Hybrid ship unit commitment with demand prediction and model predictive control

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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2020-09-11
Major/Subject
Mcode
Degree programme
Language
en
Pages
Series
Energies, Volume 13, issue 18
Abstract
We present a novel methodology for the control of power unit commitment in complex ship energy systems. The usage of this method is demonstrated with a case study, where measured data was used from a cruise ship operating in the Caribbean and the Mediterranean. The ship’s energy system is conceptualized to feature a fuel cell and a battery along standard diesel generating sets for the purpose of reducing local emissions near coasts. The developed method is formulated as a model predictive control (MPC) problem, where a novel 2-stage predictive model is used to predict power demand, and a mixed-integer linear programming (MILP) model is used to solve unit commitment according to the prediction. The performance of the methodology is compared to fully optimal control, which was simulated by optimizing unit commitment for entire measured power demand profiles of trips. As a result, it can be stated that the developed methodology achieves close to optimal unit commitment control for the conceptualized energy system. Furthermore, the predictive model is formulated so that it returns probability estimates of future power demand rather than point estimates. This opens up the possibility for using stochastic or robust optimization methods for unit commitment optimization in future studies.
Description
Keywords
Gaussian Process, Maritime, Mixed-integer linear programming, Model predictive control, Optimization, Predictive model
Other note
Citation
Huotari, J, Ritari, A, Vepsäläinen, J & Tammi, K 2020, ' Hybrid ship unit commitment with demand prediction and model predictive control ', Energies, vol. 13, no. 18, 4748 . https://doi.org/10.3390/en13184748