Short-Term Photovoltaic Power Forecasting Using a Bi-LSTM Neural Network Optimized by Hybrid Algorit...
Short-Term Photovoltaic Power Forecasting Using a Bi-LSTM Neural Network Optimized by Hybrid Algorithms
About this item
Full title
Author / Creator
Wang, Jibo , Zhang, Zihao , Xu, Wenhao , Li, Yijin and Niu, Geng
Publisher
Basel: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Basel: MDPI AG
Subjects
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Scope and Contents
Contents
Photovoltaic (PV) power generation is characterized by high fluctuation and intermittency. The accurate forecasting of PV power is crucial for optimizing grid operation and scheduling. Thus, a novel short-term PV power-forecasting method based on genetic algorithm-adaptive multi-objective differential evolution (GA-AMODE)-optimized bidirectional lo...
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Full title
Short-Term Photovoltaic Power Forecasting Using a Bi-LSTM Neural Network Optimized by Hybrid Algorithms
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Author / Creator
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Record Identifier
TN_cdi_proquest_journals_3223942952
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3223942952
Other Identifiers
ISSN
2071-1050
E-ISSN
2071-1050
DOI
10.3390/su17125277
