CN107292451B - Ship speed optimization method and equipment - Google Patents
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Abstract
The method comprises the steps of preprocessing ship navigation original data according to performance data of a ship, and establishing a ship navigation database; dividing the ship navigation database based on encounter angles of the ship, and establishing a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database; the method comprises the steps of dividing a voyage of a ship into at least one voyage section based on weather prediction and voyage planning requirements of a passing area, and establishing a ship sectional voyage speed optimization model corresponding to each voyage section based on a ship oil consumption model corresponding to an encounter angle; based on the ship sectional navigational speed optimization model, the average navigational speed of the corresponding navigational section is obtained, the overall oil consumption is lowest on the premise of meeting the safety and the efficiency of the ship, the energy efficiency of the ship is improved, and the navigational cost is reduced.
Description
Technical Field
The application relates to the field of ship shipping, in particular to a ship speed optimization method and equipment.
Background
At present, compared with land transportation, marine transportation has the advantages of large transportation volume, mature development and low cost, and plays an important role in global economy. The world economy is in lack of strength due to the influence of the international financial crisis in 2008, meanwhile, the demand of maritime trade is greatly reduced compared with that before the financial crisis, and in addition, the global maritime transport capacity is seriously excessive, the transport cost is reduced to a surprising degree, so that the contradiction that the supply is larger than the demand in the shipping market is increasingly intensified, and the normal order of the global shipping industry is influenced to a certain extent. In the whole shipping process, compared with other operation costs of shipping enterprises, the fuel consumption exceeds 40% of the whole shipping cost, and if effective measures for improving efficiency and reducing emission cannot be actively taken, the benign development of the whole shipping industry is seriously influenced. Since the beginning of the century, the oil price continues to rise and shows a trend of rising as a whole, although the oil price has declined since 2011, the new energy still does not replace the dominant position of fuel in the aspect of motive power at present from the long-term development perspective, the domestic internal combustion engine consumes about 60% of the imported petroleum in China, the development cost of the internal combustion engine is also continuously increased, and the influence of factors such as the non-regenerability of the fuel, the instability of the middle east situation and the like cannot always keep the oil price low. The increase of oil price in future will certainly bring negative influence to whole shipping market, further increase the increase of shipping cost and the vicious competition between shipping enterprises.
Aiming at ships in operation, the purposes of energy conservation and emission reduction can be achieved through the speed optimization, and through systematically inducing and analyzing the research results of the speed optimization, the current research results are discovered that some only carry out theoretical analysis from the mathematical perspective, the model is complex, the solution is difficult, and some only stay in empirical reasoning, the influence of factors such as sea conditions and the like is rarely considered, so that the ship is difficult to apply to the actual operation of the ship.
Therefore, how to reduce shipping cost in the shipping process of the ship becomes a major research topic in the industry.
Disclosure of Invention
An object of the present application is to provide a method and an apparatus for optimizing the speed of a ship, so as to solve the problem of excessive cost caused by excessive oil consumption in the existing shipping process.
According to one aspect of the application, a method for optimizing the speed of a ship is provided, and the method comprises the following steps:
preprocessing the acquired ship navigation original data to obtain a ship navigation database;
dividing the ship navigation database based on encounter angles of the ship, and establishing a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database;
the method comprises the steps of dividing a voyage of a ship into at least one voyage section based on weather prediction and voyage planning requirements of a passing area, and establishing a ship sectional voyage speed optimization model corresponding to each voyage section;
and obtaining the average navigational speed of the corresponding navigational segment based on the ship segmented navigational speed optimization model.
Further, in the above method, the preprocessing the acquired ship navigation raw data to obtain a ship navigation database includes:
acquiring original ship navigation data;
and carrying out filtering processing, and/or synchronous processing, and/or normalization processing on the ship navigation original data to obtain a ship navigation database.
Further, in the above method, the dividing the ship navigation database based on the encounter angles of the ship, and establishing a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database includes:
dividing the ship navigation database based on encounter angles of the ship to obtain a ship navigation database corresponding to each encounter angle;
establishing a first relation model between the ground speed and the opposite water speed corresponding to each encounter angle based on wind power and wave height during sailing, and statistically analyzing a second relation model between the oil consumption of a ship main engine and the opposite water speed and the displacement;
and solving the corresponding first relation model and the second relation model according to the ship navigation database corresponding to each encounter angle, and combining the oil consumption of the ship auxiliary engine to obtain the ship oil consumption model corresponding to each encounter angle.
