JP2014127045A - Operation supporting system, and operation supporting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To modify an energy prediction model of a passenger boat to match with the reality by using monitoring data of a past record, and to present energy prediction with a higher degree of precision and a fuel optimum operation plan.SOLUTION: A demand for electric power is predicted with the use of an energy prediction model of a passenger boat, weather and marine phenomenon prediction data, and a plan of a sea route, and a fuel optimum operation plan which is an operation plan with the optimal fuel consumption efficiency is presented. Actual performance of energy of the passenger boat, weather and a marine phenomenon, and an operation state is monitored on the basis of the fuel optimum operation plan. A model corresponding to the fuel optimum operation plan is modified on the basis of the monitoring result. In that case, the model is modified by setting a correlation function with an individual parameter by multivariable analysis with the use of accumulated data of similar sea routes of the same ship in the same season, and by combining contribution of each parameter with the use of a contribution coefficient.

Description

  The present invention relates to an operation support system, and more particularly to an operation support system for passenger ships and the like.

  Even now, operation according to the weather, sea conditions, etc. often relies on the experience and intuition of the captain. Ship operation information is only used for the duration of the voyage, is rarely acquired and stored as a database, and is not used for the next voyage.

  In the current technology, some manufacturers have commercialized systems for general ships. In addition, attempts are being made to acquire ship operation information and create a database.

  However, most of these objects are general merchant ships and cannot be applied to passenger ships. General merchant ships have a single propulsion unit (fuel consumption is determined only by propulsion unit efficiency). To reduce fuel, only the propulsion unit needs to be considered and only the propulsion model is targeted.

  In contrast, passenger ships use energy comparable to the energy used for propulsion for their inhabited systems. In addition, power is generated by a plurality of generators separate from the propulsion device, and the electricity is used for both the propulsion motor and the inboard power. For this reason, in addition to the propulsion model, it is necessary to consider an inboard power equipment model and a generator model, and in addition, the use of exhaust heat affects the inboard power.

[Known technology]
In order to improve the accuracy of the operation support system, there is an example in which operation data is accumulated and applied to correction correction of the model. For example, Patent Document 1 (Japanese Unexamined Patent Application Publication No. 2012-86604) is disclosed as a known technique in this technical field. This known technique relates to general merchant ships, and only targets propulsion models.

  In addition, as a known technique in this technical field, Japanese Patent Application Laid-Open No. 2009-505210 discloses a technique for optimizing use of an energy source in a ship. This known technique creates a computer simulation model of a ship that is optimized for fuel efficiency. When creating a computer simulation model, an equation is selected from a group of equations describing the core components and structural features of the ship, and data is selected from a feature data group regarding the core components and structures of the vessel. In addition, a computer simulation model is used to optimize the fuel efficiency of the ship. However, this known technique considers optimizing the use of energy sources, but does not consider optimization based on simulation based on energy prediction and energy demand in residential areas.

JP 2012-86604 A Special table 2009-505210

  As described above, since most (most) of the power is consumed in the propulsion system in the conventional operation support system, the route is selected from the meteorological information so that it can be operated with efficient propulsion energy. In addition, there is one propulsion system, and efficient propulsion energy is determined only by the propeller characteristics.

  If a large ship such as a passenger ship becomes mainstream, and the low-speed operation becomes mainstream, the above-mentioned operation support system will not be able to handle it, and combined with rising fuel costs, a new operation support system and operation guidelines that save energy will be required. It was.

  The validity of the model of the cruise ship support system is unknown. In addition, the operational model in the case of stormy weather may be different from the actual situation, and the long-term use may change the state of the power generation engine and propulsion device and deteriorate the fuel consumption, and the outer surface condition of the passenger ship It is also possible that propulsion resistance will increase due to changes. However, these considerations are not shown.

  Therefore, it is necessary to improve the accuracy by correcting and correcting the model based on the operation monitoring data. Even with reference to Patent Document 1 (Japanese Patent Application Laid-Open No. 2012-86604), the propulsion model is modeled on the basis of relatively calm sea conditions, and the accuracy is not sufficient in rough sea conditions.

  Since passenger ships are more complex than ordinary merchant ships, it is currently difficult to derive correction corrections for models as general solutions.

