Sailing Towards Efficiency: A Variational Mode Decomposition Based Approach to Forecasting Shipboard Electrical Power Consumption
- 26 November 2024
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-6
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.Keywords
This publication has 18 references indexed in Scilit:
- Short‐term electrical load forecasting model based on multi‐dimensional meteorological information spatio‐temporal fusion and optimized variational mode decompositionIET Generation, Transmission & Distribution, 2023
- Day-ahead forecasting of residential electric power consumption for energy management using Long Short-Term Memory encoder–decoder modelMathematics and Computers in Simulation, 2023
- Network traffic prediction model based on improved VMD and PSO‐ELMInternational Journal of Communication Systems, 2023
- A Comprehensive Review on Ensemble Solar Power Forecasting AlgorithmsJournal of Electrical Engineering & Technology, 2023
- Short-term load forecasting based on IPSO-DBiLSTM network with variational mode decomposition and attention mechanismApplied Intelligence, 2022
- De-noising magnetotelluric data using variational mode decomposition combined with mathematical morphology filtering and wavelet thresholdingJournal of Applied Geophysics, 2022
- Short-term PV power forecasting using variational mode decomposition integrated with Ant colony optimization and neural networkEnergy Reports, 2022
- Short-term load forecasting method with variational mode decomposition and stacking model fusionSustainable Energy, Grids and Networks, 2022
- Electric Load Forecasting by Hybrid Self-Recurrent Support Vector Regression Model With Variational Mode Decomposition and Improved Cuckoo Search AlgorithmIEEE Access, 2020
- The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysisProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 1998