Further, in the method, the first relation model and the second relation model corresponding to each encounter angle are solved according to the ship navigation database corresponding to each encounter angle, and the ship oil consumption model corresponding to each encounter angle is obtained by combining the oil consumption of the ship auxiliary engine, and the method includes the following steps:
and solving the first relation model and the second relation model according to a nonlinear least square algorithm and a ship navigation database, and combining the oil consumption of a ship auxiliary engine to obtain a ship oil consumption model corresponding to each encounter angle.
Further, in the above method, the first relationship model is:
where v is the speed of the navigation to the ground, vsFor the speed of sailing in water, B is wind power, W is wave height, j is the number of encountered angle, pj、ej、qj、fjIs a first relational model parameter;
the second relationship model is:
g(v,Δ)＝a·vs b·Δc+
wherein g is the oil consumption of the ship main engine, vsThe water speed is the sailing speed, delta is the displacement, and a, b and c are parameters of a second relation model;
the method for solving the corresponding first relation model and the second relation model according to the ship navigation database corresponding to each encounter angle and obtaining the ship oil consumption model corresponding to each encounter angle by combining the oil consumption of the ship auxiliary engine comprises the following steps:
solving the corresponding first relational model according to the ship navigation database corresponding to each encounter angle to obtain first relational model parameters and second relational model parameters; and establishing a ship oil consumption model by combining the parameters of the second relation model and the corresponding second relation model and the oil consumption of the ship auxiliary engine.
Further, in the above method, the ship fuel consumption model is:
G(vs,Δ,C)＝a·vs b·Δc++C
wherein G is the oil consumption of the ship in one day of the ship navigation, vsAnd the water speed is shown as the water displacement, delta is the displacement, a, b and C are parameters of a second relation model, and C is the oil consumption of the marine auxiliary engine.
Further, in the above method, the step of dividing the voyage of the ship into at least one voyage segment based on the weather prediction and voyage planning demand of the passing area, and the step of establishing a ship segment voyage speed optimization model corresponding to each voyage segment based on the ship oil consumption model corresponding to the encounter angle includes:
the method comprises the steps of dividing a voyage of a ship into n sections based on weather prediction and voyage planning requirements of a passing area, wherein n is a positive integer;
optimizing the navigational speed of each navigational segment based on a ship oil consumption model to obtain a ship segmented navigational speed optimization model corresponding to each navigational segment;
the ship sectional navigational speed optimization model is as follows:
wherein the content of the first and second substances,
for a voyage total fuel consumption objective function to be solved, diIs the corresponding voyage of the ith voyage,
the corresponding opposite water speed of the ith flight segment, B wind power, W wave height and pj、ej、qj、fjIs a first relational model parameter, j is an encounter angle number, vminIs the minimum speed, vmaxAt maximum speed, tiPredicted time of flight, t, at i-th flight segmentiminIs the minimum flight time, t, of the ith flight segmentimaxIs the maximum voyage time of the ith voyage, T is the total voyage time required by the voyage plan, if there is a midway port in the voyage plan requirement, delta TiFor the dwell time, if there is a switch in the magnitude of the inter-leg speed, Δ ti＝0。
Further, in the above method, the obtaining an average speed of the corresponding leg based on the ship-leg-speed optimization model includes:
converting the ship sectional navigational speed optimization model by adopting an external penalty function method to obtain a converted ship sectional navigational speed optimization model corresponding to the navigational section;
and solving the converted ship subsection navigational speed optimization model of the navigational section by adopting a preset improved particle swarm algorithm to obtain the corresponding average navigational speed of the navigational section.
Further, in the above method, the converted ship segment navigational speed optimization model of the segment is:
wherein k is the number of iterations,
r (k) is a total fuel consumption objective function of a voyage converted by using an external penalty function method, different penalty value weights are taken according to the iteration number k,
in order to be a penalty function,
is a penalty term for the constraint of the equation,
a penalty term that is an inequality constraint.
