CN117235903B - LNG ship natural evaporation BOG prediction method and system - Google Patents
LNG ship natural evaporation BOG prediction method and system Download PDFInfo
- Publication number
- CN117235903B CN117235903B CN202311508529.XA CN202311508529A CN117235903B CN 117235903 B CN117235903 B CN 117235903B CN 202311508529 A CN202311508529 A CN 202311508529A CN 117235903 B CN117235903 B CN 117235903B
- Authority
- CN
- China
- Prior art keywords
- ship
- natural evaporation
- gas
- bog
- natural
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001704 evaporation Methods 0.000 title claims abstract description 157
- 230000008020 evaporation Effects 0.000 title claims abstract description 156
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000012937 correction Methods 0.000 claims abstract description 21
- 238000013461 design Methods 0.000 claims abstract description 19
- 238000004458 analytical method Methods 0.000 claims abstract description 9
- 238000012544 monitoring process Methods 0.000 claims description 21
- 239000007788 liquid Substances 0.000 claims description 14
- 230000007613 environmental effect Effects 0.000 claims description 11
- 239000013535 sea water Substances 0.000 claims description 11
- 238000013500 data storage Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 238000012549 training Methods 0.000 claims description 5
- 238000007619 statistical method Methods 0.000 claims description 4
- 239000002344 surface layer Substances 0.000 claims description 4
- 238000004519 manufacturing process Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000012795 verification Methods 0.000 claims description 3
- 238000012800 visualization Methods 0.000 claims description 3
- 239000007787 solid Substances 0.000 abstract description 6
- 238000007726 management method Methods 0.000 description 8
- 238000005314 correlation function Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 239000000446 fuel Substances 0.000 description 3
- 230000001419 dependent effect Effects 0.000 description 2
- 239000010410 layer Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 239000012466 permeate Substances 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Landscapes
- Filling Or Discharging Of Gas Storage Vessels (AREA)
Abstract
The invention relates to the technical field of marine equipment, in particular to a natural evaporation BOG prediction method and a natural evaporation BOG prediction system for an LNG ship, wherein the method comprises the following steps: acquiring cargo state data of the LNG ship for multiple voyages; acquiring ship environment temperature, ship environment sea state data and corresponding natural evaporation BOG data; classifying the ship environment temperature and the ship environment sea state data, and comparing the associated natural evaporation BOG values to obtain a natural evaporation BOG prediction model corresponding to the two important parameters of the ship environment temperature and the ship environment sea state; converting the natural evaporation BOG data obtained under the design condition into a basic BOR value, and then comparing trend analysis with factory design BOR data to obtain a natural evaporation BOG value correction coefficient; and correcting the natural evaporation BOG prediction model. The method and the system provided by the invention have the advantages that the natural evaporation BOG value of the LNG ship is predicted more accurately, and a solid foundation is laid for the management of the natural evaporation BOG of the LNG ship.
Description
Technical Field
The invention relates to the technical field of marine equipment, in particular to a natural evaporation BOG prediction method and system for an LNG ship.
Background
LNG is clean fuel with wide application and mature technology at the present stage, has good development prospect, and LNG ships often use LNG cargo boil-off gas BOG as fuel to provide energy for engine equipment such as ship hosts and generators, and the BOG fuel comes from two parts of natural evaporation of a cargo tank and forced evaporation of an evaporator. The natural evaporation rate BOR of the LNG ship cargo tank is taken as an important parameter of ship transportation performance, the pressure balance management of the LNG cargo tank is realized, the loading rate of the LNG ship is ensured, the safe transportation of LNG is ensured, the cargo consumption is mastered, the transportation cost is reduced, and the market competitiveness is improved.
The design value of the factory BOR when the LNG ship is designed and built, namely, the theoretical calculated value under the working condition of the design condition is different from ship to ship, is related to the inherent characteristics of the cargo containment system of the cargo tank, and the LNG ship is also reduced in efficiency due to the fact that the cargo containment system is different in service life and the performance of the cargo tank self heat insulation layer is aged with time, so that the static BOR is a change value in the long term, the natural evaporation rate BOR of the LNG ship is deviated and changed compared with the BOR of a new ship, and therefore the BOR of the corresponding LNG cargo tank self is required to be recorded and evaluated continuously.
In addition, the natural evaporation BOG is a dynamic value in the actual operation of the LNG ship, and mainly can be subjected to the increase of the ambient temperature of the LNG ship, and heat permeates into the liquid cargo tank heat preservation layer, so that the natural evaporation amount of LNG in the cargo tank is increased; or the LNG ship can shake due to the influence of wind and waves in the sailing environment, the kinetic energy in the liquid cargo is increased, and the natural evaporation capacity is increased.
