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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1724
Title: Remaining useful life prediction of Solar Panels in the Microgrid using combination of CNN and LSTM approaches
Authors: Thai Hoang Tam 
Keywords: PV system;Blocking diode;Bypass diode;Lifetime consumption;CNN;LSTM;SSO
Issue Date: 2017
Abstract: 
The thesis shows some short-term prediction models using a combination of Convolutional Neural Network (CNN) and long short-term memory (LSTM) network with the SSO technique for the remaining useful life (RUL) or lifetime consumption (LC) of a PV system in a microgrid. This thesis also covers fundamental knowledge of a PV system to understand which factors, and components can affect the lifespan of a PV system. The main goal of the thesis is to try different machine-learning methods for the short-term (one day ahead) prediction model and suggest the best model for each type of dataset
URI(1): https://epub.vgu.edu.vn/handle/dlibvgu/1724
Rights: Attribution-NonCommercial 4.0 International
Appears in Collections:Computer Science (CS)

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