Further, in the above method, the raw data of the ship navigation includes:
the performance data of the ship and the navigation history log of the ship.
According to another aspect of the present application, there is also provided an apparatus for optimizing the speed of a ship, wherein the apparatus comprises:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method as described above.
Compared with the prior art, the ship navigation database is obtained by preprocessing the acquired ship navigation original data; dividing the ship navigation database based on encounter angles of the ship, and establishing a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database; dividing the voyage of a ship into at least one voyage section based on the predicted weather and voyage planning requirements of a passing area, and establishing a ship sectional voyage speed optimization model corresponding to each voyage section based on a ship oil consumption model corresponding to the encounter angle; and obtaining the average navigational speed of the corresponding navigational section based on the ship sectional navigational speed optimization model, establishing the ship sectional navigational speed optimization model corresponding to each navigational section in the navigational route under the condition of meeting the requirement of the navigational time plan, further obtaining the average navigational speed of each navigational section in the navigational route corresponding to each encountered angle, realizing the lowest oil consumption in the whole navigational route process and reducing the cost in the navigational route.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 illustrates a flow diagram of a method for optimizing the speed of a vessel according to one aspect of the present application;
FIG. 2 illustrates a schematic view of a division of a vessel encounter angle in a method of optimizing a vessel's speed according to an aspect of the present disclosure;
FIG. 3 illustrates a schematic view of segment division in a method for optimizing the speed of a vessel according to an aspect of the subject application;
FIG. 4 illustrates a flow chart for solving an optimization model using an improved particle swarm algorithm in a ship speed optimization method according to an aspect of the present application;
FIG. 5 illustrates a block diagram of components of a method for calculating an optimized ship speed using a ship segment speed optimization model according to one aspect of the present application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present application is described in further detail below with reference to the attached figures.
In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party each include one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
FIG. 1 illustrates a flow diagram of a method for optimizing the speed of a vessel according to one aspect of the present application; the method is applied to a background server for controlling the navigational speed in the navigation process of a ship, and comprises the following steps of S11, S12, S13 and S14:
step S11, preprocessing the acquired original ship navigation data to obtain a ship navigation database; the step S12, dividing the ship navigation database based on the encounter angles of the ship, and establishing a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database; step S13, based on the weather and voyage planning demand of the passing area prediction, dividing the voyage of the ship into at least one voyage section, and based on the ship oil consumption model corresponding to the encounter angle, establishing a ship sectional voyage speed optimization model corresponding to each voyage section; in the step S14, based on the ship segment navigational speed optimization model, the corresponding average navigational speed of the navigational segment is obtained, so that the ship segment navigational speed optimization model corresponding to each navigational segment in the navigational route is established under the condition that the navigational time planning requirement is met, and further, the average navigational speed of each navigational segment in the navigational route corresponding to each encountered angle is obtained, so that the oil consumption in the whole navigational route is minimized, and the cost in the navigational route is reduced.
Here, before the step S11 preprocesses the acquired raw data of the vessel navigation, the method further includes collecting the raw data of the vessel navigation. The method comprises the steps of obtaining ship self performance data and a ship navigation historical log by referring to ship data, wherein the ship self performance data can comprise ship type, ship length, ship width, ship depth, draught, total tonnage, dead ton, design navigational speed, total host power and host speed. According to different performance data of the ship, obtaining different ship oil consumption model parameters of the corresponding ship, so that the corresponding ship oil consumption model parameters are determined according to the performance data of the ship in the subsequent sailing optimization process; through the ship navigation historical log, historical record data of ship navigation, energy consumption and oceanographic weather can be obtained, including starting port, destination port, first draught, tail draught, displacement, initial stability height, speed to the ground, speed to the water, voyage time, voyage, main engine oil consumption, auxiliary engine oil consumption, wind direction, wind power, wind wave height and wave direction, so that the actual ship navigation, energy consumption and oceanographic weather historical record data are utilized for statistical analysis, and the precision and effectiveness of a ship model can be improved.
Further, the step S11 is to pre-process the acquired ship navigation raw data to obtain a ship navigation database, including: acquiring original ship navigation data; and carrying out filtering processing, and/or synchronous processing, and/or normalization processing on the ship navigation original data to obtain a ship navigation database.
