Sailing Towards Efficiency: A Variational Mode Decomposition Based Approach to Forecasting Shipboard Electrical Power Consumption

This paper presents a Variational Mode Decomposition based (VMD) approach for multi-step prediction of univariate electrical load on large passenger ships. Specifically, VMD is adopted as a pre-processing step to enhance the performance of Long Short-Term Memory (LSTM)-based forecasting models. It is demonstrated that decomposing the signal into intrinsic mode functions via VMD before forecasting significantly outperforms (up to a 66% error reduction) the conventional approach of feeding the entire signal into the forecasting model. The resulting findings suggest that the integration of VMD into the forecasting pipeline could yield a useful tool for a more accurate and efficient power management on large passenger ships.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/esars-itec60450.2024.10819873
Citations
3
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
0.98
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article

Sailing Towards Efficiency: A Variational Mode Decomposition Based Approach to Forecasting Shipboard Electrical Power Consumption

Paolo Fazzini, Matteo Diez, Giuseppe La Tona, Maria Carmela Di Piazza
3 citations
Machine Fault Diagnosis Techniques
0.98
article

Sailing Towards Efficiency: A Variational Mode Decomposition Based Approach to Forecasting Shipboard Electrical Power Consumption

Paolo Fazzini, Matteo Diez, Giuseppe La Tona, Maria Carmela Di Piazza
article en
3 citations

Abstract

This paper presents a Variational Mode Decomposition based (VMD) approach for multi-step prediction of univariate electrical load on large passenger ships. Specifically, VMD is adopted as a pre-processing step to enhance the performance of Long Short-Term Memory (LSTM)-based forecasting models. It is demonstrated that decomposing the signal into intrinsic mode functions via VMD before forecasting significantly outperforms (up to a 66% error reduction) the conventional approach of feeding the entire signal into the forecasting model. The resulting findings suggest that the integration of VMD into the forecasting pipeline could yield a useful tool for a more accurate and efficient power management on large passenger ships.

Institute of Marine Engineering (IT)
Affordable and clean energy
Openalex Percentile: Top 22%
Machine Fault Diagnosis Techniques
0.98
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