  articleSenior author

  This paper presents a strategy for controlling the phase differences of a three-phase voltage source made up of single-phase droop-controlled grid forming inverters arranged in a delta configuration. We derive a linear model approximately describing the system phase dynamics, and use it to formulate a Linear Quadratic Integral (LQI) controller capable of phase angle reference tracking. The proposed controller enables the system to be operated as a three-phase balanced source. Unbalanced operation is also desirable when supplying an unbalanced load or injecting auxiliary signals. MATLAB simulations are used to validate the proposed controller and demonstrate performance under nominal and unbalanced conditions. The LQI controller ensures minimal overshoot, zero steady-state error, and robust reference tracking in both the linearized and nonlinear model used to derive it. The results exemplify the flexibility of the controller tuning for precise shaping of system response, which is essential for adapting inverter-based resources (IBRs) to grid protection requirements.

  PublisherDOI

• Active Fault Detection in Static Systems

  IEEE Transactions on Automatic Control · 2025-03-04 · 1 citations

  articleSenior author

  We study auxiliary signal-based fault detection in static linear systems with quadratic constraints. Auxiliary signals are perturbations that make faults easier to detect, at the cost of some disruption to normal operation. In this article, we find minimally disruptive auxiliary signals that guarantee detection under set-based uncertainty. Our motivation is distance protection in inverter-dominated power systems, wherein small fault currents can go undetected by traditional schemes. We focus on static systems because distance protection is based on phasors. We formulate a general auxiliary signal design problem with constraints imposed by system operational requirements, and additive and multiplicative noise. We use a relaxation and duality to reformulate the problem as a semidefinite bilinear program. In the special case of additive uncertainty and no constraints, we obtain an analytical lower bound on the magnitude an auxiliary signal must have to guarantee detection. We solve the optimizations in an example based on distance protection, in which the auxiliary signal is negative sequence current.

  PublisherDOI

• Equivalent-circuit Models for Grid-forming Inverters under Unbalanced Steady-State Operating Conditions

  Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2025-01-01 · 1 citations

  articleOpen access

  Positive- and negative-sequence equivalent-circuit models are put forth to capture the operation of grid-forming (GFM) inverters in unbalanced steady-state operating conditions acknowledging the impact of current limiting. The particular control architecture examined adopts droop control (for primary control), nested inner-current and outer-voltage control (in the stationary reference frame), and it is adaptable to two different types of current limiting (current-reference saturation and virtual-impedance limiting). We anticipate the proposed models to be of interest in modeling, analysis, and simulation of GFM inverters in unbalanced settings that may arise, e.g., in the face of faults. Validation of the equivalent-circuit models is pursued via comparison with full-order electromagnetic-transient (EMT) simulations for representative balanced and unbalanced faults.

  PublisherOA PDFDOI

• Shadow Banning in Directed Graphs for Fault-Tolerant Averaging

  2025-06-24

  articleSenior author

  We consider the problem of average consensus in a distributed system wherein a subset of the nodes comprising the system becomes faulty. To address this problem, we rely on a class of averaging algorithms whereby each node maintains a collection of variables, which it iteratively updates as a linear combination of other variables received by the node from its in-neighbors, i.e., nodes from which it receives information directly. Algorithms within this class exhibit, throughout their execution, certain invariance properties that are local to each node and reflect the conservation of certain quantities capturing an aggregate of all the values received by a node from its in-neighbors and all the values sent by said node to its out-neighbors, i.e., nodes that receive its information directly. In this paper, we exploit one such invariance property to enable each node to check whether or not any of its in-neighbors becomes faulty during the execution of the algorithm. In addition, we provide a shadow-banning mechanism to remove faulty nodes from the execution, and nullify the information they have broadcast up to the time when they were declared faulty.