For example, according to the performance data of the ship, preprocessing is performed on the collected ship navigation raw data, and specifically includes preprocessing in several aspects: filtering some seriously damaged or long-time unchanged data in the collected ship navigation original data to reduce the accuracy influence on the establishment of a subsequent prediction model; secondly, synchronously processing data with different sequence lengths in the collected ship navigation original data; and thirdly, normalizing the integrated multivariate data in the collected ship navigation original data, and establishing an effective ship navigation database through the three aspects. In the process of analyzing problems by using ship navigation original data, the precision of parameters of a subsequent prediction model is seriously influenced by the seriously damaged and long-time unchanged data and unequal data in sequence length, the prediction error is increased, and the prediction error is reduced after the data are trimmed and synchronized for normalization.
Further, the step S12 is to divide the ship navigation database based on the encounter angles of the ship, and establish a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database, including:
dividing the ship navigation database based on encounter angles of the ship to obtain a ship navigation database corresponding to each encounter angle; the loss of navigational speed is different because the ship has different influence degrees caused by sea conditions under different encounter angles. Therefore, the established ship navigation database is used for dividing the ship navigation database according to different encounter angles in ship navigation, and the ship navigation database is divided into 5 parts, wherein the dividing method is shown as fig. 2, wherein j in fig. 2 represents encounter angle numbers, so as to establish a first relation model between the speed of the ship relative to the ground and the speed of the ship relative to the water, which corresponds to each encounter angle.
Establishing a first relation model between the ground speed and the opposite water speed corresponding to each encounter angle based on wind power and wave height during sailing, and statistically analyzing a second relation model between the oil consumption of a ship main engine and the opposite water speed and the displacement; establishing a first relation model between the speed of the ship to the ground and the speed of the ship to the water under the influence of wind power and wave height in a ship navigation database corresponding to each encounter angle:
where v is the speed of the navigation to the ground, vsFor the speed of sailing in water, B is wind power, W is wave height, and j is the encountering angleNumber pj、ej、qj、fjIs a first relational model parameter;
secondly, considering the influence of the water navigational speed and the displacement on the oil consumption of the main engine, establishing a second relation model between the oil consumption of the main engine of the ship and the navigational speed and the displacement:
g(v,Δ)＝a·vs b·Δc+，
wherein g is the oil consumption of the ship main engine, vsThe water speed is the sailing speed, delta is the displacement, and a, b and c are parameters of a second relation model;
and then, solving the corresponding first relation model according to the ship navigation database corresponding to each encounter angle to obtain a relation model between the water navigation speed and the ground navigation speed corresponding to each encounter angle, solving the second relation model according to the ship navigation database, and combining the oil consumption of the auxiliary engine of the ship to obtain the oil consumption model of the ship corresponding to each encounter angle.
In the step S12, the first relation model and the second relation model corresponding to each encounter angle are solved according to the ship navigation database corresponding to each encounter angle, and the ship oil consumption model corresponding to each encounter angle is obtained by combining the oil consumption of the ship auxiliary engine, which includes:
and solving the second relation model according to a nonlinear least square algorithm and a ship navigation database to obtain a ship main engine oil consumption model. Here, the non-linear least square algorithm may include Levenberg-Marquardt algorithm (Levenberg-Marquardt algorithm) and the like, and in a preferred embodiment of the present application, the non-linear least square algorithm is preferably Levenberg-Marquardt algorithm, and the second relation model is fitted and solved according to the Levenberg-Marquardt algorithm and the ship navigation database to obtain the ship main engine oil consumption model, wherein the Levenberg-Marquardt algorithm is a non-linear least square optimization algorithm, and has the advantages of both newton method and gradient method, which essentially divides the original problem into a plurality of least square problems in an iterative process. And then combining the oil consumption of the ship auxiliary engine according to the first relation model and the second relation model to obtain a ship oil consumption model corresponding to each encounter angle.
