Big data-based evaluation system for fuel consumption and greenhouse gas emission of ship

Abstract

A big data-based evaluation system for fuel consumption and greenhouse gas emission of a ship according to an embodiment of the present invention includes: a ship specification DB (110); a ship location information DB (120); a marine environment DB (130); a port information DB (140); a global course DB (150); a required horsepower estimation unit (160) which estimates required horsepower when sailing a corresponding sailing route by applying a resistance component calculated by analyzing ship specification information from the ship specification DB (110), ship location information from the ship location information DB (120), marine environment information of a sailing sea area from the marine environment DB (130), port area information from the port information DB (140), and course information from the global course DB (150); and an index calculation unit (170) which analyzes ship specification information extracted from the ship specification DB (110), marine environment information of a sailing sea area extracted from the marine environment DB (130), ship location information extracted from the ship location information DB (120), port area information extracted from the port information DB (140), and course information extracted from the global course DB (150) to generate a fuel consumption amount index in real time by calculating a fuel consumption amount according to an operation state of each ship on a global basis and calculates a greenhouse gas emission index according to a CII index, an EEOI index, and various calculation criteria in real time by calculating a greenhouse gas generation amount by using the calculated fuel consumption amount, thereby enabling accurate identification of greenhouse gas emission of the world shipping market and a real-time trend of a ship fuel consumption amount linked with the greenhouse gas emission.

Description

Big Data-Based Ship Fuel Consumption and Greenhouse Gas Emissions Evaluation System

[0001] The present invention relates to a big data-based ship fuel consumption and greenhouse gas emission evaluation system, and more specifically, to a big data-based ship fuel consumption and greenhouse gas emission evaluation system that can provide an index that accurately reflects the greenhouse gas emission and ship fuel consumption trends of the global shipping market by estimating the fuel consumption and greenhouse gas emission of ships based on actual operation data of ships around the world and marine environment information.

[0002] The International Maritime Organization (IMO) is applying the Carbon Intensity Indicator (CII) to ships over 5,000 GT worldwide as a greenhouse gas emission regulation introduced in 2023. The CII index is a figure that divides the amount of CO2 emissions by the deadweight of the ship - nautical miles, and is evaluated into five grades (A, B, C, D, and E). Ships that receive a D grade for three consecutive years between 2023 and 2025 or an E grade more than once will need to be remodeled or scrapped, and a decline in ship prices and restrictions on cargo transport contracts are expected.

[0003] However, although the IMO CII class reports the ship's emission performance for the previous year at the beginning of each year, the emission performance and class are not disclosed.

[0004] Meanwhile, freight indices that indicate the shipping industry are diverse depending on the type of cargo, route, and vessel size, and include the Baltic Capesize Index (BCI), Baltic Panamax Index (BPI), Baltic Supramax Index (BSI), and Baltic Handysize Index (BHI), which are composite indices by vessel type to measure changes in comprehensive dry bulk freight rates, the Baltic Dry Index (BDI), China Dry Freight Index (CDFI), World Scale, Baltic Clean / Dirty Tanker Index (BCTI and BDTI) that measure tanker freight rates, the World Container Index (WCI), China Containerized Freight Index (CCFI), and Shanghai Containerized Freight Index (SCFI) that measure changes in container freight rates.

[0005] The shipping freight index, which accurately shows the market trends, is used in various decision-making processes such as ship purchase and sale, ship financing, ship collateral value fluctuations, and related policy establishment because it accurately shows the market trends. However, there is still no index that evaluates fuel consumption and greenhouse gas emissions in real time by ship type, ship tonnage, route, shipyard, and shipping company in the shipping market. The main reason why such indices are not disclosed is because the fuel consumption of ships around the world is confidential, so information on greenhouse gas emissions is not disclosed.

[0006] Meanwhile, Korean Patent No. 10-1812802 (Method for calculating ship index for providing Asian ship index and method for brokerage service of ship index using the same, published on December 28, 2017), Korean Patent No. 10-1805402 (Method for calculating ship index for providing Asian container maritime freight index and method for brokerage service of ship index using the same, published on January 11, 2018), and Korean Patent No. 10-1830053 (Method for calculating ship freight index for providing Asian dry cargo maritime freight index and method for brokerage service of ship information using the same, published on March 30, 2018) propose a method for generating freight and ship index of maritime transport cargo by utilizing time series location information and operation route of vessels owned by each shipping company, marine environment information and cargo information, and although it was developed with the goal of maritime freight index and ship index, it is not applicable to the actual operation of vessels around the world. It does not include indices related to greenhouse gas emissions and fuel consumption.