  The operation support system according to the present invention uses a passenger ship energy prediction model, weather and sea state prediction data, and a route plan to predict power demand, and presents an optimal fuel consumption operation plan that is an operation plan with optimal fuel consumption efficiency. Based on the mechanism and the optimum fuel consumption operation plan, a mechanism for monitoring the energy of the passenger ship, the weather condition, and the operation state, and a mechanism for correcting the model for the optimum fuel consumption operation plan based on the monitoring result are provided. The mechanism that modifies the model uses the accumulated data of similar routes in the same ship and the same season, sets the correlation function with individual parameters by multivariate analysis, and combines the contribution of each parameter using the contribution coefficient. A mechanism for correcting the ship's power model, and a mechanism for correcting the ship's propulsion model indicating the relationship between propulsion speed and power consumption in the order of wind direction dependency and propulsion power.

  The operation support method according to the present invention is an operation support method implemented by an electronic device. In this operation support method, power demand prediction is performed using an energy prediction model of a passenger ship, weather and sea state prediction data, and a route plan, and an optimal fuel consumption operation plan, which is an operation plan with optimal fuel consumption efficiency, is presented. Moreover, based on the said fuel consumption optimal operation plan, the track record of the energy of a passenger ship, a weather sea condition, and an operation state is monitored. Based on the monitoring results, when correcting the model for the fuel efficiency optimal operation plan, using the accumulated data of similar routes in the same ship and the same season, a correlation function with individual parameters is set by multivariable analysis. The ship power model is corrected by combining contributions for each parameter using the contribution coefficient. In addition, the ship propulsion model indicating the relationship between propulsion speed and power consumption is corrected in the order of wind direction dependency and propulsion power.

  The program which concerns on this invention is a program for making electronic devices, such as a computer, perform the process in said operation support method. The program according to the present invention can be stored in a storage device or a storage medium.

  In an operation support system for passenger ships, it becomes possible to present energy predictions and fuel consumption optimal operation plans with higher accuracy than the current situation.

It is a figure showing the example of composition of the operation support system concerning the present invention. It is a figure which shows the other example of arrangement | positioning of an operation assistance apparatus and an energy utilization monitoring apparatus. It is a figure which shows the structural example of the operation assistance apparatus which concerns on embodiment.

<Embodiment>
Embodiments of the present invention will be described below with reference to the accompanying drawings.

  In this embodiment, power demand is predicted using the passenger ship's energy prediction model, meteorological and sea state prediction data, and the route plan, and an operation plan (optimum fuel consumption operation plan) with optimal fuel consumption efficiency (minimum fuel consumption) is made. Monitoring, monitoring the ship's energy, weather conditions, and operational status, and revising the model for the optimal fuel efficiency operation plan.

[System configuration]
With reference to FIG. 1, the structural example of the operation support system which concerns on this invention is demonstrated.

  The operation support system according to the present invention includes an operation support device 10 and an energy utilization monitoring device 20.

  The operation support device 10 uses the operation plan 1, weather and sea state prediction data 2, ship position information 3, inboard event plan 4, ship performance data 5, and operation result data 6 to predict power demand, and the optimum fuel consumption operation plan. 7 is created. Further, the operation support device 10 corrects the model for the fuel efficiency optimal operation plan 7 based on the result of monitoring.

  The operation plan 1 is an operation plan created in advance (in advance). The meteorological sea state prediction data 2 is meteorological sea state prediction data sequentially notified from an artificial satellite or the like. The ship position information 3 is ship position data sequentially notified from GPS or the like. The inboard event plan 4 is an inboard event schedule. The inboard event plan 4 may be created based on the operation result data 6. The ship performance data 5 is data indicating the performance of the ship. The ship performance data 5 is made into a database. The operation record data 6 is data indicating a record value (actual value) obtained as a result of monitoring. The operation result data 6 is made into a database. The fuel consumption optimal operation plan 7 is an operation plan in which the fuel consumption efficiency is optimal (the fuel consumption is minimum). The fuel consumption optimal operation plan 7 is used as the operation plan 1 after the model is corrected.