Further, the step of solving the corresponding first relational model and the second relational model according to the ship navigation database corresponding to each encounter angle, and obtaining the ship oil consumption model corresponding to each encounter angle by combining the oil consumption of the ship auxiliary engine includes:
solving the corresponding first relational model according to the ship navigation database corresponding to each encounter angle to obtain first relational model parameters and second relational model parameters; and establishing a ship oil consumption model corresponding to each encounter angle by combining the ship auxiliary engine oil consumption according to the first relation model parameters and the corresponding first relation model thereof and the second relation model parameters and the corresponding second relation model thereof which are obtained by solving. Obtaining a first relation model parameter between the corresponding water speed and the corresponding ground speed of each encounter angle; and solving the second relational model according to the ship navigation database to obtain parameters of the second relational model, and establishing a ship oil consumption model corresponding to each encounter angle by combining the oil consumption of a ship auxiliary engine. Fitting and solving the first relational model and the second relational model according to the Levenberg-Marquardt algorithm and a ship navigation database to respectively obtain a first relational model parameter pj、ej、qj、fjAnd the second relational model parameters a, b, c; and then, according to the first relation model parameters obtained by solving and the corresponding first relation model, establishing a first relation model between the water speed and the ground speed corresponding to each encounter angle, and according to the second relation model parameters and the corresponding second relation model, establishing a ship oil consumption model by combining the oil consumption of the ship auxiliary engine. .
Then, in the embodiment of the application, the influence of the ground speed, the water speed, the displacement, the wind power and the wave height on the oil consumption of the ship main engine is comprehensively considered, the oil consumption of the ship auxiliary engine is combined, the ship oil consumption model G corresponding to each encounter angle is established, and parameters in the model are solved by using a Levenberg-Marquardt algorithm. Wherein, the ship oil consumption model is as follows:
G(vs,Δ,C)＝a·vs b·Δc++C
wherein G is the oil consumption of the ship in one day of the ship navigation, vsAnd the water speed is shown as the water displacement, delta is the displacement, a, b and C are parameters of a second relation model, and C is the oil consumption of the marine auxiliary engine. And obtaining an improved and optimized ship oil consumption model according to the second relation model and the oil consumption of the ship auxiliary engine.
In the embodiment of the present application, in step S12, the database is divided into 5 parts as shown in fig. 2 according to the difference of encounter angles during the ship navigation, a first relationship model between the speed of going to the ground and the speed of going to the water under the influence of wind and waves in the ship navigation database corresponding to each encounter angle is statistically analyzed, a second relationship model between the oil consumption of the ship host and the oil consumption of going to the ground and the water displacement in the ship navigation data is statistically analyzed, and a corresponding oil consumption ship model is established in combination with the ship auxiliary engine, so that the actual navigation can be conveniently used, the accuracy of the predicted ship oil consumption is improved, and deep navigation optimization is facilitated.
At present, when most ships make a navigation plan, a navigation frequency plan is generally made according to the navigation distance between ports and the arrival time, and in the making process, a captain always designs a rich planned navigation speed in order to ensure the punctual arrival and avoid the influence of weather in the navigation, so that the ships can arrive at the ports in advance by one day or more in most cases, and in addition, in the navigation process, the ships can always keep constant navigation speed no matter whether the weather is good or bad. For the navigation mode, although the punctual arrival at the port can be guaranteed to complete the navigation planning, the average speed is high, so that the oil consumption is high, in addition, the constant average speed is still used in the environment with poor weather, the loss of the speed caused by weather is large, and the power of a host is relatively large under the same speed condition, so that the total oil consumption is greatly improved.
In fact, a reasonable voyage planning requirement would be to try to reduce the average speed while ensuring a punctual arrival, and also to reduce the speed in poor weather conditions while maintaining a relatively high speed in good weather conditions. In view of the above reasons, the step S13 is to divide the voyage of the ship into at least one voyage segment based on the weather and voyage planning demand predicted by the passing area, and establish a ship segment voyage speed optimization model corresponding to each voyage segment based on the ship oil consumption model corresponding to the encounter angle, and includes:
the method comprises the steps of dividing a voyage of a ship into n sections based on weather prediction and voyage planning requirements of a passing area, wherein n is a positive integer; here, the ship needs to go through different weather and sea state areas from the origin port to the destination port, and the whole voyage of the ship is divided into n different voyage segments according to the difference of weather and sea state predicted by the passing areas and the voyage planning requirement, as shown in fig. 3.