[0007] In addition, Korean Patent No. 10-1982582 (AIS data and marine environment data-linked big data-based ship operation evaluation system, announced on May 27, 2019) and Korean Patent No. 10-1714028 (AIS information-based ship greenhouse gas emission management system and method, announced on March 22, 2017) are related to greenhouse gas emissions, but are limited to individual ships, and do not include calculation methods for global ship types and tonnage, delivered shipyards and operating shipping companies, and shipping greenhouse gas emissions and fuel consumption indices by route and port.

[0008] In addition, Korean Patent No. 10-2338291 (Method for assessing asset value of a ship by big data analysis, published on December 13, 2021), which was previously filed and registered by the applicant, uses big data using the actual operation of the ship and the marine environment, but it is a technology for evaluating the asset value of an individual ship by reflecting the individual ship's freight income, hull remaining fatigue life and equipment aging, operation risk, transported cargo risk, and legal risk in case of sanctions / seizure / operation ban by linking the AIS (Automatic Identification System) data that indicates the operation status and location of each ship and the marine environment data experienced during actual ship operation. It is not related to the greenhouse gas emission performance evaluation of ships worldwide, the operation efficiency of ships owned by ship owners, the greenhouse gas index by ship type and tonnage of global shipping, and by route.

[0009] Therefore, a technology is required to develop an index that shows the trends in fuel consumption and greenhouse gas emissions in the shipping market through big data analysis of the fuel consumption and greenhouse gas emissions of ships actually in operation, thereby enabling the identification of real-time trends in fuel consumption and greenhouse gas emissions in the shipping market.

[0010] The technical task to be achieved by the idea of ​​the present invention is to provide a big data-based ship greenhouse gas emission evaluation system that can calculate the actual greenhouse gas emissions of ships around the world according to the actual distance traveled, speed, and maritime environment at the time of operation, perform a greenhouse gas emission evaluation for each ship, calculate a greenhouse gas emission index by ship type and tonnage, delivered shipyard and operating shipping company, route, region, country, and port, and provide various service platforms using this.

[0011] In order to achieve the above-described object, an embodiment of the present invention comprises: a ship specification DB for collecting and storing ship specification information of ships around the world based on big data; a ship location information DB for collecting and storing ship location information including at least one of the operation status, location information, and operation route of ships around the world in real time based on big data; a maritime environment DB for collecting and storing maritime environment information in real time; a port information DB for collecting and storing port area information including at least one of port locations and quay locations around the world; a global route DB for collecting and storing route information that can be navigated around the world based on big data; a required horsepower estimation unit for applying a resistance component calculated by analyzing the ship specification information extracted from the ship specification DB, the ship location information extracted from the ship location information DB, the maritime environment information of the operation sea area extracted from the maritime environment DB, the port area information extracted from the port information DB, and the route information extracted from the global route DB, thereby estimating the required horsepower for navigation of a corresponding operation route; And the ship specification information extracted from the ship specification DB, the ship location information extracted from the ship location information DB, the maritime environment information of the operation area extracted from the maritime environment DB, the port area information extracted from the port information DB, and the route information extracted from the global route DB are analyzed to calculate fuel usage in real time according to the operation status of each ship around the world to create a fuel usage index, and the greenhouse gas emission index is calculated in real time according to a plurality of calculation standards including the CII index and the EEOI index by using the calculated fuel usage amount. The present invention provides a big data-based ship fuel usage and greenhouse gas emission evaluation system, including an index calculation unit.

[0012] Here, based on big data, a shipyard and operating company DB is further included that collects and stores ship information on ships delivered by a shipyard and ships owned by operating companies, and an operating efficiency calculation unit is further included that extracts and combines variables that affect the operating efficiency of operating companies from the ship specification DB, the ship location information DB, the maritime environment DB, the port information DB, and the global route DB, and calculates and generates an operating efficiency index for each operating company according to the ship information.

[0013] At this time, a ship performance calculation unit may further be included that calculates and generates a still water or wave ship performance index by combining the fuel consumption index, the CII index, the EEOI index, and the greenhouse gas emission index to evaluate the ship performance of the ship delivered to each shipyard.