The BOG amount naturally evaporated in real time is not easy to grasp due to the influence of the factors. The real-time natural evaporation BOG cannot be accurately predicted, and the BOG balance utilization management of the LNG ship cannot be realized, so that trend prediction and effective analysis of the natural evaporation BOG of the LNG cargo hold are necessary for better mastering the BOG management of the LNG ship, balancing the cabin pressure of the LNG cargo hold, reducing the LNG loss and improving the natural evaporation BOG cargo utilization rate.
Disclosure of Invention
The invention aims to solve the technical problem of providing a natural evaporation BOG prediction method and a natural evaporation BOG prediction system for an LNG ship, wherein the natural evaporation BOG prediction model corresponding to two important parameters of the ship environment temperature and the ship environment sea condition is obtained by collecting data of influence of marine navigation environment factors on the natural evaporation BOG when the LNG ship is fully loaded for multiple voyages, extracting correlation functions of the ship environment temperature and the ship environment sea condition and the natural evaporation BOG respectively, then the basic BOR value of the LNG ship is calculated, and the basic BOR value is compared with factory design BOR data for trend analysis, so that the natural evaporation BOG value is corrected by the correction coefficient of the natural evaporation BOG value, the generation amount of the natural evaporation BOG of the LNG ship can be accurately predicted, and a solid foundation is laid for the management of the natural evaporation BOG of the LNG ship.
The invention is realized by the following technical scheme:
a natural evaporation BOG prediction method for an LNG ship comprises the following steps:
s1: acquiring initial cargo state data of the LNG ship in a multi-voyage full-load normal voyage state, and performing the next step when the difference value between the initial cargo state data of the LNG ship in the multi-voyage state and the historical average data is within a corresponding set threshold range;
s2: acquiring and storing the ship environment temperature, the ship environment sea state data and the corresponding natural evaporation BOG data of the LNG ship in a full-load normal sailing state for multiple voyages;
s3: classifying the acquired ship environment temperature and ship environment sea state data, comparing the obtained ship environment temperature and ship environment sea state data with the associated natural evaporation BOG value to obtain associated functions of the ship environment temperature and the ship environment sea state and the natural evaporation BOG respectively, and obtaining a preliminary natural evaporation BOG prediction model corresponding to the ship environment temperature and the ship environment sea state two important parameters;
s4: comparing the acquired ship environment temperature and ship environment sea state data of the LNG ship in the full-load normal sailing state with the design conditions respectively, finding out corresponding natural evaporation BOG data when the ship environment temperature and the ship environment sea state data of the corresponding LNG ship in the full-load normal sailing state are closest to the design conditions respectively, converting the natural evaporation BOG data into basic BOR values respectively, and comparing trend analysis is carried out on all basic BOR values with the factory design BOR data to obtain a natural evaporation BOG value correction coefficient;
s5: and correcting the preliminary natural evaporation BOG prediction model by using the natural evaporation BOG value correction coefficient to obtain a corrected natural evaporation BOG prediction model.
Preferably, the initial cargo state data in step S1 includes a cargo temperature, a pressure, and a liquid level, where the set threshold of the cargo temperature is 3 times the standard deviation of the cargo temperature and the historical average, the set threshold of the pressure is 3 times the standard deviation of the pressure and the historical average, and the set threshold of the liquid level is 3 times the standard deviation of the liquid level and the historical average.
Further, in step S2, the ship ambient temperature is a weighted average of the ambient sea water skin temperature and the ambient sea air temperature.
Further, the ship ambient temperature is calculated according to formula (1):
（1）；
wherein:for the ambient temperature of the ship, < > is->Is the surface temperature of the ambient seawater, < > is->Is the weight coefficient of the temperature of the surface layer of the environmental seawater, +.>Is ambient marine air temperature, +.>Is a weight for the ambient offshore air temperature.
