A research on the energy efficiency operational indicator EEOI calculation tool on M/V NSU JUSTICE of VINIC transportation company, Vietnam

Tran, Tien Anh

doi:10.1016/j.joes.2017.01.001

Cited by 40 publications

(13 citation statements)

References 2 publications

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“…The research key of the data clustering method is a classification of big data into a separate group in which each group will contain the data that is the same characteristic together. Even though there is an increasing interest in the use of clustering methods in pattern recognition [16], image processing [17], and information retrieval [18,19], clustering has a rich history in other disciplines [20] such as biology, geography, geology, archeology, psychology, psychiatry, marketing, and finance.…”

Section: Data Clustering Methodsmentioning

confidence: 99%

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Selection of the Best Optimal Operational Parameters to Reduce the Fuel Consumption Based on the Clustering Method of Artificial Neural Networks

Tran¹

2019

Energy-Efficient Approaches in Industrial Applications

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The international shipping transportation industry becomes gradually important in the field of national economic development. It is explained by means of an increase in a number of ships nowadays, and it also expands the operating routes on international routes including the North of America, Baltic Sea, and emission control areas (ECAs). The energy efficiency of ships is very necessary to respond to the regulations of the International Maritime Organization (IMO). Moreover, the operational parameters have a significant meaning in supervising and monitoring the engines on a ship. They completely depend on the navigation environment condition. So, selecting the optimal operational parameters' component is a target of this study. In this chapter, a study on the energy efficiency of ship by decreasing the fuel consumption of the main engine for a certain ship namely M/V NSU JUSTICE 250,000 DWT of VINIC shipping transportation company in Vietnam is by the method of artificial neural networks (ANNs). In particular, these studies were conducted by the classification and clustering method of artificial neural networks (ANNs) based on the experimental database of M/V NSU JUSTICE 250,000 DWT. The results of this chapter will solve the energy efficiency issue on ships nowadays and contribute the aims in the next studies.

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Section: Data Clustering Methodsmentioning

confidence: 99%

“…Furthermore, there are some recent researches which concentrate on this index through their studies. A tool of EEOI calculation for bulk carriers of VINIC shipping transportation is carried out by Tran [16]. Hence, the optimization of this index is also conducted by him [17].…”

Section: Eeoi Measurementioning

confidence: 99%

Selection of the Best Optimal Operational Parameters to Reduce the Fuel Consumption Based on the Clustering Method of Artificial Neural Networks

Tran¹

2019

Energy-Efficient Approaches in Industrial Applications

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“…Taking CO 2 emissions from ships in operation into consideration, IMO developed the Energy Efficiency Operational Indicator (EEOI) [35,36] as a tool for determining the energy efficiency of a ship and then monitoring during its operation. EEOI was defined as the ratio of the mass of CO 2 emitted by a ship to a specific unit of work.…”

Section: Introductionmentioning

confidence: 99%

A New Method of Determining Energy Efficiency Operational Indicator for Specialized Ships

et al. 2020

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Limitation of CO2 emission is one of the main goals and regulations introduced by the international institutions’ rules. In the case of ships using oil-related and gas fuels this problem is dealt with by the International Maritime Organization (IMO) introducing the methodology of Energy Efficiency Operational Indicator (EEOI) determining for ships being under exploitation. The methodology allows for determining EEOI for seven types of ships, for which the value of this index depends on the amount of transported cargo or number of passengers, type of and amount of fuel used, as well as distance travelled by the ship. Such a methodology cannot be used for the specialized ships, whose exploitation tasks are different to the ships of the trade fleet that transport the cargo or the passengers. The methodology allows for determining EEOI for seven types of ships and it does not include specialized ships. The article presents a new methodology of determining EEOI for specialized ships that takes the characteristics of their exploitation into consideration. The way of its use has been presented taking into account the results of exploitation studies carried out on the chosen research and training ship. Obtained results and their analysis allowed for energy efficiency assessment of research and training ships depending on exploitation tasks, voyage time, type of fuel used, distance travelled and ship’s speed. EEOI index value determines energy efficiency of the vessel power system that is directly connected to the amount of the liquid or gas fuel used and the amount of emitted CO2. The aim should be to minimalize the value of EEOI index through planning of the exploitation tasks realization order and adjusting the speed of the ship as well as realization time of particular exploitation tasks, in the case of specialized ships. The analysis results can also be used when managing energy efficiency of these types of ships.

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“…Measuring tools are important for implementing emission control policies and management plans. 7 The evaluation of these indices for particular vessels is of interest, 8 and sophisticated mathematical tools have been proposed to properly assess the reliability and carbon footprint of a shipping link. 9 In this framework, the efficiency of the electric generators 10 is an essential ingredient.…”

Section: Introductionmentioning

confidence: 99%

Analysis of key variables for energy efficiency in warships

Carrasco¹,

Bendaña

Paredes

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part M:

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The purpose of this work is to investigate the effect of environmental variables on the electric energy expenditure of a typical surface warship. Studies with similar objectives are much more frequent for merchant ships, but warship operations have peculiarities that will be emphasised. In particular, they spend large fractions of their life cycle at port, during which the vessel remains active. First, a discussion of the embarked systems is presented, pointing out the importance of auxiliary systems and, in particular, heating, ventilation and air conditioning. Quantitative estimates of the energy consumption of those systems are provided. Then, using data taken during real operations of a frigate of the Spanish Navy, correlations are computed between power consumption and different environmental variables. As a novelty, the analysis is carried out separating the different modes of operation of the ship. This leads to interesting conclusions, including a considerable positive correlation between seawater temperature and fuel consumption when the vessel is in port. The effect of a moored ship on the surrounding seawater temperature is studied by a numerical computation. The results suggest that the position of sea chests may be consequential for energy efficiency.

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A research on the energy efficiency operational indicator EEOI calculation tool on M/V NSU JUSTICE of VINIC transportation company, Vietnam

Cited by 40 publications

References 2 publications

Selection of the Best Optimal Operational Parameters to Reduce the Fuel Consumption Based on the Clustering Method of Artificial Neural Networks

Selection of the Best Optimal Operational Parameters to Reduce the Fuel Consumption Based on the Clustering Method of Artificial Neural Networks

A New Method of Determining Energy Efficiency Operational Indicator for Specialized Ships

Analysis of key variables for energy efficiency in warships

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