Power Electronics
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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Health degradation issues in automotive power electronics converter systems (PECs) arise due to repetitive thermomechanical stress experienced during real-world vehicle operation. This stress, caused by heat generated during semiconductor operation within PECs, leads to the degradation of semiconductor's operating life. Estimating the power semiconductor junction temperature (Tj) is crucial for assessing semiconductor degradation in operation. Although physics-of-failure-based models can estimate Tj, they require substantial computational power.
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A PSCAD simulation model of direct-drive wind farm connected to the grid via VSC-HVDC is provided. Because there are a large number of power electronic devices and complex multi-time scale control links in the system, there is mutual coupling between power electronic devices or between power electronic devices and the power grid, which may lead to the risk of oscillation in the wide-band range from several hertz to hundreds of hertz.
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<p>Abstract – This paper shows an overview of the recent developments in the field of Electric Vehicles (EVs), the integration of EVs and Smart Cars, the battery technology and the power electronics in EVs. Over the past decades, the automotive industry has faced growing challenges, including environmental concerns and the finite amount of fuel resources that mainly includes petrol and diesel. In response to these challenges, Electric Vehicles (EVs) have emerged as sustainable alternative, promising reduced emissions and increased energy efficiency.
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Despite numerous advantages of space vector pulse width modulation (SVPWM) methods, their implementation on multilevel inverters (MLI) is onerous. Due to the ever-increasing use of MLIs in power electronic applications, it is essential to implement efficient modulation procedures aiming to keep control sampling periods sufficiently short. Here, a novel and straightforward SVPWM Strategy is introduced, which uses algebraic functions throughout the procedure and avoids using hardware-consuming trigonometric functions. Look-up tables and region detection are no more necessary.
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Space vector pulse width modulation (SVPWM) is a superior switching technique offering several benefits for power electronic inverters. However, concerning multilevel inverters (MLIs), implementing SVPWM is a demanding and time-consuming task because it deals with the six sectors of the space vector modulation (SVM) plane and numerous regions and vectors. Several research works in the literature tried to simplify SVPWM implementation for MLIs.
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The Inverter Fault Diagnosis dataset is a comprehensive collection of data aimed at facilitating research and development in the field of fault diagnosis for solar integrated grid-side three-phase inverters. This dataset includes three key features, namely Ea, Eb, and Ec, representing the energy calculated from the fault currents for phases A, B, and C, respectively.
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