Further, in step S3, a natural evaporation BOG prediction model is obtained according to the following method:
s31: storing, screening and training natural evaporation BOG data under the condition that the ship environment temperature corresponds to the ship environment sea state data by adopting a statistical method, and manufacturing a data graph of the relationship among the ship environment temperature, the ship environment sea state and the natural evaporation BOG by using a chart visualization tool;
s32: according to the data graph of the relationship between the ship environment temperature, the ship environment sea condition and the natural evaporation BOG, a four-parameter fitting equation is utilized to select a proper function curve, a relationship correlation curve reflecting the relationship between the marine environment and the natural evaporation BOG data is obtained, and a corresponding function model is formed;
s33: and evaluating the fitting degree and the prediction capacity of the function model, and verifying, if the fitting degree and the prediction capacity of the function model do not meet the requirements, reselecting the function curve and re-fitting until the fitting degree and the prediction capacity of the function model meet the requirements, thereby obtaining the preliminary natural evaporation BOG prediction model.
Further, the four-parameter fitting equation in step S32 is formula (2):
（2）；
wherein:representing the ship ambient temperature or the ship ambient sea state, representing the independent variable of the function curve,/->Represents the BOG value of natural evaporation, represents the dependent variable of the function curve, < ->Representing the lower limit of the natural evaporation BOG, representing the lower asymptote of the function curve, ++>Represents the upper limit of the natural evaporation BOG, represents the upper asymptote of the function curve, ++>A value indicating that the argument influences the growth rate to begin to change,/->Represents the rate of increase parameter, representing the slope of the function curve.
Further, the preliminary natural evaporation BOG prediction model obtained in step S33 is formula (3):
（3）；
wherein:represents the predicted value of BOG for natural evaporation, +.>Representing the predicted value of BOG naturally evaporated under the influence of the temperature of the offshore environment,/->Weight representing predicted value of natural evaporation BOG under influence of offshore environment temperature, < + >>Representing the predicted value of BOG naturally evaporated under the influence of the sea conditions of the ship environment, < >>The weight of the natural evaporation BOG predicted value under the influence of the ship environment and sea conditions is represented;
optimally, the design condition in the step S4 is that the temperature of the ambient marine air is 5 ℃, the temperature of the surface layer of the ambient seawater is 0 ℃, and the grade of the ambient sea condition of the ship is less than or equal to one grade.
Further, in step S4, the corrected natural evaporation BOG prediction model is represented by formula (4):
（4）；
wherein:for the corrected natural evaporation BOG prediction value, -/-, for>And represents the correction coefficient of the natural evaporation BOG value.
The LNG ship natural evaporation BOG prediction system is used for executing the LNG ship natural evaporation BOG prediction method, and comprises an LNG ship cargo state monitoring unit, an offshore environment monitoring unit, a BOG data processing control unit and a BOG flow monitoring unit, wherein the LNG ship cargo state monitoring unit is used for collecting LNG ship cargo state data in an LNG ship full-load sailing state, the offshore environment monitoring unit is used for collecting ship environment temperature and ship environment sea state data in the LNG ship full-load normal sailing state, the BOG flow monitoring unit is used for collecting natural evaporation BOG data corresponding to a sailing offshore environment, the BOG data processing control unit comprises a cargo hold BOG data storage module, a cargo hold BOG data comparison correlation module and a cargo hold BOG data correction module, the cargo hold BOG data storage module is used for collecting, storing and training real-time natural evaporation BOG and corresponding offshore environment monitoring data, the cargo hold BOG data comparison correlation module is used for analyzing correlation of the offshore environment and natural evaporation BOG data, a fitting function and a comparison verification function are selected, and the cargo hold BOG data correction module is used for correcting and predicting natural evaporation BOG values.
The invention has the beneficial effects that:
according to the invention, the data of the influence of the marine navigation environmental factors on the natural evaporation BOG during the full-load navigation of the LNG ship at multiple voyages are collected, the correlation functions of the ship environmental temperature and the ship environmental sea condition and the natural evaporation BOG are extracted, the preliminary natural evaporation BOG prediction model corresponding to the ship environmental temperature and the ship environmental sea condition is obtained, the basic BOR value of the LNG ship is calculated, and the basic BOR value is compared with the factory design BOR data for trend analysis, so that the natural evaporation BOG value correction coefficient is obtained to correct the preliminary natural evaporation BOG prediction model, thereby the generation amount of the natural evaporation BOG of the LNG ship can be accurately predicted, and a solid foundation is laid for the management of the natural evaporation BOG of the LNG ship.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
Fig. 2 is a schematic diagram of the system of the present invention.
