Profile

Ayrton Pablo Almada Jimenez

PhD Candidate in Applied Mathematics | Researcher in Power Grids

About Me

I am a Ph.D. student at The University of Arizona, supervised by Dr. Michael Chertkov and Dr. Laurent Pagnier, specializing in the mathematical modeling of power grid systems. My work integrates probabilistic and statistical methods with object-oriented programming to study complex energy infrastructures. I have engaged in collaborative research at Los Alamos National Laboratory and provided consulting services for NOGA, the Power System Operator of Israel. These experiences have strengthened my ability to work across industry, national laboratories, and academic environments, contributing to multidisciplinary teams focused on modernizing and optimizing power systems. Looking ahead, I plan to continue my graduate studies with a focus on artificial intelligence, machine learning, and operations research. I am particularly interested in data-augmentation methodologies, including natural language processing, diffusion models, and large language models, and aim to apply these tools to advance research at the intersection of energy systems and intelligent algorithms.

Publications

Projects

Real-Time Stochastic Assessment of Dynamic N-1 Grid Contingencies: Transient Stability and Thermal Risk in Power Networks.

This project develops a computational framework for analyzing the dynamic response of power transmission networks under N-1 contingency scenarios, with a focus on transient stability and line overheating risk. The system models the grid as a weighted graph and uses the linearized swing equation to capture the evolution of generator phase angles and frequency deviations following transmission line faults. The implementation combines closed-form analytical solutions with stochastic simulations to evaluate system behavior across fault, faulted, and post-fault regimes. Analytical methods enable efficient time-domain evaluation of linearized dynamics, while stochastic simulations—via Euler–Maruyama integration—incorporate variability from load fluctuations and renewable generation. A key component of the framework is the modeling of fault events through time-dependent network topology changes, allowing detailed analysis of disturbance propagation. The project also introduces overheating indicators based on phase differences to quantify thermal stress on transmission lines, providing insight into potential cascading failures. Monte Carlo simulations are used to generate distributions of system responses under randomized fault scenarios, enabling identification of vulnerable network components and probabilistic risk assessment. The framework supports large-scale experimentation and offers a systematic approach to studying resilience and stability in modern power grids. Project's Repository

System-Agnostic Localization of Oscillations (SALO): Identifying Sources of Forced Dynamics in Complex Networks.

This project implements the System-Agnostic Localization of Oscillations (SALO) algorithm to identify the origin and frequency of forced oscillations in complex dynamical networks. Using time series data of phase angles and frequencies from interconnected agents, the method formulates and solves an optimization problem to infer the most likely source and characteristics of external forcing. The approach combines spectral analysis (via Fourier transforms) with maximum likelihood estimation to reconstruct the underlying system dynamics, including interaction structure, damping parameters, and forcing amplitudes. Both standard and relaxed formulations of the SALO algorithm are implemented, along with parallelized versions to enable efficient analysis of large-scale systems. The framework is designed to be system-agnostic, requiring only observable time series data, making it broadly applicable to networked systems such as power grids, coupled oscillators, and other high-dimensional dynamical systems. By enabling accurate localization of oscillatory disturbances, this work supports improved monitoring, diagnostics, and stability analysis in complex infrastructures. Project's Repository

Contact

Email: p.ayrtonalmada@gmail.com

LinkedIn: Ayrton Almada

GitHub: AyrtonAlmada

Resume: AyrtonAlmadaResume