arXiv subjects

Alejandro D. Domínguez-García

Publications and source records attributed to Alejandro D. Domínguez-García.

10 recordsLinked to original sources

arXiv2026

Reachability-based Time-domain Distance Protection

Distance relays detect faults on transmission lines from local voltage and current measurements. In this paper, we characterize the set of time-domain measurements a distance relay can observe during a fault as a reachable set. We define corresponding fault tests in terms of set-based state estimation. This allows us to model the full network as an RLC circuit with voltage and current sources. In general, computing reachable sets and set-based state estimates is intractable. For each fault type, we construct a reduced-order, two-dimensional model in terms of the apparent voltage and current seen by the relay. This makes all computations efficient, aligns with standard quantities in distance protection, and allows us to define instantaneous fault tests in terms of unsolved differential equations.

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arXiv2026

Distance characteristics for incremental quantities

We derive distance relay characteristics in terms of incremental phasors. We use a circuit model of the network to estimate the incremental remote current. If we assume that all sources are stationary, i.e., remain periodic shortly after a fault, then the incremental remote current, and thus the characteristics, do not depend on the real-time voltages or current injections of the sources.

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arXiv2025

Geometry of Distance Protection

Distance relays detect faults on transmission lines. They face uncertainty from the fault's location and resistance, as well as the current from the line's remote terminal. In this paper, we aggregate this uncertainty with the Minkowski sum. This allows us to explicitly model the power grid surrounding the relay's line, and in turn accommodate any mix of synchronous machines and inverter-based resources. To make the relay's task easier, inverters can inject perturbations, or auxiliary signals, such as negative-sequence current. We use Farkas' lemma to construct an optimization for designing inverter auxiliary signals.

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arXiv2023

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

Power system protection schemes today rely on currents rising by several orders of magnitude when faults occur. 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.

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arXiv2019

Data-driven Coordination of Distributed Energy Resources for Active Power Provision

In this paper, we propose a framework for coordinating distributed energy resources (DERs) connected to a power distribution system, the model of which is not completely known, so that they collectively provide a specified amount of active power to the bulk power system as quantified by the power exchange between both systems at the bus interconnecting them, while respecting distribution line capacity limits. The proposed framework consists of (i) a linear time-varying input-output (IO) system model that represents the relation between the DER active power injections (inputs), and the total active power exchanged between the distribution and bulk power systems (output); (ii) an estimator that aims to estimate the IO model parameters, and (iii) a controller that determines the optimal DER active power injections so the power exchanged between both systems equals to the specified amount at a minimum generating cost. We formulate the estimation problem as a quadratic program with box constraints and solve it using the projected gradient descent algorithm. To resolve the potential issue of collinearity in the measurements used by the estimator, we introduce random perturbations in the DER active power injections during the estimation process. Using the estimated IO model, the optimal DER coordination problem to be solved by the controller can be formulated as a convex optimization problem, which can be solved easily. The effectiveness of the framework is validated via numerical simulations using the IEEE 123-bus distribution test feeder.

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arXiv2019

Optimal Tap Setting of Voltage Regulation Transformers Using Batch Reinforcement Learning

In this paper, we address the problem of setting the tap positions of load tap changers (LTCs) for voltage regulation in radial power distribution systems under uncertain load dynamics. The objective is to find a policy to determine the tap positions that only uses measurements of voltage magnitudes and topology information so as to minimize the voltage deviation across the system. We formulate this problem as a Markov decision process (MDP), and propose a batch reinforcement learning (RL) algorithm to solve it. By taking advantage of a linearized power flow model, we propose an effective algorithm to estimate the voltage magnitudes under different tap settings, which allows the RL algorithm to explore the state and action spaces freely offline without impacting the system operation. To circumvent the "curse of dimensionality" resulted from the large state and action spaces, we propose a sequential learning algorithm to learn an action-value function for each LTC, based on which the optimal tap positions can be directly determined. The effectiveness of the proposed algorithm is validated via numerical simulations on the IEEE 13-bus and 123-bus distribution test feeders.

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arXiv2019

Data-driven Voltage Regulation in Radial Power Distribution Systems

In this paper, we develop a data-driven voltage regulation framework for distributed energy resources (DERs) in a balanced radial power distribution system. The objective is to determine optimal DER power injections that minimize the voltage deviations from a desirable voltage range without knowing a complete power distribution system model a priori. The nonlinear relationship between the voltage magnitudes and the power injections in the power distribution system is approximated by a linear model, the parameters of which---referred to as the voltage sensitivities---can be computed directly using information on the topology and the line parameters. Assuming the knowledge of feasible topology configurations and distribution line resistance-to-reactance ratios, the true topology configuration and corresponding line parameters can be estimated effectively using a few sets of measurements on voltage magnitudes and power injections. Using the estimated voltage sensitivities, the optimal DER power injections can be readily determined by solving a convex optimization problem. The proposed framework is intrinsically adaptive to changes in system conditions such as unknown topology reconfiguration due to its data-driven nature. The effectiveness and efficiency of the proposed framework is validated via numerical simulations on the IEEE 123-bus distribution test feeder.

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arXiv2018

Utilization of Water Supply Networks for Harvesting Renewable Energy

Renewable surplus power is increasing due to the increasing penetration of these intermittent resources. In practice, electric grid operators either curtail the surplus energy resulting from renewable-based generations or utilize energy storage resources to absorb it. In this paper, we propose a framework for utilizing water pumps and tanks in water supply networks to absorb the surplus electrical energy resulting from renewable-based electricity generation resources in the electrical grid. We model water supply networks analytically, and propose a two-step procedure that utilizes the water tanks in the water supply network to harvest the surplus energy from an electrical grid. In each step, the water network operator needs to solve an optimization problem that is non-convex. To compute optimal pump schedules and water flows, we develop a second-order cone relaxation and an approximation technique that enable us to transform the proposed problems into mixed-integer second-order cone programs. We then provide the conditions under which the proposed relaxation is exact, and present an algorithm for constructing an exact solution to the original problem from a solution to the relaxed problem. We demonstrate the effectiveness of the proposed framework via numerical simulations.

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arXiv2018

Adaptive Coordination of Distributed Energy Resources in Lossy Power Distribution Systems

This paper is concerned with the problem of coordinating a set of distributed energy resources (DERs) in a lossy power distribution system to provide frequency regulation services to a bulk power grid with the explicit consideration of system losses. To this end, we formulate the problem as an optimization problem, the objective of which is to minimize some cost function subject to a set of constraints. The formulation requires knowledge of incremental total system losses, which we approximate using the so-called loss factors (LFs) that explicitly capture the impacts of both active and reactive power injections on system losses. The LFs are estimated recursively using power injection measurements; thus, they are adaptive to various phenomena that impact the power system operation. Numerical simulation on a 33-bus distribution test feeder validated the effectiveness of the proposed framework.

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arXiv2017

A Data-driven Voltage Control Framework for Power Distribution Systems

In this paper, we address the problem of coordinating a set of distributed energy resources (DERs) to regulate voltage in power distribution systems to desired levels. To this end, we formulate the voltage control problem as an optimization problem, the objective of which is to determine the optimal DER power injections that minimize the voltage deviations from desirable voltage levels subject to a set of constraints. The nonlinear relationship between the voltage magnitudes and the nodal power injections is approximated by a linear model, the parameters of which can be estimated in real-time efficiently using measurements. In particular, the parameter estimation requires much fewer data by exploiting the structural characteristics of the power distribution system. As such, the voltage control framework is intrinsically adaptive to parameter changes. Numerical studies on the IEEE 37-bus power distribution test feeder validated the effectiveness of the propose framework.

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