Detailed Description
The LNG ship natural evaporation BOG prediction method comprises the following steps, wherein a flow chart of the method is shown in figure 1:
s1: acquiring initial cargo state data of the LNG ship in a multi-voyage full-load normal voyage state, and performing the next step when the difference value between the initial cargo state data of the LNG ship in the multi-voyage state and the historical average data is within a corresponding set threshold range; the initial cargo state data comprise liquid cargo temperature, pressure and liquid level, wherein the set threshold value of the liquid cargo temperature is 3 times of the standard deviation of the liquid cargo temperature and the historical average value, the set threshold value of the pressure is 3 times of the standard deviation of the pressure and the historical average value, the set threshold value of the liquid level is 3 times of the standard deviation of the liquid level and the historical average value, if the difference value between the initial cargo state data of the LNG ship with multiple voyages and the corresponding historical average data does not exceed the value of 3 times of the standard deviation, the corresponding BOG under the marine environmental condition of the LNG ship is started, otherwise, the system is not started, and the abnormality is warned;
s2: acquiring and storing the ship environment temperature, the ship environment sea state data and the corresponding natural evaporation BOG data of the LNG ship in a full-load normal sailing state for multiple voyages;
because the two parameters of the ship environment temperature and the sailing ship environment sea state grade are key factors influencing the natural evaporation BOG fluctuation, the two parameters of the ship environment temperature and the sailing ship environment sea state grade are selected during testing, and the ship environment temperature takes a weighted average of the environment sea water surface temperature and the environment sea air temperature and can be calculated according to the formula (1):
（1）；
wherein:for the ambient temperature of the ship, < > is->Is the surface temperature of the ambient seawater, < > is->The weight coefficient of the surface temperature of the ambient seawater can be 0.6%>Is ambient marine air temperature, +.>The weight of the environmental marine air temperature can be 0.4, so that the obtained ship environmental temperature is more favorable for later prediction, the prediction result is more accurate, and the ship environmental sea condition data refer to the sea wave grade of the LNG ship directly obtained from the marine environment prediction network.
S3: classifying the acquired ship environment temperature and ship environment sea state data, comparing the obtained ship environment temperature and ship environment sea state data with the associated natural evaporation BOG value to obtain associated functions of the ship environment temperature and the ship environment sea state and the natural evaporation BOG respectively, and obtaining a preliminary natural evaporation BOG prediction model corresponding to the ship environment temperature and the ship environment sea state two important parameters;
the preliminary natural evaporation BOG prediction model is obtained by the following method:
s31: storing, screening and training natural evaporation BOG data under the condition that the ship environment temperature corresponds to the ship environment sea state data by adopting a statistical method, and manufacturing a data graph of the relationship among the ship environment temperature, the ship environment sea state and the natural evaporation BOG by using a chart visualization tool;
s32: according to the data graph of the relationship between the ship environment temperature, the ship environment sea condition and the natural evaporation BOG, a four-parameter fitting equation is utilized to select a proper function curve, a relationship correlation curve reflecting the relationship between the marine environment and the natural evaporation BOG data is obtained, and a corresponding function model is formed;
the four-parameter fitting equation is of formula (2):
（2）；
wherein:representing the ship ambient temperature or the ship ambient sea state, representing the independent variable of the function curve,/->Represents the BOG value of natural evaporation, represents the dependent variable of the function curve, < ->Representing the lower limit of the natural evaporation BOG, representing the lower asymptote of the function curve, ++>Represents the upper limit of the natural evaporation BOG, represents the upper asymptote of the function curve, ++>A value indicating that the argument influences the growth rate to begin to change,/->Represents the rate of increase parameter, representing the slope of the function curve.
Further, the preliminary natural evaporation BOG prediction model obtained in step S33 is formula (3):
（3）；
wherein:represents the predicted value of BOG for natural evaporation, +.>Representing the predicted value of BOG naturally evaporated under the influence of the temperature of the offshore environment,/->Weight representing predicted value of natural evaporation BOG under influence of offshore environment temperature, < + >>Representing the predicted value of BOG naturally evaporated under the influence of the sea conditions of the ship environment, < >>The weight of the natural evaporation BOG predicted value under the influence of the ship environment and sea conditions is represented;
s33: and evaluating the fitting degree and the prediction capacity of the function model by using a statistical method, evaluating and verifying by using a residual analysis and a pearson correlation coefficient method, and if the fitting degree and the prediction capacity of the function model do not meet the requirements, reselecting the function curve and re-fitting until the fitting degree and the prediction capacity of the function model meet the requirements, thereby obtaining the preliminary natural evaporation BOG prediction model.
By adopting the method, the corresponding natural evaporation BOG predicted value under the specific offshore environment can be accurately obtained, and a foundation is laid for predicting the natural evaporation BOG value of the LNG ship.