[0014] In addition, the index calculation unit can calculate in real time at least one evaluation index by combining the fuel consumption index, the CII index, the EEOI index, and the greenhouse gas emission index, and applying weights by combining two or more items of shipping company, ship type, ship tonnage, shipyard, operating shipping company, route, season, region, country, and port.

[0015] Here, the index calculation unit can provide a derivatives trading service using the evaluation index as a base index.

[0016] Specifically, the above derivatives trading service may include ESG (Environmental, Social, Governance) ETFs (Exchanged Traded Funds).

[0017] In addition, the ship specification DB can be constructed by collecting at least one of the length, width, load, speed, and draft of ships registered worldwide, and storing the ship specification information including at least one of the IMO number, MMSI number, ship name, ship type, ship tonnage, hull main specification information, engine information, cargo hold size, ship age, shipbuilding yard, and operating shipping company of ships owned by each shipping company.

[0018] In addition, the fuel consumption index and the greenhouse gas emission index can be calculated for each route by applying different weights to each route of the route information extracted from the global route DB.

[0019] According to the present invention, by using big data on the actual operating status of ships and the maritime environment, greenhouse gas emissions of ships in the actual maritime environment are calculated, and real-time greenhouse gas emissions and fuel consumption in the maritime sector are estimated through an evaluation of greenhouse gas emissions and fuel consumption for ships by ship type, ship tonnage, route, shipyard delivery, and ships operated by shipping companies, thereby performing maritime business forecasting, and using the fuel usage index and greenhouse gas emission index, there is an effect of being able to provide derivative products and related services such as bunkering usage index of ports around the world, ESG (Environmental, Social, Governance) ETFs (Exchanged Traded Funds).

[0020] In addition, it has the effect of carrying out preemptive planning to prevent the risk of asset value decline due to changes in greenhouse gas emission levels, reasonable ship value evaluation when trading ships through accurate fuel consumption and greenhouse gas emission information, ESG Scope 3 evaluation related to greenhouse gases in the process of transporting goods scheduled to be introduced to the International Financial Reporting Standards (IFRS), selection of ships with the lowest greenhouse gas emissions and determination of reasonable freight rates by shippers, and objective design evaluation of shipyards based on performance evaluation of ships delivered to shipyards.

[0021] Furthermore, it has the effect of improving ship design, enhancing operational efficiency of shipping companies, and establishing a diverse service platform by providing fuel consumption indices and greenhouse gas emission indices that are beneficial to shipping companies, shippers, investors, banks, insurance companies, shipping and shipbuilding companies, marine fuel bunkering companies, research institutes, economic organizations, and regulatory agencies.

[0022] In addition, by calculating fuel consumption based on the operating status of each ship worldwide and verifying the actual fuel consumption of the reported ship, it is possible to purchase undervalued ships that have good ship performance but generate a lot of greenhouse gas emissions due to poor operation management or route selection, and then reduce fuel costs after optimal operation and obtain profits after sale.

[0023] Figure 1 is a schematic diagram illustrating a configuration of a big data-based ship fuel usage and greenhouse gas emission evaluation system according to an embodiment of the present invention.

[0024] Figure 2 illustrates a flow chart of the big data-based ship fuel usage and greenhouse gas emission evaluation system of Figure 1.

[0025] Figure 3 illustrates the greenhouse gas emission index by ship type and ship tonnage of the big data-based ship fuel consumption and greenhouse gas emission evaluation system of Figure 1.

[0026] Figure 4 illustrates the route-specific greenhouse gas emission index of the big data-based ship fuel consumption and greenhouse gas emission evaluation system of Figure 1.

[0027] Figure 5 illustrates the greenhouse gas emission index of tanker ships by route in the big data-based ship fuel consumption and greenhouse gas emission evaluation system of Figure 1.

[0028] Figure 6 illustrates the ship evaluation index of the big data-based ship fuel usage and greenhouse gas emission evaluation system of Figure 1.

[0029] Hereinafter, an embodiment of the present invention having the above-described features will be described in more detail with reference to the attached drawings.

[0030] The big data-based ship fuel consumption and greenhouse gas emission evaluation system according to an embodiment of the present invention includes a ship specification DB (110), a ship location information DB (120), a marine environment DB (130), a port information DB (140), a global route DB (150), and a ship specification DB (110), ship location information from the ship location information DB (120), marine environment information of the operation sea area from the marine environment DB (130), port area information from the port information DB (140), and route information from the global route DB (150), and a required horsepower estimation unit (160) that estimates the required horsepower when sailing on the corresponding operation route by applying a resistance component that is calculated by analyzing the ship specification information extracted from the ship specification DB (110), the marine environment information of the operation sea area extracted from the marine environment DB (130), the ship location information extracted from the ship location information DB (120), and the route information from the port information DB (140). The main purpose is to accurately grasp the real-time trend of greenhouse gas emissions in the global shipping market and the ship fuel consumption linked to greenhouse gas emissions, including an index calculation unit (170) that calculates fuel consumption according to the operation status of each ship worldwide by analyzing extracted port area information and route information extracted from a global route DB (150), and generates a fuel consumption index in real time, and calculates greenhouse gas emissions using the calculated fuel consumption to calculate the CII index, the EEOI index, and a greenhouse gas emission index according to various calculation standards.

[0031] Hereinafter, with reference to the drawings, the big data-based ship fuel usage and greenhouse gas emission evaluation system of the aforementioned configuration is specifically described as follows.

[0032] First, the ship specification DB (110) collects and stores specification information of ships around the world based on big data.

[0033] For example, a ship specification DB (110) can be constructed by collecting the length, width, load, speed and / or draft of ships registered around the world, and storing ship specification information such as the IMO number, MMSI number, ship name, ship type, ship tonnage, hull main specification information, engine information, cargo hold size, ship age, shipbuilding yard and / or operating company of ships owned by each shipping company.

[0034] Here, engine information includes necessary information such as engine model, unit fuel consumption, maximum and minimum horsepower, and maximum and minimum revolutions per minute for accurate assessment of greenhouse gas emissions of the ship.

[0035] Next, the ship location information DB (120) collects and stores ship location information, such as the operating status, location information, and / or operating route of ships around the world, in real time based on big data.

[0036] For example, a ship location information DB (120) can be constructed by collecting the ship's time series location information and operating route from the ship's AIS (Auto Identification System) information, RF or LRIT (Long Range Identification and Tracking) by a satellite and local location information receiving device, and storing the ship's location information.

[0037] Next, the maritime environment DB (130) collects and stores satellite-based maritime environment information in real time.

[0038] For example, the marine environment DB (130) can be constructed by periodically receiving, updating, and storing satellite-based marine environment information, such as wave direction and wave height, wind direction and wind speed, current direction and current strength, provided by private companies such as the National Oceanic and Atmospheric Administration (NOAA), the European Centre for Medium-Range Weather Forecasts (ECMWF), the National Data Center for Buoys (NDBC), or SPIRE.

[0039] Next, the port information DB (140) collects and stores port area information such as global port locations and / or global quay locations.

[0040] For example, the locations of approximately 12,000 ports around the world are usually presented as a single coordinate, but since the length of the quay walls of large ports such as Shanghai Port in China can reach several kilometers, in order to accurately identify the activities or anchoring of ships at the quay walls, which have a significant impact on greenhouse gas emissions, a port information DB (140) can be constructed by storing port area information including the location coordinates of each quay wall of ports around the world.

[0041] Next, the global route DB (150) collects and stores route information that can be operated worldwide based on big data.

[0042] Next, the required horsepower estimation unit (160) applies the vessel resistance component calculated by analyzing the vessel specification information extracted from the vessel specification DB (110), the vessel location information extracted from the vessel location information DB (120), the marine environment information of the operating sea area extracted from the marine environment DB (130), the port area information extracted from the port information DB (140), and the route information from the global route DB (150) (S110), thereby estimating the required horsepower for sailing the corresponding operating route (S120).

[0043] For example, the required horsepower estimation unit (160) uses a port information DB (140) including port location and quay location information to determine the status of a vessel operating at sea or moving, unloading, or anchoring at the quay of a port, and uses a maritime environment DB (130) of the sea area where the vessel actually operated to calculate various resistance components such as the frictional resistance, shape resistance, additional resistance, wave generation resistance, wave breaking resistance considering the wave direction, wind resistance considering the wind direction, resistance due to the current, and additional resistance, and then estimates the required horsepower in real time or periodically.

[0044] Next, the index calculation unit (170) analyzes the ship specification information extracted from the ship specification DB (110), the ship location information extracted from the ship location information DB (120), the maritime environment information of the operation area extracted from the maritime environment DB (130), the port area information extracted from the port information DB (140), and the route information extracted from the global route DB (150), calculates the fuel consumption according to the operation status of each ship around the world (S130), and creates a fuel consumption index in real time, and calculates the greenhouse gas emission amount using the calculated fuel consumption (S140), and calculates the CII (Carbon Intensity Indicator) index, the EEOI (Energy Efficiency Operational Indicator) index, and the greenhouse gas emission index for each ship according to various calculation standards in real time or periodically (S150).

[0045] For example, since the main engine is mainly used at sea and auxiliary engines such as generators and boilers are mainly used during movement, unloading, or anchoring at the quay wall, the index calculation unit (170) calculates the fuel consumption by fuel used in real time according to the operating status of each ship around the world, and creates a fuel consumption index of ships around the world using the fuel consumption information calculated in advance, and calculates the greenhouse gas emission or pollutant emission amount using the calculated fuel consumption, and by combining various variables, it is possible to calculate the IMO's CII index, the EEOI index used by the EU and ESG (Environmental, Social, Governance), the greenhouse gas emission index or pollutant emission index, and various greenhouse gas emission indices or pollutant emission indices, etc.

[0046] Meanwhile, the CII index for each ship required by IMO can be calculated by inputting greenhouse gas emissions and operating ton-miles using the following [Mathematical Formula 1].

[0047]

[0048] Additionally, the IMO CII index is evaluated in 5 stages as shown in Table 1 below.

[0049] Group ABCDE Evaluation Criteria CII < 1-d11-d1 < CII< 1-d21-d2 < CII< d2-1d2-1 < CII< d4-1d4-1 < CII

[0050] In addition, the EEOI index can be calculated by substituting the greenhouse gas emissions and the actual cargo weight (ton-mile) transported using the following [Mathematical Formula 2].

[0051]

[0052] In addition, the greenhouse gas emission index calculated for each ship can be divided into a greenhouse gas emission index by ship type and tonnage, a greenhouse gas emission index by route, and / or a greenhouse gas emission index by shipyard and shipping company. Various greenhouse gas emission indices can be composed by combining ship type, tonnage, season, region, country, route, port, shipyard, and / or shipping company. In addition, a time-series greenhouse gas emission composite index can be calculated and provided periodically on an annual, monthly, and / or weekly basis for the calculated greenhouse gas emission indices. In a similar manner, indices for greenhouse gases or air pollutants such as NOx, SOx, methane, and PM can also be derived.

[0053] For example, as shown in Fig. 3, this shows an example of CII generated according to the ship type and deadweight tonnage standards set by IMO, and by applying the weighted average of ship type / tonnage of ships worldwide, the greenhouse gas (CO2, PM, methane, NOX, SOX, etc.) emission index of ships worldwide can be calculated using various standards.

[0054] Here, by applying different weights to each route of route information extracted from the global route DB (150), fuel consumption indices and greenhouse gas emission indices for various routes can be calculated, respectively.

[0055] In addition, Fig. 4 shows an example of calculating the greenhouse gas emission index of a bulk carrier for a route defined by the Baltic Exchange. In order to calculate the greenhouse gas emission index by route by considering the proportion of each route (Bulk Carrier Routes), the greenhouse gas emission index for various routes (by route) can be calculated by using the route information of the global route DB (150) for routes used by the Baltic Exchange or similar routes (S160).

[0056] In addition, although it is desirable to follow the IMO standards for classification of ship types and tonnage, classifications based on ship types and tonnage (e.g., VLCC, Aframax, Suezmax, Panamax, Post Panamax, LR, MR, Handymax, Handy, etc.) that are commonly used in shipbuilding and shipping markets such as the Baltic Exchange can also be used, and as shown in Fig. 5, the greenhouse gas emission index of tankers by route can be calculated and provided according to the ship classification standards used in the Baltic Exchange.

[0057] Meanwhile, the index calculation unit (170) can combine various greenhouse gas-related indices, pollutant generation indices, pollutant emission indices, etc., such as the previously generated fuel consumption index, CII index, EEOI index, Annual Efficiency Ratio (AER), Energy Efficiency Design Index (EEDI), Energy Efficiency Existing Ship Index (EEXI), and Environmental Ship Index (ESI), according to the purpose, and can apply weights by combining items related to shipping company, ship type, ship tonnage, shipyard, operating shipping company, route, season, region, country, and / or port, thereby calculating an evaluation index by shipping company, ship type, ship tonnage, and / or route in real time.

[0058] In addition, similar to the method of calculating greenhouse gas emission indices by ship type, ship tonnage, and / or route, greenhouse gas emission indices by season, region, country, and / or port can also be calculated using the ship specification DB (110), ship location information DB (120), maritime environment DB (130), port DB (140), and global route DB (150) (S170).

[0059] Additionally, similar to the previous greenhouse gas emission index calculation method, fuel consumption indices can also be calculated by vessel, ship owner, route, season, region, country and / or port.

[0060] Meanwhile, as shown in FIGS. 1 and 2, the shipyard and operating company DB (180) is further included to collect and store ship information on ships delivered by a shipyard and ships owned by operating companies based on big data, and the operating efficiency calculation unit (190) extracts and combines variables that affect the operating efficiency of operating companies from the ship specification DB (110), the ship location information DB (120), the maritime environment DB (130), the port information DB (140), and the global route DB (150), thereby calculating and generating an operating efficiency index for each operating company based on the ship information of the shipyard and operating company DB (180) (S180).

[0061] For example, various factors such as accumulated fatigue of the hull during operation in waves, ballast tank usage time, total engine rotation speed (actual rotations per minute × operation time), actual greenhouse gas emissions per cargo ton-mile, increase or decrease in greenhouse gas emissions due to wind direction and wind speed, greenhouse gas emission ratio during operation, unloading and anchoring of the entire ship during operation, average wave height and wave direction by selected route, strength and direction of current, and / or wind direction and wind speed affect the efficiency of ship operation. The operation efficiency calculation unit (190) can calculate and generate an operation efficiency index by considering factors affecting operation efficiency in this way.

[0062] That is, the operational efficiency index of a shipping company can be used for efficient operation of the shipping company, management of ships, sale of ships, financing of shipping companies, investment, etc., and the following [Mathematical Formula 3] can present one example of the operational efficiency index of a shipping company created using important variables representing the operational efficiency of each shipping company.

[0063]

[0064] Here d j is a coefficient, K1 is the proportion of CII generated at the port quay wall among the total CII generated, K2 is the proportion of CII generated while at anchor, and K3 is the proportion of CII generated while operating at sea.

[0065] In addition, the following [Table 2] is an example of a grade that was selected by applying various criteria to judge the operational efficiency of shipping companies. It presents an evaluation of the operational efficiency of ships by classifying them into five grades, and through these evaluation grades, an objective evaluation of the operational efficiency of shipping companies can be made.

[0066] Group ABCDE Evaluation Criteria 0 < M < 20% 20% < M < 40% 40% < M < 60% 60% < M < 80% 80% < M

[0067] Meanwhile, the ship performance calculation unit (200) can calculate and generate a still water or wave ship performance index that evaluates the ship performance of the delivered ship by each shipyard by combining the amount of CO2 generated in still water during operation, the amount of CO2 generated at sea during operation, the fuel consumption index, the greenhouse gas generation index or pollutant generation index, the CII index, the EEOI index, the greenhouse gas emission index or pollutant emission index, etc. (S190). At this time, the ship performance calculation unit (200) can calculate and generate a ship performance index by each shipyard and verify the special features of the ship's actual fuel consumption report. For reference, fuel consumption and greenhouse gas emissions from ship operation occur not only in still water but also when operating in waves. However, ships delivered by shipyards only guarantee fuel consumption for the design speed in still water, and do not guarantee wave breaking performance for various wave heights. In addition, information on fuel consumption and greenhouse gas emissions from actual shipyards and shipping companies when operating in still water and waves is confidential, and the actual fuel consumption and greenhouse gas emissions of ships operating around the world are not disclosed.

[0068] In addition, since ships operate in still water and waves, the required horsepower and fuel consumption change according to the change in the ship's breaking performance by wave height and speed, and this affects the greenhouse gas emission index. Therefore, an evaluation index (ship performance index) for the greenhouse gas emission and fuel consumption performance of ships delivered from shipyards that comprehensively reflects the greenhouse gas emission performance in still water and waves is needed.

[0069] Accordingly, the greenhouse gas emission performance of ships delivered by each shipyard can be evaluated by various variables such as frictional resistance performance, still water speed performance, wave breaking performance, and added resistance performance. Various ship performance indices can be generated through combinations of various variables that can determine the ship's operational performance as mentioned above. For example, the following [Mathematical Formula 4] presents an example of calculating the greenhouse gas emission index (R) of ships delivered by each shipyard using the still water CII index per unit speed, the wave CII index per unit wave height, etc. to evaluate the shipyard's delivered ship performance.

[0070]

[0071] Here c i is the coefficient, S1 is the CII index of the wave per unit speed, and S2 is the CII index of the wave per unit wave height.

[0072] Meanwhile, greenhouse gas emission ratings can be categorized into various grades by applying various criteria to all ships. The following [Table 3] is an example of one of them, suggesting an evaluation divided into five grades based on the previously calculated greenhouse gas emission index (R).

[0073] Group ABCDE Evaluation Criteria 0 < R < 20% 20% < R < 40% 40% < R < 60% 60% < R < 80% 80% < R

[0074] In addition, a ship performance index by shipyard that shows the fuel consumption and greenhouse gas emission-related capabilities of the shipyard that delivered the ship, and an evaluation index classified by individual shipyards and shipping companies, regions, countries, etc. to understand the operational efficiency of shipping companies can be derived, and Fig. 6 presents examples of greenhouse gas emission performance of ships delivered by shipyards classified by regions and countries, operational efficiency indices by shipping companies, and greenhouse gas emission indices of individual shipyards and shipping companies. Meanwhile, the index calculation unit (170) can also provide a trading service for derivatives such as ESG (Environmental, Social, Governance) ETFs (Exchanged Traded Funds) that use the various evaluation indices presented above as base indices (S200).

[0075] Meanwhile, route information big data including route, operating distance, operating time, etc. extracted from the global route DB, wave height, wind strength and direction, tidal current speed and direction, etc. extracted from the maritime environment DB, and fuel usage, greenhouse gas emissions or pollutant emissions, greenhouse gas emissions index or pollutant emissions index, EEOI index, greenhouse gas emission index or pollutant emissions index, etc. extracted from the index calculation section are constructed, and similar route information is extracted from the route information big data according to the weather forecast, and then the shortest distance, minimum time, minimum fuel usage, minimum greenhouse gas emission index, etc. can be extracted.

[0076] In addition, in the case of a ship analyzed by a big data-based ship fuel consumption and greenhouse gas emission evaluation system according to an embodiment of the present invention, the still water and wave performance of the ship is analyzed to purchase an undervalued ship that has excellent performance but has a low ship price due to a large amount of greenhouse gas emissions caused by insufficient ship operation or route selection, and then a ship operation improvement policy that minimizes fuel consumption, greenhouse gas emissions, or pollutant emissions from route information big data is applied to improve the greenhouse gas emission index or pollutant emission index, thereby reducing fuel costs and calculating profit after selling the ship.

[0077] Therefore, by configuring the big data-based ship fuel consumption and greenhouse gas emission evaluation system as described above, the greenhouse gas emissions of ships in the actual marine environment are calculated using big data on the actual ship's operating status and the marine environment, and the greenhouse gas emissions and fuel consumption of ships by ship type, tonnage, route, shipyard delivery, and ships operated by shipping companies are evaluated to estimate real-time greenhouse gas generation and fuel consumption in the shipping industry, thereby performing shipping business forecasting, and using the fuel consumption index and greenhouse gas emission index, the bunkering usage index of ports around the world, derivative products such as ESG ETFs (Exchanged Traded Funds) and related services are provided, and preemptive planning is performed to prevent the risk of asset value decline due to changes in greenhouse gas emission levels, and a reasonable ship value evaluation when trading ships through accurate fuel consumption and greenhouse gas emission information, and ESG Scope 3 related to greenhouse gases in the process of transporting goods to be introduced in the International Financial Reporting Standards (IFRS) Evaluation, selection of ships with minimum greenhouse gas emissions by shippers and determination of reasonable freight rates, and objective evaluation of shipyard fuel consumption, still water and wave performance based on performance evaluation of ships delivered to shipyards, improvement of ship design and enhancement of operating efficiency of shipping companies, and provision of fuel consumption index and greenhouse gas emission index useful to shipping companies, shippers, investors, banks, insurance, shipping and shipbuilding-related companies, marine fuel bunkering companies, research institutes, economic institutions and regulatory agencies, enabling the establishment of various service platforms, calculating fuel consumption based on the operating status of each ship around the world and verifying the actual fuel consumption of the reported ship, and purchasing undervalued ships with good ship performance but high greenhouse gas emissions due to insufficient operation management or route selection, thereby reducing fuel costs after optimal operation and generating profit after sale.

[0078] The embodiments described in this specification and the configurations illustrated in the drawings are only the most preferred embodiments of the present invention and do not represent all of the technical ideas of the present invention. Therefore, it should be understood that there may be various equivalents and modified examples that can replace them at the time of filing this application.

Claims

1. A ship specification database that collects and stores ship specification information for ships around the world based on big data; A ship location information DB that collects and stores ship location information including one or more of the operation status, location information, and operation routes of ships around the world in real time based on big data; Marine environment DB that collects and stores marine environment information in real time; A port information DB that collects and stores port area information including one or more of the world's port locations and quay locations; A global route database that collects and stores route information that can be operated worldwide based on big data; A required horsepower estimation unit that estimates the required horsepower for sailing the corresponding operating route by applying a resistance component calculated by analyzing the vessel specification information extracted from the vessel specification DB, the vessel location information extracted from the vessel location information DB, the maritime environment information of the operating sea area extracted from the maritime environment DB, the port area information extracted from the port information DB, and the route information extracted from the global route DB; and An index calculation unit that calculates fuel consumption in real time according to the operation status of each ship around the world by analyzing the ship specification information extracted from the ship specification DB, the ship location information extracted from the ship location information DB, the maritime environment information of the operation area extracted from the maritime environment DB, the port area information extracted from the port information DB, and the route information extracted from the global route DB, and generates a fuel consumption index, and calculates greenhouse gas emissions using the calculated fuel consumption to calculate greenhouse gas emissions in real time according to multiple calculation standards including the CII index and the EEOI index, A big data-based ship fuel consumption and greenhouse gas emissions evaluation system.

2. In paragraph 1, Based on big data, it further includes a shipyard and shipping company DB that collects and stores ship information on ships delivered by shipyards and ships owned by shipping companies. It is characterized by further including an operation efficiency calculation unit that extracts and combines variables that affect the operation efficiency of an operating shipping company from the ship specification DB, the ship location information DB, the maritime environment DB, the port information DB, and the global route DB, and calculates and generates an operation efficiency index for each operating shipping company according to the ship information. A big data-based ship fuel consumption and greenhouse gas emissions evaluation system.

3. In paragraph 2, It is characterized by further including a ship performance calculation unit that calculates and generates a still water or wave ship performance index that evaluates the ship performance of a ship delivered to each shipyard by combining the fuel consumption index, the CII index, the EEOI index, and the greenhouse gas emission index. A big data-based ship fuel consumption and greenhouse gas emissions evaluation system.

4. In paragraph 1, The above index calculation section, The fuel consumption index, the CII index, the EEOI index, and the greenhouse gas emission index are combined, and weights are applied by combining two or more items among shipping company, ship type, ship tonnage, shipyard, operating shipping company, route, season, region, country, and port, thereby calculating in real time at least one evaluation index among shipping company, ship type, ship tonnage, route, season, region, country, and port. A big data-based ship fuel consumption and greenhouse gas emissions evaluation system.

5. In paragraph 4, The above index calculation section, It is characterized by providing a derivatives trading service using the above evaluation index as a base index. A big data-based ship fuel consumption and greenhouse gas emissions evaluation system.

6. In paragraph 5, The above derivatives trading service is: Characterized by including ESG (Environmental, Social, Governance) ETFs (Exchanged Traded Funds), A big data-based ship fuel consumption and greenhouse gas emissions evaluation system.

7. In paragraph 1, The above ship specification DB is, It is characterized in that it is constructed by collecting at least one of the length, width, load, speed and draft of registered ships around the world, and storing the ship specification information including at least one of the IMO number, MMSI number, ship name, ship type, ship tonnage, hull main specification information, engine information, cargo hold size, ship age, shipbuilding yard and operating shipping company of the ships owned by each shipping company. A big data-based ship fuel consumption and greenhouse gas emissions evaluation system.

8. In paragraph 1, Characterized in that the fuel consumption index and the greenhouse gas emission index are calculated for each route by applying different weights to each route of the route information extracted from the global route DB. A big data-based ship fuel consumption and greenhouse gas emissions evaluation system.

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