Next, the step S13 optimizes the navigational speed of each navigational segment based on the ship oil consumption model corresponding to the encounter angle, to obtain a ship segment navigational speed optimization model corresponding to each navigational segment; the ship sectional navigational speed optimization model is as follows:
wherein the content of the first and second substances,
for a voyage total fuel consumption objective function to be solved, diIs the corresponding voyage of the ith voyage,
the corresponding opposite water speed of the ith flight segment, B wind power, W wave height and pj、ej、qj、fjIs a first relational model parameter, j is an encounter angle number, vminIs the minimum speed, vmaxAt maximum speed, tiPredicted time of flight, t, at i-th flight segmentiminIs the minimum flight time, t, of the ith flight segmentimaxIs the maximum voyage time of the ith voyage, T is the total voyage time required by the voyage plan, if there is a midway port in the voyage plan requirement, delta TiFor the dwell time, if there is a switch in the magnitude of the inter-leg speed, Δ ti＝0。
In order to consider the influence of factors such as the range of the navigational speed, the navigation time of each navigational segment, the navigation time of the navigational times, the midway parking time and the like, a global optimization model is established to calculate the average navigational speed of the ship in each navigational segment, so that the overall oil consumption in the navigation process is the lowest on the premise of meeting the safety and the efficiency of the ship. The step S14 is to obtain the average speed of the corresponding voyage segment based on the ship segment voyage speed optimization model, and includes:
converting the ship sectional navigational speed optimization model by adopting an external penalty function method to obtain a converted ship sectional navigational speed optimization model corresponding to the navigational section; the constrained optimization problem of the ship segmented navigational speed optimization model is converted into an unconstrained optimization problem through an external penalty function method, and the optimized model is solved by using an improved particle swarm algorithm, so that the solution is simple, the related parameters are few, and the precision is high.
And solving the converted ship subsection navigational speed optimization model of the navigational section by adopting a preset improved particle swarm algorithm to obtain the corresponding average navigational speed of the navigational section. And converting the constraint problem into an unconstrained problem by using an external function method to solve, and solving the converted optimization model by using an improved particle swarm optimization.
Further, after the ship subsection navigational speed optimization model of each navigation segment is converted by adopting an external penalty function method, the obtained converted ship subsection navigational speed optimization model of each navigation segment is as follows:
wherein k is the number of iterations,
r (k) is a total fuel consumption objective function of a voyage converted by using an external penalty function method, different penalty value weights are taken according to the iteration number k,
in order to be a penalty function,
is a penalty term for the constraint of the equation,
a penalty term that is an inequality constraint. And solving the converted ship sectional navigational speed optimization model by using a preset improved particle swarm algorithm. After the flight segment is divided into N segments, the optimization solution in the N-dimensional space can be assumed, the number of particles is set to be m, and the positions of the particles are regarded as a ship target speed sequence, namely when the kth time is updated, the positions of the particles are as follows:
the particle motion speed is:
n is less than or equal to N, and the individual optimal position is as follows:
the global optimal positions are:
and solving the ship segmented navigational speed optimization model of each segment by utilizing a solving method flow chart shown in FIG. 4. Wherein, wmin、wmaxRespectively the maximum and minimum of the inertial weight w,
are respectively a learning factor c1And c2The initial values of (a) are typically set to 2.5 and 0.5,
are respectively a learning factor c1And c2The stop values of (A) are also typically set to 0.5 and 2.5, respectively, kmaxIs a preset maximum number of iterations.
Next, in the above embodiment of the present application, C, D, E, F4 each select a voyage number for each ship with different tonnage to predict the average speed of each voyage. The predicted values of the speed and the fuel consumption of the optimized ship sectional speed optimization model are compared with the actual sailing value and the simulated values under the traditional typical constant-speed (the speed to the ground is kept constant) sailing model, in addition, in order to ensure the consistency of meteorological conditions under 3 modes, when the sailing times for evaluation are selected, the sailing times under the conditions that the meteorological prediction data are basically the same as or similar to the actual meteorological conditions are selected, and the evaluation result is shown in the following table 1.
