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First Name: 
Xuan
Last Name: 
Liu

Datasets & Competitions

Conversion loss modeling plays a crucial role in hybrid AC/DC microgrid (MG) energy management (EM). However, accurate calculation of the conversion losses is often very costly. Additionally, existing surrogate models typically rely on fixed-voltage DC buses, leading to excessive voltage magnitudes. To overcome these limitations, we propose surrogate models based on piecewise linear neural networks (NNs) that estimate conversion losses using converter power and variable-voltage DC buses.

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This dataset is created for neural network-based surrogate modeling of the power conversion losses. The dataset includes four sets of data (for AC/DC conversion losses under inversion/rectification moes and DC/DC conversion losses during battery charging/discharging, respectively) for the neural network. The raw data is generated using high fidelity analytical models. 

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40 Views

This dataset is created for neural network-based surrogate modeling of the power conversion losses. The dataset includes two sets of training and test data (for AC/DC and DC/DC converters respectively) for the neural network. The raw data is generated using PLECS Blockset Packages in MATLAB-Simulink environment. 

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83 Views