S4: comparing the acquired ship environment temperature and ship environment sea state data of the LNG ship in the full-load normal sailing state with the design conditions respectively, finding out corresponding natural evaporation BOG data when the ship environment temperature and the ship environment sea state data of the corresponding LNG ship in the full-load normal sailing state are closest to the design conditions respectively, converting the natural evaporation BOG data into basic BOR values respectively, and comparing trend analysis is carried out on all basic BOR values with the factory design BOR data to obtain a natural evaporation BOG value correction coefficient;
s5: and correcting the preliminary natural evaporation BOG prediction model by using the natural evaporation BOG value correction coefficient to obtain a corrected natural evaporation BOG prediction model.
According to the method, the natural evaporation BOG value correction coefficient is calculated, and the natural evaporation BOG value correction coefficient is used for correcting the preliminary natural evaporation BOG prediction model to obtain the corrected natural evaporation BOG prediction model, so that the influence of the change of the self conditions of the LNG ship on the preliminary natural evaporation BOG prediction model can be corrected, the predicted natural evaporation BOG is more accurate, and a solid foundation is laid for the management of the natural evaporation BOG of the LNG ship.
Optimally, the design condition in the step S4 is that the temperature of the ambient marine air is 5 ℃, the temperature of the surface layer of the ambient seawater is 0 ℃, and the grade of the ambient sea condition of the ship is less than or equal to one grade.
Further, in step S4, the corrected natural evaporation BOG prediction model is represented by formula (4):
（4）；
wherein:for the corrected natural evaporation BOG prediction value, -/-, for>And represents the correction coefficient of the natural evaporation BOG value.
An LNG ship natural evaporation BOG prediction system for executing the LNG ship natural evaporation BOG prediction method described in any one of the above, wherein the system schematic diagram is shown in fig. 2, and the system schematic diagram includes an LNG ship cargo state monitoring unit, an offshore environment monitoring unit, a BOG data processing control unit, and a BOG flow monitoring unit, wherein the LNG ship cargo state monitoring unit is used for collecting LNG ship cargo state data in an LNG ship full voyage state, the offshore environment monitoring unit is used for collecting ship environment temperature and ship environment sea state data in an LNG ship full voyage normal voyage state, the BOG flow monitoring unit is used for collecting natural evaporation BOG data corresponding to the offshore environment, the BOG data processing control unit includes a cargo hold BOG data storage module, a cargo hold BOG data comparison correlation module, and a cargo hold BOG data correction module, the cargo hold BOG data storage module is used for collecting, storing, training real-time natural evaporation BOG and corresponding offshore environment monitoring data, the cargo hold BOG data comparison correlation module is used for analyzing correlation between the offshore environment and natural evaporation BOG data, and selecting a fitting function and a comparison verification function, and the cargo evaporation BOG data correction module is used for collecting natural evaporation BOG data corresponding to the voyage predicted value.
According to the natural evaporation BOG prediction method and system for the LNG ship, provided by the invention, the data of the influence of the marine navigation environment factors on the natural evaporation BOG during the full-load navigation of the LNG ship for multiple times are collected, the correlation functions of the ship environment temperature and the ship environment sea condition and the natural evaporation BOG are extracted, the natural evaporation BOG prediction model corresponding to the ship environment temperature and the ship environment sea condition is obtained, the basic BOR value of the LNG ship is calculated, the basic BOR value is compared with the factory design BOR data for trend analysis, the natural evaporation BOG value correction coefficient is obtained to correct the natural evaporation BOG value, the influence of the change of the conditions of the LNG ship on the natural evaporation BOG prediction model is corrected, the natural evaporation BOG value of the LNG ship is predicted to be more accurate, and a solid foundation is laid for the management of the natural evaporation BOG of the LNG ship.