  The energy usage monitoring device 20 monitors the passenger ship's energy, weather conditions, and operational status based on the fuel efficiency optimal operation plan 7. For example, the energy usage monitoring device 20 indicates the state of the propulsion system, power system, meteorological state, onboard equipment, etc. via the sensor group 21 which is a set of various sensors during the operation based on the optimum fuel consumption operation plan 7. Monitor.

  In particular, the energy of a passenger ship is mainly comprised of propulsion energy determined by weather conditions, ship speed, and the propulsion performance inherent to the passenger ship, and inboard power energy.

  Since the propulsion energy prediction model is initially set from model calculation and model test, it is assumed that it is different from the actual ship. Therefore, the energy utilization monitoring device 20 has meteorological sea state data (wave height, wind speed, tidal current direction speed, wind direction and speed, draft), the engine used, the output / rotation speed / fuel supply amount of the engine. Then, the relationship between the propulsion speeds of the cruise ship is made into a database as operation result data 6. The operation support apparatus 10 corrects and optimizes the original propulsion energy prediction model according to the operation result data 6.

  In addition, there is a concern that the state of the ship changes during long-term engine use and fuel consumption deteriorates. For example, it is assumed that propulsion unit shaft vibration is enhanced, propeller deformation, propulsion resistance change due to changes in the outer surface of a passenger ship (coating peeling, fujitsumi adhesion, etc.). The operation support device 10 recognizes the deviation (divergence) from the ship performance data 5 and promotes the operation support system in accordance with the state of the passenger ship at that time so that fuel consumption calculation and optimum operation can be presented in that situation. Correct and correct the energy prediction model.

  Moreover, the energy utilization monitoring apparatus 20 also makes the database of the operation values of the main devices and the actual values of the power monitoring data as the operation actual data 6 for the onboard power energy. The operation support apparatus 10 corrects and optimizes the original shipboard power energy prediction model according to the operation result data 6.

[Remarks]
In addition, although it is suitable for the energy utilization monitoring apparatus 20 to exist in a ship, the operation assistance apparatus 10 does not necessarily need to be in a ship. For example, as shown in FIG. 2, it is also possible to install the energy utilization monitoring device 20 on the ship and install the operation support device 10 outside the ship. In this case, it is assumed that the operation support device 10 and the energy usage monitoring device 20 perform wireless communication with each other.

[Example configuration of navigation support equipment]
With reference to FIG. 3, the structural example of said operation support apparatus 10 is demonstrated.

  The operation support apparatus 10 includes an operation plan creation unit 11 and a model correction unit 12.

  The operation plan creation unit 11 uses the operation plan 1, weather and sea state prediction data 2, ship position information 3, inboard event plan 4, ship performance data 5, and operation result data 6 to predict power demand and to operate fuel efficiency optimally. Create plan 7.

  The model correction unit 12 corrects the model for the fuel efficiency optimal operation plan 7 based on the result of monitoring by the energy usage monitoring device 20.

  Here, the model correction unit 12 includes an inboard power model correction unit 121, a propulsion model correction unit 122, and a power generation model correction unit 123.

  Each of the inboard power model correction unit 121, the propulsion model correction unit 122, and the power generation model 33 sets and applies a correction coefficient by multivariable analysis using relatively similar data. Specifically, using the accumulated data of similar routes in the same ship and the same season, a correlation function with individual parameters is set by multivariable analysis, and contributions for each parameter are combined using a contribution coefficient.

  Multivariable analysis is a statistical technique for analyzing the correlation between data based on data consisting of a plurality of values (multivariate data). For each major factor, the difference is expressed by a linear function or a quadratic function, and those principal components are selected and combined.

[Inboard power model correction section]
The inboard power model correction unit 121 is a correlation function for individual parameters such as temperature (A), weather (B), number of passengers (C), exhaust heat utilization (D), time (E), etc. Based on F (x), the difference (Δ) between the predicted value and the actual value of the inboard power (power used in the ship) is set using the least square method. Here, the accuracy is determined based on the standard deviation of the difference (Δ) between the predicted value of the inboard power and the actual value, and the correlation function is set in order from the highest accuracy. The accuracy is improved by reviewing the upper function after setting the lower correlation function as necessary. In this way, a highly accurate correlation function of several parameters is set and selected, a correction function Δ is obtained by combining the correlation functions of these parameters, and the ship power model is corrected and applied based on the correction function Δ.

