A Statistical Approach to Ship Fuel Consumption Monitoring

Appl Stoch Models Bus & Ind

et al. 2019

Self Cite

Shipping companies are forced by the current EU regulation to set up a system for monitoring, reporting, and verification of harmful emissions from their fleet. In this regulatory background, data collected from onboard sensors can be utilized to assess the ship's operating conditions and quantify its CO2 emission levels. The standard approach for analyzing such data sets is based on summarizing the measurements obtained during a given voyage by the average value. However, this compression step may lead to significant information loss since most variables present a dynamic profile that is not well approximated by the average value only. Therefore, in this work, we test two feature‐oriented methods that are able to extract additional features, namely, profile‐driven features (PdF) and statistical pattern analysis (SPA). A real data set from a Ro‐Pax ship is then considered to test the selected methods. The data set is segregated according to the voyage distance into short, medium, and long routes. Both PdF and SPA are compared with the standard approach, and the results demonstrate the benefits of employing more systematic and informative feature‐oriented methods. For the short route, no method is able to predict CO2 emissions in a satisfactory way, whereas for the medium and long routes, regression models built using features obtained from both PdF and SPA improve their prediction performance. In particular, for the long route, the standard approach failed to provide reasonably good predictions.

“…In the following paragraphs, we provide more details regarding the variables collected during each voyage. Further details can be found in Bocchetti et al…”

Section: Methodsmentioning

confidence: 99%

Section: Data Descriptionmentioning

confidence: 99%

Predicting ships' CO₂emissions using feature‐oriented methods

Reis

Rendall

Appl Stoch Models Bus & Ind

et al. 2019

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“…The first variable is the SOG, which is known as the most important predictor of the FCPH . Moreover, FDA recommends to explore instantaneous information not only about variables but also about their derivatives, as they often give useful additional information.…”

Section: Real Case Studymentioning

confidence: 99%

Analysis of profiles for monitoring of modern ship performance via partial least squares methods

Lepore

Quality & Reliability Eng

Capezza

2018

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Shipping operators are nowadays facing the challenge of monitoring ship performance based on operational data. This is triggered by the compelling air pollution regulation EU 2015/757 of the European Parliament, which aims from January 2018 to monitoring, reporting, and verification of all harmful emissions of ships operating in the European Economic Area. On the other hand, the continuous acquisition of operational data, which is performed on most of the modern ships, urgently calls for the application of new and opportune statistical methods able to deal with high‐dimensional data. Ship operating conditions can be in fact described by sensor signals collected throughout each voyage and stored as profiles. In this paper, the latter are analyzed through multiway partial least squares regression of the average fuel consumption per hour over each voyage, which is chosen as scalar performance response, being proportional to harmful emissions. The proposed approach is able to monitor profiles with different length at different voyages. Nevertheless, it is capable of indicating at which instant anomalies may have occurred in ship operating conditions. The proposed approach is shown to be able to furnish clear indications for supporting prognosis of faults. By means of real data acquired from a Ro‐Pax cruise ship owned by the shipping company Grimaldi Group, a different multilinear version that explicitly takes into account the 3‐way structure of the data is also compared with the proposed approach.

“…Through a multiple linear regression, the procedure provides point and interval prediction of the fuel consumption that can be used to control potential anomalous voyages. In this way, the technical management of a shipping company can be rationally supported in making decision on ship energy efficiency …”

Section: Introductionmentioning

confidence: 99%

A Procedure for Predicting and Controlling the Ship Fuel Consumption: Its Implementation and Test

Erto

Lepore

Quality & Reliability Eng

et al. 2015

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In light of the International Maritime Organization guidelines, the new Regulation of the European Union urges shipping companies to set up a system for monitoring, reporting and verification of CO2 emissions based on ship fuel consumption. However, in nowadays market, there is a lack of techniques for fuel consumption monitoring that can be adopted in a real environment. The proposed procedure overcomes the use of Speed–Power curves, which are commonly utilized in the Naval Architecture, by means of a multiple linear regression model that exploits the navigation information usually available in modern ships. This procedure can be used both to alert technical management of a shipping company for anomalous fuel consumption and to quantify the fuel consumption reduction connected with any specific policy adopted to improve energy efficiency. Therefore, this can be particularly profitable for shipping companies and operators in order to claim for carbon credits. The proposed approach is currently implemented by the Energy Saving Technical Department of the Grimaldi Group on a Ro‐Ro Pax ship. Copyright © 2015 John Wiley & Sons, Ltd.