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Noon report data uncertainty

Smith, TWP; Aldous, L; Bucknall, R; (2013) Noon report data uncertainty. In: Low Carbon Shipping Conference. Low Carbon Shipping Conference: London, UK. Green open access

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Abstract

Noon report data is a low resolution dataset (sampling frequency of approximately 24 hours) from which it is possible to extract the principal variables required to define the ship’s performance in terms of fuel consumption. There are increasing economic and environmental incentives for ship owners and operators to develop tools to optimise operational decisions with the aim of reducing fuel consumption and/or maximising profit. Further, a ships current performance needs to be measured in order for fuel savings from technological interventions to be assessed. These tools and measurements may be based on models developed from historical trends that are extracted from noon reports; however there is inherent uncertainty in this dataset. As a prerequisite the uncertainty must be quantified to understand fully the potential and limitations of predictive models from which operational tools may be designed and of statistical models from which technological interventions are assessed. This paper initially presents a method for quantifying the uncertainty in reported fuel consumption using between two months and one year’s worth of data from 89 ships. The subsequently calculated confidence is then compared to the uncertainty in the data acquired from an on board continuous monitoring system.

Type: Proceedings paper
Title: Noon report data uncertainty
Event: Low Carbon Shipping 2013
Location: London
Dates: 2013-09-09 - 2013-09-10
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.lowcarbonshipping.co.uk/
Language: English
Keywords: Shipping, Uncertainty, Energy efficiency
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/1413453
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