  Δ = fa (A) + fb (B) + fc (C) + fd (D) + fe (E) +.

[Propulsion Model Modification Department]
The propulsion model correction unit 122 corrects the ship propulsion model (model indicating the relationship between the propulsion speed and power consumption) in the order of wind direction dependency and propulsion power.

  Regarding the wind direction dependency, the relationship between the angle of the wind direction, the predicted value of the propulsion power, and the actual value is graphed and corrected by approximating the Nth order equation. Here, 4 to 6 are applied as N.

  The propulsion power is basically proportional to the third power of the boat speed, so the third power of the boat speed (A), the second power of the boat speed (B), the first power of the boat speed (C), the relative wind speed (D ), Relative tidal current (E), propulsion device output (F), draft (G), engine room temperature (H), water temperature (I), accumulation (number of passengers, etc.) (J), etc. Based on the function F (x), the difference (Δ) between the predicted value and the actual value of the propulsion power is set using the least square method. The accuracy is determined by the standard deviation of the difference (Δ) between the predicted value and the actual value, and the correlation function is set in order from the highest accuracy. The accuracy is improved by reviewing the upper function after setting the lower correlation function as necessary. In this way, a highly accurate correlation function of several parameters is set and selected, a correction function Δ is obtained by combining the correlation functions of these parameters, and the propulsion model is corrected and applied based on the correction function Δ.

  Δ = fa (A) + fb (B) + fc (C) + fd (D) + fe (E) +.

[Power generation model correction section]
The power generation model correcting unit 123 corrects the model based on the predicted value to the model based on the actual value using the relationship between the predicted value of the fuel consumption for each power generation output and the actual value for the power generation model.

[Result]
A model created from the data for the third time on a route from a cruise database of a passenger ship shows that the difference in fuel consumption is the standard deviation when the results of energy predictions and actual results for the fourth and fifth times are compared. The result of the 7th verification with a model created from 6 data is 6%, and the standard deviation of the difference is 4% in the model created from 10 data. And improved accuracy was confirmed.

  In the above description, the predicted value is corrected as the correction coefficient. However, in practice, it is desirable to review the model itself when the performance data is accumulated. By doing so, the difference between the predicted value and the actual value can be reduced, and the variation (distribution) of the difference is also reduced, so that the accuracy of calculating the correction coefficient in the present embodiment is also improved. Actually, when the model itself was reviewed based on the 10 data in this embodiment, the standard deviation of the difference was 3%.

[Operation and effect of this embodiment]
As described above, it is possible to present more accurate energy prediction and optimum fuel consumption operation plan by using the actual monitoring data and correcting the energy prediction model of the passenger ship according to the actual situation.

  The operation support system according to the present invention is assumed to be operated in a relatively similar situation (route, season, etc.). Unlike ordinary merchant ships, passenger ships operate relatively short routes of about 1 to 10 days depending on the season, so it is possible to accumulate data in similar situations, and model correction using accumulated data in that case・ Correction is performed.

  The operation support system according to the present invention may be mounted on a target ship, or may be mounted on a satellite or the like and communicate with the ground (land station) or the target ship from the satellite or the like.

  Note that the operation support system according to the present invention can be applied to the prediction of the maintenance time of equipment by analyzing the change over time for each equipment based on the result of monitoring.

<Example of hardware>
Below, the example of the concrete hardware for implement | achieving the operation assistance system which concerns on this invention is demonstrated.

  Although not shown, the navigation support system according to the present invention includes a processor that is driven based on a program and executes predetermined processing, a memory that stores the program and various data, and an interface used for communication with a network. It may be realized by an electronic device such as a computer.

  Examples of the processor include a CPU (Central Processing Unit), a network processor (NP), a microprocessor, a microcontroller (microcontroller), or a semiconductor integrated circuit (LSI: Large Scale) having a dedicated function. Integration) or the like.

