Electric Utility
The work starts with a short overview of grid requirements for photovoltaic (PV) systems and control structures of grid-connected PV power systems. Advanced control strategies for PV power systems are presented next, to enhance the integration of this technology. The aim of this work is to investigate the response of the three-phase PV systems during symmetrical and asymmetrical grid faults.
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The given data contains the results from laboratory trials related to the paper "Optimizing Congestion Management andEnhancing Resilience in Low-Voltage Grids Using OPF and MPC Control Algorithms Through Edge Computing and IEC 61850 Standards" currently in publication in IEEE Access.
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This repository contains the datasets produced using different data generation strategies to train data driven models (e.g., decision trees, gradient tree boosting, and deep neural networks), and to evaluate their performances. The data generation strategies are described, and the results are presented in the conference paper: "Training Data Generation Strategies for Data-driven Security Assessment of Low Voltage Smart Grids" J. Cuenca, E. Aldea, E. Le Guern-Dall'o, R. Féraud, G. Camilleri, and A. Blavette. IEEE ISGT EU 2024, Dubrovnik, Croatia, Oct 2024.
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This paper presents a method for modeling and simulating three-phase grid-connected solid-oxide fuel cell systems in the Matlab/Simulink environment. The approach is utilized to analyze the interaction between solid-oxide fuel cells and the electrical power system, focusing on understanding the dynamics of the electrochemical reaction and its impact on the performance of grid-connected fuel cell systems. The results highlight the effectiveness of the proposed method in accurately modeling and operating three-phase grid-connected solid-oxide fuel cell systems.
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This dataset provides a comprehensive load flow analysis of the Dhaka Grid Circle in Bangladesh, based on data from the year 2018 and conducted using the Power System Analysis Toolbox (PSAT). The analysis includes detailed information on power generation units, transmission line parameters, load data, transformer specifications, and shunt capacitors. The dataset features results obtained from different load flow methods, including the Newton-Raphson and Fast Decoupled methods, with and without the application of a Static Var Compensator (SVC).
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Electric Vehicles Charging Station with Photovoltaic Panels
This dataset contains the model and simulation output results in Matlab/Simulink of a three-phase grid-connected charging station with PV panels for electric vehicles realized in a work submitted to the 13th IEEE International Conference and Exposition on Electrical and Power Engineering EPEi 2024, Iasi, Romania, October 17-19, 2024 (https://www.epe.tuiasi.ro/).
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This dataset contains the Matlab code of the nonlinear state-space model of a power electronics-dominated grid. A power grid with 3 grid following converters is taken under consideration, following the publication:
F. Cecati, R. Zhu, M. Liserre and X. Wang, "Nonlinear Modular State-Space Modeling of Power-Electronics-Based Power Systems," in IEEE Transactions on Power Electronics, vol. 37, no. 5, pp. 6102-6115, May 2022, doi: 10.1109/TPEL.2021.3127746.
Abstract of the paper:
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This study is utilized for submodule open-circuit fault detection uncertainty analysis of modular multilevel converters. The dataset consists of 8 uncertainty factors and 15 system variables under four operation scenarios. The 1000 sets of uncertainty factor samples are generated randomly as initial configuration of the system. The 15 system variables are obtained by 1000 Monte Carlo simulations. We found that there are 153 residual samples exceeded the threshold of 0.8, which indicated a high false alarm rate.
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