  PublisherDOI

• Trustworthy Distributed Average Consensus Based on Locally Assessed Trust Evaluations

  IEEE Transactions on Automatic Control · 2024-07-03 · 10 citations

  articleSenior author

  This article proposes a distributed algorithm for average consensus in a multiagent system under a fixed bidirectional communication topology, in the presence of untrustworthy (malicious) agents (nodes) that may try to influence the average consensus outcome by manipulating their updates. The proposed algorithm converges asymptotically to the average of the initial values of the trustworthy (nonmalicious) nodes, which we refer to as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">trustworthy average</i>, as long as the underlying topology that describes the information exchange among the trustworthy nodes is connected. We first present a distributed iterative algorithm that assumes that each node receives (at each iteration or periodically) side information about the trustworthiness of the other nodes, and it uses such trust assessments to determine whether or not to incorporate messages received from its neighbors, as well as to make proper adjustments in its calculation depending on whether a previously trustworthy neighbor becomes untrustworthy or vice-versa. We show that, as long as the trust assessments for each trustworthy node eventually reflect correctly the status (trustworthy or untrustworthy) of its neighboring nodes, the algorithm guarantees asymptotic convergence to the trustworthy average. We subsequently discuss how the proposed algorithm can be enhanced with functionality that enables each node to obtain trust assessments about its neighbors by utilizing information that it receives from its two-hop neighbors at infrequent, perhaps randomly chosen, time instants.

  PublisherDOI

• Auxiliary Signal-Based Distance Protection in Inverter-Dominated Power Systems

  2024-06-25 · 2 citations

  articleSenior author

  Power system protection schemes today rely on currents rising by several orders of magnitude when faults oc-cur. In inverter-dominated power systems, a fault current might be just a few percent larger than normal, making fault detection more difficult. One solution is for the inverter to slightly perturb its output current and/or voltage, i.e., to inject an auxiliary signal, so as to make the system's behavior under faults easier to distinguish from normal. In this paper, we optimize auxiliary signals for fault detection with distance relays. We begin with a standard auxiliary signal design problem for generic static systems. We use duality to reformulate the problem as a bilinear program, which we solve using the convex-concave procedure. We implement the framework in an example based on distance protection, in which the auxiliary signal is negative sequence current.

  PublisherDOI

• Distributed Average Consensus in Open Multi-Agent Systems

  2024-12-16 · 3 citations

  articleSenior author

  In this paper, we consider the problem of distributed average consensus in multi-agent systems, where each agent can come in or move out of the system, possibly multiple times. In the literature, such systems are referred to as open multi-agent systems. A typical goal in such settings is to use an iterative distributed algorithm to calculate the average of some quantities of interest each agent possesses, which can be crucial in many estimation, control, or optimization applications. We consider an open multi-agent setting and propose a distributed algorithm that allows the participating agents to track their average. More specifically, if the set of agents remaining in the computation eventually settles to a certain subset of agents, then the proposed algorithm allows them (under some mild connectivity conditions) to asymptotically reach consensus to the average of the quantities of interest these remaining agents hold. Analysis and numerical examples to illustrate the operation of the proposed algorithm are also provided.

  PublisherDOI

• Robustified Distributed Average Consensus

  Elsevier eBooks · 2024-12-14

  book-chapter
  PublisherDOI

Recent grants

• Managing Intermittency in Planning and Operations of Power

  NSF · $349k · 2009–2013

• EAGER-DynamicData: A Scalable Framework for Data-Driven Real-Time Event Detection in Power Systems

  NSF · $185k · 2015–2018

• CAREER: Reliability Engineering for Electrical Energy Systems 2020: Smart Grid Applications and Beyond

  NSF · $400k · 2010–2016

Frequent coauthors

• Christoforos N. Hadjicostis

  University of Cyprus

  66 shared

• Daniel Liberzon

  University of Illinois Urbana-Champaign

  50 shared

• Venugopal V. Veeravalli

  University of Illinois Urbana-Champaign

  49 shared

• Subhonmesh Bose

  University of Illinois Urbana-Champaign

  42 shared

• Peter W. Sauer

  University of Illinois Urbana-Champaign

  41 shared

• Georgios Fellouris

  University of Illinois Urbana-Champaign

  41 shared

• Bronwyn H. Bradshaw‐Hajek

  University of South Australia

  41 shared

• N. Minh

  VinUniversity

  41 shared

Awards & honors

• M. Stanley Helm Professorship in Electrical and Computer Eng…