  Examples of the memory include semiconductor storage devices such as a RAM (Random Access Memory), a ROM (Read Only Memory), an EEPROM (Electrically Erasable and Programmable Read Only Memory), a flash memory, and an HDD (Hold SMD). An auxiliary storage device such as State Drive), a removable disk such as a DVD (Digital Versatile Disk), a storage medium such as an SD memory card (Secure Digital memory card), or the like is conceivable. Further, a buffer, a register, or the like may be used. Alternatively, DAS (Direct Attached Storage), FC-SAN (Fibre Channel-Storage Area Network), NAS (Network Attached Storage), IP-SAN (IP-Storage Area), etc. may be used.

  Note that the processor and the memory may be integrated. For example, in recent years, a single chip such as a microcomputer has been developed. Therefore, a case where a one-chip microcomputer mounted on an electronic device or the like includes the processor and the memory can be considered.

  Examples of the interfaces include semiconductor integrated circuits such as substrates (motherboards and I / O boards) and chips that support network communication, network adapters such as NIC (Network Interface Card), and similar expansion cards and communication devices such as antennas. A communication port such as a connection port (connector) is conceivable.

  Examples of the network include the Internet, a LAN (Local Area Network), a wireless LAN (Wireless LAN), a WAN (Wide Area Network), a backbone (Backbone), a cable television (CATV) line, a fixed telephone network, a mobile phone network, WiMAX (IEEE 802.16a), 3G (3rd Generation), dedicated line (lease line), IrDA (Infrared Data Association), Bluetooth (registered trademark), serial communication line, data bus, and the like can be considered.

  The internal components of the operation support system may be a module, a component, a dedicated device, or an activation (calling) program thereof.

  However, actually, it is not limited to these examples.

<Remarks>
As mentioned above, although embodiment of this invention was explained in full detail, actually, it is not restricted to said embodiment, Even if there is a change of the range which does not deviate from the summary of this invention, it is included in this invention.

DESCRIPTION OF SYMBOLS 10 ... Operation support apparatus 11 ... Operation plan preparation part 12 ... Model correction part 121 ... Inboard electric power model correction part 122 ... Propulsion model correction part 123 ... Electric power generation model correction part 13 ... Equipment state management part 20 ... Energy utilization monitoring apparatus 21 ... Sensor group

Claims (9)