In summary, the method and the system for predicting the natural evaporation BOG of the LNG ship can accurately predict the value of the natural evaporation BOG of the LNG ship under the influence of two important parameters, namely the ship environment temperature and the ship environment sea state, correct the influence of the change of the condition of the LNG ship on the natural evaporation BOG predicted value, predict the natural evaporation BOG value of the LNG ship more accurately, and lay a solid foundation for the management of the natural evaporation BOG of the LNG ship.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The natural boil-off gas prediction method for the LNG ship is characterized by comprising the following steps of:
s1: acquiring initial cargo state data of the LNG ship in a multi-voyage full-load normal voyage state, and performing the next step when the difference value between the initial cargo state data of the LNG ship in the multi-voyage state and the historical average data is within a corresponding set threshold range;
s2: acquiring and storing the ship environment temperature, the ship environment sea state data and the corresponding natural evaporation gas data of the LNG ship in the normal sailing state of multiple voyages;
s3: classifying the acquired ship environment temperature and ship environment sea state data, comparing the obtained ship environment temperature and ship environment sea state data with the associated natural evaporation gas values to obtain associated functions of the ship environment temperature and the ship environment sea state and the natural evaporation gas respectively, and obtaining a preliminary natural evaporation gas prediction model corresponding to the ship environment temperature and the ship environment sea state two important parameters;
s4: comparing the acquired ship environment temperature and ship environment sea state data of the LNG ship in the full-load normal sailing state with the design conditions respectively, acquiring corresponding natural evaporation gas data when the ship environment temperature and the ship environment sea state data of the corresponding LNG ship in the full-load normal sailing state are closest to the design conditions respectively, converting the natural evaporation gas data into basic BOR values respectively, and comparing trend analysis is carried out on all basic BOR values with the factory design BOR data to obtain a natural evaporation gas value correction coefficient;
s5: and correcting the preliminary natural evaporation vapor prediction model by using the natural evaporation vapor value correction coefficient to obtain a corrected natural evaporation vapor prediction model.
2. The method for predicting natural boil-off gas of an LNG ship according to claim 1, wherein the initial cargo state data in step S1 includes a cargo temperature, a pressure and a liquid level, the cargo temperature is set to a threshold value 3 times a standard deviation of the cargo temperature from a historical average value, the pressure is set to a threshold value 3 times a standard deviation of the pressure from the historical average value, and the liquid level is set to a threshold value 3 times a standard deviation of the liquid level from the historical average value.
3. The method for predicting natural boil-off gas of an LNG ship according to claim 1, wherein the ship ambient temperature in step S2 is a weighted average of the ambient sea water skin temperature and the ambient sea air temperature.
4. A method of predicting natural boil-off gas for an LNG ship according to claim 3, wherein the ship ambient temperature is calculated according to formula (1):
（1）；
wherein:for the ambient temperature of the ship, < > is->Is the surface temperature of the ambient seawater, < > is->Is the weight coefficient of the temperature of the surface layer of the environmental seawater, +.>Is ambient marine air temperature, +.>Is a weight for the ambient offshore air temperature.
5. The LNG ship natural boil-off gas prediction method according to claim 1, wherein the preliminary natural boil-off gas prediction model is obtained in step S3 according to the following method:
s31: storing, screening and training the natural evaporation and evaporation gas data corresponding to the ship environment temperature and the ship environment sea state data of the LNG ship for multiple voyages by adopting a statistical method, and manufacturing a data graph of the relationship among the ship environment temperature, the ship environment sea state and the natural evaporation and evaporation gas by using a chart visualization tool;
s32: according to the data graph of the relationship between the ship environment temperature, the ship environment sea condition and the natural evaporation gas, selecting a proper function curve by utilizing a four-parameter fitting equation to obtain a relationship correlation curve reflecting the relationship between the marine environment and the natural evaporation gas data, and forming a corresponding function model;
s33: and evaluating the fitting degree and the prediction capacity of the function model, and verifying, if the fitting degree and the prediction capacity of the function model do not meet the requirements, reselecting the function curve and re-fitting until the fitting degree and the prediction capacity of the function model meet the requirements, thereby obtaining the preliminary natural evaporation gas prediction model.
6. The method for predicting natural boil-off gas of an LNG ship according to claim 5, wherein the four-parameter fitting equation in step S32 is formula (2):
（2）；
wherein:representing the ambient temperature of the ship or the sea state of the ship, < +.>Indicating the value of natural evaporating vapor->Indicates the lower limit value of the natural evaporation vapor, +.>Represents the upper limit value of the natural evaporation vapor, +.>A value indicating that the argument influences the growth rate to begin to change,/->Indicating the rate of increase parameter.
7. The LNG ship natural boil-off gas prediction method according to claim 5, wherein the preliminary natural boil-off gas prediction model obtained in step S33 is formula (3):
（3）；
wherein:representing the predicted value of natural evaporation vapor, +.>Representing predicted value of natural evaporation gas under influence of offshore environment temperature,/->Weight representing natural evaporation gas prediction value under influence of offshore environment temperature, +.>Representing the predicted value of natural evaporation gas under the influence of the sea conditions of the ship environment, < ->And the weight of the natural evaporation gas predicted value under the influence of the ship environment and sea conditions is expressed.