TABLE 1 comparison of evaluation data
As can be seen from the table 1, through the optimization of the sectional navigational speed, fuel oil is saved by about 4% on average compared with the traditional constant-speed navigational mode, in addition, compared with the fuel consumption in the actual navigation process, the prediction error can be controlled within 2% generally, and the average absolute error of the navigational speed predicted by each navigational section is lower than 0.5 kn. The analysis fully shows that the ship navigation speed optimization method provided by the application can provide a better navigation strategy for ship navigation and reduce the navigation energy consumption.
In summary, the invention provides a composition block diagram of an energy-saving and emission-reducing ship speed optimization method as shown in fig. 5, which comprehensively considers the influence of the ground speed, the water speed, the displacement, the wind power, the wave height and the encounter angle on the ship navigation, statistically analyzes a second relation model of the oil consumption of the main engine, the water speed and the displacement of the main engine and a first relation model between the ground speed and the water speed under the influence of wind waves by using historical record data of the ship, and establishes an improved ship oil consumption model by combining with an auxiliary engine of the ship; based on the ship oil consumption model, the air route is divided according to the marine meteorological forecast data and the voyage number plan requirement, an energy-saving and emission-reducing ship segmented voyage speed optimization model is provided, and finally, the optimized voyage speed can be obtained by using an improved particle algorithm, so that the oil consumption of the whole voyage number is the lowest under the condition of meeting the voyage number requirement.
In addition, this application embodiment still provides a boats and ships speed of a ship optimization's equipment, and wherein, this equipment includes:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the foregoing method.
For example, the computer readable instructions, when executed, cause the one or more processors to: preprocessing the acquired ship navigation original data to obtain a ship navigation database; dividing the ship navigation database based on encounter angles of the ship, and establishing a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database; dividing the voyage of the ship into at least one voyage section based on the weather prediction and voyage planning requirements of the passing area, and establishing a ship subsection voyage speed optimization model corresponding to each voyage section based on a first relation model of the water-to-water voyage speed and the ground-to-ground voyage speed and a ship oil consumption model corresponding to each encounter angle; and obtaining the average navigational speed of the corresponding navigational section based on the ship sectional navigational speed optimization model, establishing the ship sectional navigational speed optimization model corresponding to each navigational section in the navigational route under the condition of meeting the requirement of the navigational time plan, further obtaining the average navigational speed of each navigational section in the navigational route corresponding to each encountered angle, realizing the lowest oil consumption in the whole navigational route process and reducing the cost in the navigational route.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, some of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to the aforementioned embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (9)
1. A method for optimizing the speed of a ship, wherein the method comprises:
preprocessing the acquired ship navigation original data to obtain a ship navigation database;
dividing the ship navigation database based on encounter angles of the ship, and establishing a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database;
dividing the voyage of a ship into at least one voyage section based on the predicted weather and voyage planning requirements of a passing area, and establishing a ship sectional voyage speed optimization model corresponding to each voyage section based on a ship oil consumption model corresponding to the encounter angle;
obtaining the average navigational speed of the corresponding navigational segment based on the ship segmented navigational speed optimization model;
the method comprises the following steps of dividing the ship navigation database based on encounter angles of ships, and establishing a ship oil consumption model corresponding to each encounter angle based on the divided ship navigation database, wherein the method comprises the following steps:
dividing the ship navigation database based on encounter angles of the ship to obtain a ship navigation database corresponding to each encounter angle;
establishing a first relation model between the ground speed and the opposite water speed corresponding to each encounter angle based on wind power and wave height during sailing, and statistically analyzing a second relation model between the oil consumption of a ship main engine and the opposite water speed and the displacement;
solving the corresponding first relation model and the second relation model according to the ship navigation database corresponding to each encounter angle, and obtaining a ship oil consumption model corresponding to each encounter angle by combining oil consumption of a ship auxiliary engine;
the method for solving the corresponding first relation model and the second relation model according to the ship navigation database corresponding to each encounter angle and obtaining the ship oil consumption model corresponding to each encounter angle by combining the oil consumption of the ship auxiliary engine comprises the following steps:
and solving the first relation model and the second relation model according to a nonlinear least square algorithm and a ship navigation database, and combining the oil consumption of a ship auxiliary engine to obtain a ship oil consumption model corresponding to each encounter angle.
