Energy efficiency estimation of a steam powered LNG tanker using normal operating data

A ship’s energy efficiency performance is generally estimated by conducting special sea trials of few hours under very controlled environmental conditions of calm sea, standard draft and optimum trim. This indicator is then used as the benchmark for future reference of the ship’s Energy Efficiency Performance (EEP). In practice, however, for greater part of operating life the ship operates in conditions which are far removed from original sea trial conditions and therefore comparing energy performance with benchmark performance indicator is not truly valid. In such situations a higher fuel consumption reading from the ship fuel meter may not be a true indicator of poor machinery performance or dirty underwater hull. Most likely, the reasons for higher fuel consumption may lie in factors other than the condition of hull and machinery, such as head wind, current, low load operations or incorrect trim [1]. Thus a better and more accurate approach to determine energy efficiency of the ship attributable only to main machinery and underwater hull condition will be to filter out the influence of all spurious and non-standard operating conditions from the ship’s fuel consumption [2]. The author in this paper identifies parameters of a suitable filter to be used on the daily report data of a typical LNG tanker of 33000 kW shaft power to remove effects of spurious and non-standard ship operations on its fuel consumption. The filtered daily report data has been then used to estimate actual fuel efficiency of the ship and compared with the sea trials benchmark performance. Results obtained using data filter show closer agreement with the benchmark EEP than obtained from the monthly mini trials. The data filtering method proposed in this paper has the advantage of using the actual operational data of the ship and thus saving cost of conducting special sea trials to estimate ship EEP. The agreement between estimated results and special sea trials EEP is expected to improve further with use of better and more accurate filtering techniques.

Abstract licence: CC BY

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