Juan Ospina

TL;DR: In this article, the authors provide a comprehensive overview of the cyber-physical energy systems (CPS) security landscape with an emphasis on CPES, and demonstrate a threat modeling methodology to accurately represent the CPS elements, their interdependencies, as well as the possible attack entry points and system vulnerabilities.

TL;DR: A novel forecasting model designed to accurately forecast the PV power output for both large-scale and small-scale PV systems is proposed and improved the forecasting accuracy significantly in the metrics used to compare with other models while reducing the number of features needed to perform the forecasting operation.

TL;DR: In this paper, the authors proposed a cybersecurity assessment approach designed to assess the cyberphysical security of electric power systems (EPS), taking into consideration the intermittent generation of RES, vulnerabilities introduced by microprocessor-based electronic information and operational technology (IT/OT) devices, and contingency analysis results.

TL;DR: The topics presented in this paper include novel power-distribution architectures, protection techniques considering large renewable integration in smart grids, wireless charging in electric vehicles, simultaneous power and information transmission, multi-hop network-based coordination, power technologies for renewable energy and smart transformer, CPS reliability, transactive smart railway grid, and real-time simulation of shipboard power systems.

TL;DR: The proposed model uses sampling-based model predictive control (SBMPC), together with the real-time price of energy and forecasts of PV and load power, to allocate the dispatch of the available distributed energy resources (DERs) while minimizing the overall cost.