2. The method of claim 1, wherein the preprocessing the acquired raw ship navigation data to obtain a ship navigation database comprises:
acquiring original ship navigation data;
and carrying out filtering processing, and/or synchronous processing, and/or normalization processing on the ship navigation original data to obtain a ship navigation database.
3. The method of claim 1, wherein the first relationship model is:
where v is the speed of the navigation to the ground, vsFor the speed of sailing in water, B is wind power, W is wave height, j is the number of encountered angle, pj、ej、qj、fjIs a first relational model parameter;
the second relationship model is:
g(v,Δ)＝a·vs b·Δc+
wherein g is the oil consumption of the ship main engine, vsThe water speed is the sailing speed, delta is the displacement, and a, b and c are parameters of a second relation model;
the method for solving the corresponding first relation model and the second relation model according to the ship navigation database corresponding to each encounter angle and obtaining the ship oil consumption model corresponding to each encounter angle by combining the oil consumption of the ship auxiliary engine comprises the following steps:
solving the corresponding first relational model according to the ship navigation database corresponding to each encounter angle to obtain first relational model parameters and second relational model parameters; and establishing a ship oil consumption model corresponding to each encounter angle by combining the ship auxiliary engine oil consumption according to the first relation model parameters and the corresponding first relation model thereof and the second relation model parameters and the corresponding second relation model thereof which are obtained by solving.
4. The method of claim 3, wherein the ship fuel consumption model is:
G(vs,Δ,C)＝a·vs b·Δc++C
wherein G is the oil consumption of the ship in one day of the ship navigation, vsAnd the water speed is shown as the water displacement, delta is the displacement, a, b and C are parameters of a second relation model, and C is the oil consumption of the marine auxiliary engine.
5. The method of claim 4, wherein the step of dividing the voyage of the ship into at least one voyage segment based on the weather and voyage planning demand predicted by the passing area, and the step of establishing a ship segment voyage speed optimization model corresponding to each voyage segment based on the ship oil consumption model corresponding to the encounter angle comprises the following steps:
the method comprises the steps of dividing a voyage of a ship into n sections based on weather prediction and voyage planning requirements of a passing area, wherein n is a positive integer;
optimizing the navigational speed of each navigational section based on a ship oil consumption model corresponding to an encounter angle to obtain a ship sectional navigational speed optimization model corresponding to each navigational section;
the ship sectional navigational speed optimization model is as follows:
wherein the content of the first and second substances,
for a voyage total fuel consumption objective function to be solved, diIs the corresponding voyage of the ith voyage,
the corresponding opposite water speed of the ith flight segment, B wind power, W wave height and pj、ej、qj、fjIs a first relational model parameter, j is an encounter angle number, vminIs the minimum speed, vmaxAt maximum speed, tiPredicted time of flight, t, at i-th flight segmentiminIs the minimum flight time, t, of the ith flight segmentimaxIs the ith flight segmentA large voyage time, T being the total voyage time required for a voyage plan, Δ T if there is a mid-way port in the voyage plan requirementiFor the dwell time, if there is a switch in the magnitude of the inter-leg speed, Δ ti＝0。
6. The method of claim 5, wherein the deriving the average speed for the corresponding leg based on the vessel segment speed optimization model comprises:
converting the ship sectional navigational speed optimization model by adopting an external penalty function method to obtain a converted ship sectional navigational speed optimization model corresponding to the navigational section;
and solving the converted ship subsection navigational speed optimization model of the navigational section by adopting a preset improved particle swarm algorithm to obtain the corresponding average navigational speed of the navigational section.
7. The method of claim 6, wherein the converted vessel segment cruise optimization model for the leg is:
wherein k is the number of iterations,
r (k) is a total fuel consumption objective function of a voyage converted by using an external penalty function method, different penalty value weights are taken according to the iteration number k,
in order to be a penalty function,
being equality constraintsA penalty term is given to the system for the system,
a penalty term that is an inequality constraint.
8. The method of any one of claims 1 to 7, wherein the vessel voyage raw data comprises:
the performance data of the ship and the navigation history log of the ship.
9. An apparatus for optimizing the speed of a ship, wherein the apparatus comprises:
one or more processors; and a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method of any of claims 1 to 8.
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