A means for predicting electricity demand using a passenger ship energy prediction model, meteorological and sea state prediction data, and a route plan, and presenting an optimal fuel consumption operation plan that is an optimal operation plan with fuel consumption efficiency;
Based on the fuel efficiency optimal operation plan, means for monitoring the energy of the cruise ship, the weather conditions, and the actual operation status;
Means for correcting a model for the fuel efficiency optimal operation plan based on a monitoring result,
The means for modifying the model is:
Using the accumulated data of similar routes in the same ship and the same season, set a correlation function with individual parameters by multivariate analysis, and correct the inboard power model by combining contributions for each parameter using the contribution coefficient Means,
A navigation support system comprising means for correcting a propulsion model of a ship indicating a relationship between propulsion speed and power consumption in the order of wind direction dependency and propulsion power. The operation support system according to claim 1,
Means for correcting the power generation model from the model based on the predicted value to the model based on the actual value using the relationship between the predicted value of the fuel consumption for each power generation output and the actual value;
The means for correcting the ship power model is:
Based on the correlation function for the individual parameters, using a least square method, a means for setting the difference between the predicted value of the inboard power and the actual value;
Means for determining the accuracy by the standard deviation of the difference between the predicted value and the actual value of the used power of the ship power;
An operation support system comprising: means for setting a correlation function of the numerical parameter with high accuracy, obtaining a correction function by combining the correlation function of the numerical parameter, and correcting and applying the inboard power model based on the correction function . The operation support system according to claim 1 or 2,
Means for correcting the propulsion model of the ship,
A graph that plots the relationship between the wind direction angle, the predicted value of the propulsion power, and the actual value, and approximates the Nth order equation to correct the wind direction dependency;
A means for setting a difference between a predicted value and an actual value of propulsion power using a least square method based on a correlation function for individual parameters including the cube of a ship speed;
Means for determining accuracy with a standard deviation of the difference between the predicted value and the actual value of the propulsion power;
An operation support system comprising: means for setting a correlation function of the number parameter with high accuracy, obtaining a correction function by combining the correlation function of the number parameter, and correcting and applying the propulsion power model based on the correction function . A navigation support method implemented by an electronic device,
Using the passenger ship's energy prediction model, meteorological and sea state prediction data, and the route plan, predicting electricity demand, and presenting the optimum fuel consumption operation plan, which is the operation plan with optimal fuel consumption efficiency,
Based on the fuel efficiency optimum operation plan, monitoring the energy of the passenger ship, the weather conditions, and the operation status,
Based on the monitoring results, when correcting the model for the fuel efficiency optimal operation plan,
Using the accumulated data of similar routes in the same ship and the same season, set a correlation function with individual parameters by multivariate analysis, and correct the inboard power model by combining contributions for each parameter using the contribution coefficient And
An operation support method including correcting a ship's propulsion model indicating the relationship between propulsion speed and power consumption in the order of wind direction dependency and propulsion power. The operation support method according to claim 4,
When correcting the power generation model from the model based on the predicted value to the model based on the actual value using the relationship between the predicted value of the fuel consumption for each power generation output and the actual value,
Based on the correlation function for the individual parameters, using a least square method, setting the difference between the predicted value of the inboard power and the actual value;
Determining the accuracy by the standard deviation of the difference between the predicted value and the actual value of power used in the ship,
The operation support method further includes: setting a correlation function of the high-precision number parameter, obtaining a correction function by combining the correlation function of the number parameter, correcting the ship power model based on the correction function, and applying the correction function. . The operation support method according to claim 4 or 5,
When correcting the propulsion model of the ship,
Graphing the relationship between the wind direction angle and the predicted value of propulsion power and the actual value, approximating the Nth order equation and correcting the wind direction dependency,
Based on the correlation function for individual parameters including the cube of the ship speed, using the least square method, setting the difference between the predicted value and the actual value of the propulsion power,
Determining accuracy by standard deviation of the difference between the predicted value and the actual value of the propulsion power;
The operation support method further includes: setting a correlation function of the numerical parameter with high accuracy, obtaining a correction function by combining the correlation function of the numerical parameter, correcting and applying the propulsion power model based on the correction function . Using the passenger ship's energy prediction model, meteorological and sea state prediction data, and route plan, predicting power demand, and presenting an optimal fuel consumption operation plan, which is an operation plan with optimal fuel consumption efficiency;
Monitoring the cruise ship's energy, weather conditions, and operational status based on the fuel efficiency optimal operation plan; and
Based on the monitoring results, when correcting the model for the fuel efficiency optimal operation plan,
Using the accumulated data of similar routes in the same ship and the same season, set a correlation function with individual parameters by multivariate analysis, and correct the inboard power model by combining contributions for each parameter using the contribution coefficient Steps,
A program for causing an electronic device to execute a step of correcting a ship's propulsion model indicating the relationship between propulsion speed and power consumption in the order of wind direction dependency and propulsion power. The program according to claim 7,
When correcting the power generation model from the model based on the predicted value to the model based on the actual value using the relationship between the predicted value of the fuel consumption for each power generation output and the actual value,
Based on the correlation function for the individual parameters, using a least square method, setting the difference between the predicted value of the inboard power and the actual value;
Determining accuracy with a standard deviation of a difference between a predicted value and an actual value of power used in the ship;
A step of setting a highly accurate correlation function of several parameters, obtaining a correction function by combining the correlation functions of the number parameters, correcting the ship power model based on the correction function, and applying the correction function to the electronic device is further executed. Program to let you. The program according to claim 7 or 8,
When correcting the propulsion model of the ship,
Graphing the relationship between the wind direction angle, the predicted value of the propulsion power, and the actual value, and correcting the wind direction dependency by approximating the Nth order equation;
Setting the difference between the predicted value and the actual value of the propulsion power using the least square method based on the correlation function for the individual parameter for causing the electronic device to execute the cube of the ship speed;
Determining accuracy with a standard deviation of the difference between the predicted value and the actual value of the propulsion power;
A step of setting a highly accurate correlation function of several parameters, obtaining a correction function by combining the correlation functions of the number parameters, correcting the propulsion power model based on the correction function, and further applying to the electronic device Program to let you.

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