8. The method for predicting natural boil-off gas of an LNG ship according to claim 1, wherein the design condition in step S4 is that the ambient sea air temperature is 5 ℃, the ambient sea surface temperature is 0 ℃, and the ship ambient sea condition level is less than or equal to one stage.
9. The LNG ship natural boil-off gas prediction method according to claim 7, wherein the modified natural boil-off gas prediction model in step S4 is represented by formula (4):
（4）；
wherein:for the modified natural evaporation gas prediction value, < >>The natural evaporation gas value correction coefficient is shown.
10. An LNG ship natural boil-off gas prediction system, characterized in that it is configured to perform an LNG ship natural boil-off gas prediction method according to any one of claims 1 to 9, and the LNG ship natural boil-off gas prediction system includes an LNG ship cargo state monitoring unit, an offshore environment monitoring unit, a boil-off gas data processing control unit, and a boil-off gas flow monitoring unit, where the LNG ship cargo state monitoring unit is configured to collect LNG ship cargo state data in an LNG ship full voyage state, the offshore environment monitoring unit is configured to collect ship environment temperature and ship environment sea state data in an LNG ship full voyage normal voyage state, the boil-off gas flow monitoring unit is configured to collect natural boil-off gas data corresponding to the voyage marine environment, and the boil-off gas data processing control unit includes a cargo hold boil-off gas data storage module, a cargo hold boil-off gas data comparison correlation module, and a cargo hold boil-off gas data correction module, where the cargo hold boil-off gas data storage module is configured to collect, store, train real-time natural boil-off gas and corresponding marine environment monitoring data, and select a function, and a comparison verification function, and correct cargo hold boil-off gas data correction value for natural boil-off gas prediction value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311508529.XA CN117235903B (en) | 2023-11-14 | 2023-11-14 | LNG ship natural evaporation BOG prediction method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311508529.XA CN117235903B (en) | 2023-11-14 | 2023-11-14 | LNG ship natural evaporation BOG prediction method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117235903A CN117235903A (en) | 2023-12-15 |
| CN117235903B true CN117235903B (en) | 2024-01-26 |
Family
ID=89095290
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311508529.XA Active CN117235903B (en) | 2023-11-14 | 2023-11-14 | LNG ship natural evaporation BOG prediction method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117235903B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117950430A (en) * | 2024-03-26 | 2024-04-30 | 中海油能源发展股份有限公司采油服务分公司 | Method and system for controlling cabin pressure of bulk liquefied gas carrier in estuary inland river |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108663727A (en) * | 2017-03-31 | 2018-10-16 | 西北工业大学 | The method for estimating height of evaporation duct within the scope of world marine site using evaporation rate |
| WO2019044797A1 (en) * | 2017-08-31 | 2019-03-07 | 川崎重工業株式会社 | Spray vaporization rate prediction method and device, and operation assistance method and system for liquefied gas carrying vessel |
| KR20210065215A (en) * | 2019-11-26 | 2021-06-04 | 대우조선해양 주식회사 | Method for estimating bog influence by considering voyage data and marine environment data in lngc |
| CN113988771A (en) * | 2021-12-29 | 2022-01-28 | 中海油能源发展股份有限公司采油服务分公司 | LNG transport ship cargo remote management system and LNG transport ship |
| KR20220064156A (en) * | 2020-11-11 | 2022-05-18 | 대우조선해양 주식회사 | Method for calculating boil off rate of excessive boil off gas in cargo hold |
| KR20230040471A (en) * | 2021-09-16 | 2023-03-23 | 삼성중공업 주식회사 | Condition prediction system and method of LNG storage tank |
| KR20230097421A (en) * | 2021-12-24 | 2023-07-03 | 한화오션 주식회사 | Method for calculating boil-off gas rate according to ship voyage and navigating autonomously by using boil-off gas rate and computer-readable recording medium including the same |
| CN116529521A (en) * | 2020-12-03 | 2023-08-01 | 气体运输技术公司 | Method and system for assisting management of a liquefied gas carrier of the type that consumes boil-off gas to enable propulsion of the liquefied gas carrier |
-
2023
- 2023-11-14 CN CN202311508529.XA patent/CN117235903B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108663727A (en) * | 2017-03-31 | 2018-10-16 | 西北工业大学 | The method for estimating height of evaporation duct within the scope of world marine site using evaporation rate |
| WO2019044797A1 (en) * | 2017-08-31 | 2019-03-07 | 川崎重工業株式会社 | Spray vaporization rate prediction method and device, and operation assistance method and system for liquefied gas carrying vessel |
| KR20210065215A (en) * | 2019-11-26 | 2021-06-04 | 대우조선해양 주식회사 | Method for estimating bog influence by considering voyage data and marine environment data in lngc |
| KR20220064156A (en) * | 2020-11-11 | 2022-05-18 | 대우조선해양 주식회사 | Method for calculating boil off rate of excessive boil off gas in cargo hold |
| CN116529521A (en) * | 2020-12-03 | 2023-08-01 | 气体运输技术公司 | Method and system for assisting management of a liquefied gas carrier of the type that consumes boil-off gas to enable propulsion of the liquefied gas carrier |
| KR20230040471A (en) * | 2021-09-16 | 2023-03-23 | 삼성중공업 주식회사 | Condition prediction system and method of LNG storage tank |
| KR20230097421A (en) * | 2021-12-24 | 2023-07-03 | 한화오션 주식회사 | Method for calculating boil-off gas rate according to ship voyage and navigating autonomously by using boil-off gas rate and computer-readable recording medium including the same |
| CN113988771A (en) * | 2021-12-29 | 2022-01-28 | 中海油能源发展股份有限公司采油服务分公司 | LNG transport ship cargo remote management system and LNG transport ship |
Non-Patent Citations (2)
| Title |
|---|
| "A voyage optimization model of LNG carriers considering boil-off gas";Seyong Jeong et al.;《OCEANS 2019 MTS/IEEE SEATTLE》;全文 * |
| "大型LNG 储备站蒸发气( BOG) 产生量及其特点的分析";翟俊红 等;《山东化工》;第44卷(第4期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117235903A (en) | 2023-12-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117235903B (en) | LNG ship natural evaporation BOG prediction method and system | |
| Dedes et al. | Assessing the potential of hybrid energy technology to reduce exhaust emissions from global shipping | |
| Borkowski et al. | Assessment of ship's engine effective power, fuel consumption and emission using the vessel speed | |
| CN111310972A (en) | Offshore wind turbine maintenance path random planning method considering wake effect | |
| CN110705797A (en) | Ship oil consumption data prediction method based on ship sensor network | |
| CN112088122B (en) | Method and system for evaluating actual sea area propulsion performance of ship and computer readable storage medium | |
| CN103017895A (en) | Laying method for vibration monitoring points of offshore wind power generation support structure | |
| JP2019018641A (en) | Ship performance analysis system and ship performance analysis method | |
| Wan et al. | A review on the technical development of combined wind and wave energy conversion systems | |
| CN116611628A (en) | Two-stage capacity configuration method of comprehensive energy production unit considering dynamic performance | |
| CN116316683A (en) | Method, system and computer readable medium for online evaluation of primary frequency modulation capability of unit based on energy contribution degree | |
| CN105241760A (en) | Method for testing bending strength of sea ice | |
| Gutiérrez et al. | An empirical analysis on the operational profile of liquefied natural gas carriers with steam propulsion plants | |
| Vasilikis | Operational data-driven energy efficiency and effectiveness assessment of a hybrid propulsion equipped naval vessel | |
| Jeon et al. | Energy management system in naval submarines | |
| Baardsen | A concept study on offshore floating hydrogen production, storage, and offloading | |
| Pani et al. | A vikors method-based multi-criteria decision analysis for energy storage system selection for wave energy | |
| CN111275320A (en) | Performance adjustment data processing method and system of generator set and storage medium | |
| KR20210051547A (en) | Operation Support System for Liquefied Gas Carrier | |
| Marques et al. | AN APPROACH TO OPTIMISE THE SELECTION OF LNG CARRIERS’PROPULSION SYSTEM | |
| CN117521947B (en) | Hybrid power ship energy efficiency ratio optimization method, system, medium and equipment | |
| Francisco de Santos et al. | Farm-wide fatigue loads estimation: a data-driven approach | |
| Kleivane et al. | Reliability Analysis of Crack Growth Occurrence for a Secondary Structural Component due to Vibration Excitation | |
| KR102541355B1 (en) | Charging control method for marine batteries AND COMPUTER-READABLE RECORDING MEDIUM INCLUDING THE SAME | |
| CN117251692B (en) | Ship oil consumption energy-saving evaluation method based on fuel oil cleaning synergistic agent |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |