Energy configuration and sailing operation optimization method, device and medium for transport ship

Abstract

The present application relates to the technical field of energy configuration and navigation operation optimization of hybrid energy storage ships, in particular to an energy configuration and navigation operation optimization method, device and medium for transport ships, which constructs dynamic constraints of effective navigation time and navigation speed according to the uncertainty of transport material reserves and loading time, and establishes comprehensive power constraints of propulsion power, generators, energy storage batteries and fuel cells in combination with a navigation dynamics model and an energy balance model. By uniformly modeling the device configuration power, battery capacity and operation power, a two-stage optimization model of planning cost and operation cost is constructed, and a column and constraint generation algorithm is adopted to realize robust optimization of capacity configuration and operation scheduling. The present application can dynamically match the navigation speed and energy system configuration under different reserve scenarios, and improve the operation efficiency of hybrid energy storage ships.

Description

Technical Field

[0001] This invention relates to the field of energy configuration and navigation operation optimization technology for hybrid energy storage ships, specifically to methods, equipment, and media for energy configuration and navigation operation optimization of transport ships. Background Technology

[0002] A ship departs from its origin, loading materials to be transported to its destination. Before departure, the ship needs to plan its speed based on the distance between the origin and destination to ensure it arrives on time within the stipulated sailing time. However, loading materials takes time, which is unknown before departure. Existing technology estimates this time and subtracts it from the stipulated sailing time to obtain the effective sailing time. Within this effective sailing time, the ship's power and configuration parameters are optimized to improve speed, ultimately ensuring the ship reaches its destination within the effective sailing time. However, since the estimated time does not represent the actual time, the power, configuration parameters, and speed may be overestimated or underestimated.

[0003] In summary, the existing technology's navigation power, configuration parameters, and navigation speed are difficult to match with the cargo to be transported.

[0004] Therefore, existing technologies still need to be improved and enhanced. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method, equipment, and medium for optimizing the energy configuration and navigation operation of transport vessels, which solves the problem that the existing technology's navigation power, configuration parameters, and navigation speed are difficult to match with the materials to be transported.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a method for energy configuration and navigation operation optimization of a transport vessel, comprising:

[0008] The total voyage distance to be traversed by the ship and the total voyage time set in advance are obtained. Based on the constraints of the ship's berthing time on the transported material, as well as the total voyage distance and the total voyage time, the constraints of the transported material on the sailing speed are constructed. The transported material affects the ship's berthing time to affect the sailing speed required for the ship to complete the total voyage distance within the total voyage time.

[0009] Based on the constraints on the sailing speed imposed by the transported material, constraints on propulsion power are constructed, and based on the constraints on propulsion power, constraints on sailing power are constructed. The constraints on sailing power are used to constrain the power of the equipment that provides power to the ship.

[0010] Based on the constraints on the speed of the transported material and the constraints on the power of the transport, the objective function is used as the optimization objective to optimize the speed of the transport, the power of the transport, and the configuration parameters of the equipment. The variables of the objective function are the speed of the transport, the power of the transport, and the configuration parameters.

[0011] In one implementation, the method for constructing the constraint on ship berthing time for the transported materials includes:

[0012] The preparation time required to load the transported material onto the ship is obtained, as is the loading rate of the transported material.

[0013] Based on the preparation time and the loading rate, a constraint is constructed on the ship's berthing time for the amount of the transported material, and this constraint is used as the constraint on the ship's berthing time for the transported material.

[0014] In one implementation, based on the constraints on the ship's berthing time imposed by the transported cargo, as well as the total voyage distance and the total sailing time, the constraints on the sailing speed imposed by the transported cargo are constructed, including:

[0015] Based on the total sailing time and the constraints on the ship's berthing time imposed by the transported materials, the constraints on the ship's effective sailing time imposed by the transported materials are constructed.

[0016] Based on the constraints of the transported material on the ship's effective sailing time and the total voyage, the constraints of the transported material on the sailing speed are constructed.

[0017] In one implementation, based on the constraint of the transported material on the sailing speed, a constraint condition for propulsion power is constructed, including:

[0018] A navigation dynamics model is applied to constrain the speed of the transported material to construct the propulsion power constraint.

[0019] In one implementation, constraints on the propulsion power are constructed based on the propulsion power constraints, including:

[0020] Obtain the load power, which is the power required by the load equipment on the ship;

[0021] An energy balance model is applied to the constraints of the load power and the propulsion power to obtain the constraints of the combined power of the battery and generator. The energy balance model is used to characterize the balance relationship between the load power, the propulsion power, and the combined power of the battery and generator, where the combined power of the battery and generator is the total power output by the battery and generator for the ship's navigation.

[0022] Based on the constraints of the generator's configured power and the combined power of the battery and generator, the constraints of the generator's motor power are obtained.

[0023] Based on the constraints of the battery's lifetime safe power, the battery's configured power, and the combined power of the battery and generator, the constraints of the battery power are obtained.

[0024] The constraints on motor power and battery power are used as constraints on navigation power.

[0025] In one implementation, the equipment providing power to the ship includes a generator, an energy storage battery, and a fuel cell, and the construction of the objective function includes:

[0026] The configuration parameters are determined, including the maximum power of the generator, the maximum power of the energy storage battery, and the maximum power of the fuel cell; the battery capacity is the capacity of the energy storage battery.

[0027] Using the configured power and the battery capacity as variables, construct a planning cost function;

[0028] Determine the motor power provided by the generator, the battery power provided by the energy storage battery, and the battery power provided by the fuel cell in the navigation power;

[0029] A navigation cost function is constructed using the motor power, the battery power provided by the energy storage battery, the battery power provided by the fuel cell, and the navigation speed as variables.

[0030] Based on the planning cost function and the navigation cost function, an objective function is constructed.

[0031] In one implementation, based on the constraints on the sailing speed and the sailing power imposed by the transported material, the sailing speed, the sailing power, and the equipment configuration parameters are optimized using an objective function as the optimization objective, including:

[0032] The power constraints of the generator and the battery in the navigation power constraints of the ship are determined. The power constraint of the generator is related to the configured power of the generator. The power constraint of the battery includes the power constraint of the energy storage battery and the power constraint of the fuel cell. The power constraint of the energy storage battery is related to the battery capacity and the configured power of the energy storage battery. The power constraint of the fuel cell is related to the configured power of the fuel cell.

[0033] Based on the power constraints of the generator, the energy storage battery, and the fuel cell, the value of the planning cost function is optimized by optimizing the configuration power values ​​of the generator, the energy storage battery, and the fuel cell, so as to minimize the planning cost function and obtain the optimization target values ​​of the battery capacity and the configuration power. The configuration power includes the configuration power of the generator, the energy storage battery, and the fuel cell.

[0034] Based on the optimized target values ​​of the generator's configured power, the energy storage battery's configured power, the fuel cell's configured power, the power constraints of the motor, the energy storage battery, and the fuel cell, and in conjunction with the constraints of the transported material on the sailing speed, the value of the sailing cost function is optimized by optimizing the transport volume of the transported material, so that the value of the sailing cost function is minimized.

[0035] Update the transport volume of the material to be transported, continue to iteratively optimize the navigation cost function, and determine the optimization target values ​​of the navigation speed, the motor power, the energy storage battery power, and the fuel cell power corresponding to the maximum transport volume of the material to be transported.

[0036] In one implementation, the substance to be transported is hydrogen produced by a hydrogen production platform at sea.

[0037] Secondly, embodiments of the present invention also provide a terminal device, wherein the terminal device includes a memory, a processor, and an energy configuration and navigation operation optimization program for a transport vessel stored in the memory and executable on the processor. When the processor executes the energy configuration and navigation operation optimization program for the transport vessel, it implements the steps of the energy configuration and navigation operation optimization method for the transport vessel described above.

[0038] Thirdly, embodiments of the present invention also provide a computer-readable storage medium storing an energy configuration and navigation operation optimization program for a transport vessel. When the energy configuration and navigation operation optimization program for a transport vessel is executed by a processor, it implements the steps of the above-described energy configuration and navigation operation optimization method for a transport vessel.

[0039] Beneficial effects: The cargo to be transported affects the ship's speed required to complete the total voyage within the specified total sailing time by influencing the ship's berthing time. Therefore, the cargo to be transported constitutes a constraint on the sailing speed. The ship's propulsion power is related to the sailing power, which in turn is related to the sailing power. The sailing power is related to the configuration parameters of the equipment that provides kinetic energy. Therefore, the sailing speed can be directly constrained by the cargo to be transported, and the sailing power and configuration parameters can be indirectly constrained. Under the above constraints, this invention optimizes the sailing speed, sailing power, and configuration parameters, so that the optimized sailing speed, sailing power, and configuration parameters match the cargo to be transported, thereby improving the ship's transportation efficiency. Attached Figure Description

[0040] Figure 1 This is an overall flowchart of the present invention;

[0041] Figure 2 This is a schematic diagram of hydrogen transportation by ship in an embodiment of the present invention;

[0042] Figure 3 This is a schematic diagram of iterative convergence in an embodiment of the present invention;

[0043] Figure 4 This is a block diagram illustrating the internal structure of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0044] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments and accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0045] Research has shown that when a ship departs from its origin, loading materials to be transported to its destination, it needs to plan its speed based on the distance between the origin and destination before departure to ensure timely arrival within the allotted time. However, loading materials takes time, which is unknown before departure. Existing technology estimates this time and subtracts it from the allotted time to obtain the effective travel time. Within this effective travel time, the ship's power and configuration parameters are optimized to improve speed, ultimately ensuring arrival at the destination within the allotted time. However, since the estimated time does not represent the actual travel time, the power, configuration parameters, and speed may be underestimated or overestimated.

[0046] To address the aforementioned technical problems, this invention provides a method, equipment, and medium for optimizing the energy configuration and navigation operation of transport vessels, which solves the problem that the navigation power, configuration parameters, and navigation speed of existing technologies are difficult to match with the materials to be transported.

[0047] The energy configuration and navigation operation optimization method for a transport vessel according to this embodiment can be applied to a terminal device, which can be a terminal product with data processing capabilities, such as a computer. In this embodiment, as... Figure 1 As shown, the energy configuration and navigation operation optimization method for the transport vessel specifically includes the following steps:

[0048] S100: Obtain the total voyage distance to be traversed by the ship and the total voyage time preset for the ship's voyage. Based on the constraints of the berthing time of the cargo to be transported, as well as the total voyage distance and the total voyage time, construct the constraints of the berthing speed of the cargo to be transported. The cargo to be transported affects the berthing time of the ship to affect the voyage speed required for the ship to complete the total voyage distance within the total voyage time.

[0049] S200, based on the constraint of the transported material on the sailing speed, construct the propulsion power constraint condition, and based on the propulsion power constraint condition, construct the sailing power constraint condition, the sailing power constraint condition is used to constrain the power of the equipment that provides power to the ship;

[0050] S300, based on the constraints on the sailing speed and the sailing power of the transported material, optimize the sailing speed, the sailing power, and the configuration parameters of the equipment with the objective function as the optimization objective. The variables of the objective function are the sailing speed, the sailing power, and the configuration parameters.

[0051] Step S100, based on the constraints of the transported material on the ship's berthing time, the total voyage, and the total sailing time, constructs the constraints of the transported material on the sailing speed, including: obtaining the preparation time required to load the transported material onto the ship, and obtaining the loading rate of the transported material; based on the preparation time and the loading rate, constructs the constraints of the transported material volume on the ship's berthing time, and uses the constraints of the transported material volume on the ship's berthing time as the constraints of the transported material on the ship's berthing time; based on the total sailing time and the constraints of the transported material on the ship's berthing time, constructs the constraints of the transported material on the ship's effective sailing time; and based on the constraints of the transported material on the ship's effective sailing time and the total voyage, constructs the constraints of the transported material on the sailing speed.

[0052] Formula (1) characterizes the constraint of the transport volume of the required material on the ship's berthing time:

[0053] (1)

[0054] In the formula, The representative ship in The docking time of each platform, The representative is the first The preparation time required for loading the materials to be transported onto the ship on each platform. Representing the The volume of goods to be transported on each platform. Representing the Loading rate of each platform.

[0055] Formula (2) represents the constraint on effective sailing time:

[0056] (2)

[0057] In the formula, Representative from the first Effective sailing time from one platform to the next. Represents the total prescribed sailing time. This represents the total number of platforms. A platform is a platform that produces and transports substances. For example, if the substance to be transported is hydrogen, then the platform is a hydrogen production platform at sea.

[0058] Based on the constraints of the transported substance on the ship's effective sailing time and the total voyage, the constraints of the transported substance on the sailing speed are constructed, that is, the constraints of the transported substance on the sailing speed are represented by formulas (3) and (4):

[0059] (3)

[0060] (4)

[0061] In the formula, Represents the total voyage. The representative ship in The speed of travel at any given moment Representing the The flight distance between the first platform and the next platform The sum of the initial and final distances represents the distance between the ship's origin and the first platform, and the distance between the last platform and the ship's destination, respectively. In this embodiment, the origin and destination are not the same place.

[0062] Transforming formula (4), we obtain the following about of The expression will Substituting the expression into formula (3) establishes the effective sailing time. Total voyage The relationship between them.

[0063] Based on formulas (1), (2), (3), and (4), we can derive... , , and The inequalities formed, and because and All of these are known quantities, therefore, we can construct the formula using formulas (1), (2), (3), and (4). and The inequalities formed can be derived from... (representing the first) The volume of transported materials on each platform (Representative ship in the) Constraints on the sailing speed at any given time (in this embodiment) and All are unknowns, meaning the optimization involves addressing the uncertainty of the quantity of the transported material. This is to enable the ship to complete the total voyage within the prescribed total sailing time.

[0064] Step S200, which involves constructing the propulsion power constraint based on the constraint of the transported material on the sailing speed, includes applying a sailing dynamics model to the constraint of the transported material on the sailing speed to construct the propulsion power constraint.

[0065] The navigation dynamics model is formula (5):

[0066] (5)

[0067] In the formula, The representative ship in The propulsion power at any given moment; propulsion power is used to move the ship forward. It represents the meaning of moving forward. Represents linear parameters. Represents the exponential parameter. and The size of each can be a specified value, where The value can be 3.

[0068] Since the above has already been established right Constraints, therefore right Substituting the constraints into formula (5) yields the following result. For propulsion power The constraint, that is, based on formula (5) right Constraints can be used to construct constraints on propulsion power.

[0069] The step S200, based on the propulsion power constraint, constructs the navigation power constraint, including the following specific steps S201, S202, S203, S204, and S205:

[0070] S201, Obtain the load power, which is the power required by the load equipment on the ship.

[0071] use This represents the load power of the load equipment at time t. Load power is the power consumed by the load equipment. Figure 2 The service load in the ship requires the power of generators and fuel cells. The service load includes other equipment on board, such as lighting equipment, that provides services to users.

[0072] S202, apply the energy balance model to the constraints of the load power and the propulsion power to obtain the constraints of the combined power of the battery and generator. The energy balance model is used to characterize the balance relationship between the load power, propulsion power, and combined power of the battery and generator. The combined power of the battery and generator is the total power output by the battery and generator for the ship's navigation.

[0073] The energy balance model is formula (6):

[0074] (6)

[0075] In the formula, Representing fuel cells in the Power at any moment Represents the generator's power. Representative energy storage battery in the first Discharge power at any given time Representative energy storage battery in the first The charging power at any given time; charging and discharging cannot occur simultaneously. Representing the combined power of the battery and generator, the above For propulsion power Substituting the constraints into formula (6), we obtain the result based on... of The constraints.

[0076] S203, based on the constraints of the generator's configured power and the combined power of the battery and generator, the constraints of the generator's motor power are obtained.

[0077] The configured power is the maximum output power of the generator. This represents the maximum output power of the generator.

[0078] motor power and The inequality established by formula (7) is satisfied:

[0079] (7)

[0080] The constraints implicitly impose on By combining the constraint with formula (7), the motor power is obtained. The constraints, due to The constraints are Established, therefore motor power The constraints also include right Due to constraints, subsequent decisions based on motor power... The optimized sailing speed, sailing power, and configuration parameters obtained under the constraints are all applicable to situations where the constraints are unclear. The situation.

[0081] S204, Based on the constraints of the battery's lifetime safe power, the battery's configured power, and the combined power of the battery and generator, the constraints of the battery power are obtained.

[0082] The range of safe power values ​​for the lifespan of the energy storage battery is determined using formulas (8) and (9):

[0083] (8)

[0084] (9)

[0085] In the formula, Representative energy storage battery in the first The battery state of charge value at time t. Representative energy storage battery in the first The state of charge of the battery at any given time. Represents battery capacity. This represents the minimum value of the battery's state of charge. Represents the maximum value of the battery's state of charge. This represents the charging efficiency of the energy storage battery. This represents the discharge efficiency of the energy storage battery.

[0086] The battery power in this embodiment includes the battery power of the energy storage battery and the battery power of the fuel cell.

[0087] The configured power of the energy storage battery is the maximum output power of the energy storage battery. This represents the maximum output power of the energy storage battery. Battery power includes the charging power of the energy storage battery. and discharge power , and The inequality established by formula (10) is satisfied. and The inequality established by formula (11) is satisfied.

[0088] (10)

[0089] (11)

[0090] In the formula, This represents a binary variable used to characterize the operating state of an energy storage battery, which includes charging and discharging states.

[0091] The constraints on the combined power output of the battery and generator have already been included. right and The constraints, together with formulas (8), (9), (10), and (11), constitute the constraints on the battery power of the energy storage battery. The battery power of the energy storage battery includes the charging power of the energy storage battery. and discharge power .

[0092] The power constraints of a fuel cell are related to its configured power, which is the maximum power of the fuel cell. The maximum power of the fuel cell is represented by formula (12), which establishes the constraint condition for the fuel cell power:

[0093] (12)

[0094] When the fuel cell is a hydrogen fuel cell, the hydrogen consumption of the hydrogen fuel cell is... The relationship is shown in formula (13):

[0095] (13)

[0096] In the formula, It refers to the efficiency of hydrogen fuel cells. It is the low calorific value of hydrogen. This represents the amount of hydrogen consumed. The hydrogen used in hydrogen fuel cells is hydrogen carried by the ship itself, not hydrogen collected from a hydrogen production platform.

[0097] S205, the constraints on the motor power and the battery power are used as constraints on the navigation power.

[0098] In other words, the navigation power constraint consists of constraints on motor power and constraints on battery power.

[0099] In this embodiment, the equipment that provides power to the ship includes a generator, an energy storage battery, and a fuel cell. The generator, the hydrogen fuel cell system, and the battery energy storage system are connected to the DC bus through a power electronic converter to form a unified power generation system that powers the ship's propulsion load and service load. The electrical energy generated by the fuel cell and the diesel generator can prioritize meeting the real-time load demand, and the remaining electrical energy can charge the battery. The battery, as a buffer unit, can be charged and discharged to suppress power fluctuations.

[0100] Based on the objective function in step S300 of the construction of the generator, energy storage battery, and fuel cell, the construction method includes the following specific steps S301, S302, S303, S304, and S305:

[0101] S301, determine the configuration power and battery capacity in the configuration parameters, wherein the configuration power includes the maximum power of the generator, the maximum power of the energy storage battery, and the maximum power of the fuel cell, and the battery capacity is the capacity of the energy storage battery.

[0102] S302, using the configured power and the battery capacity as variables, construct a planning cost function. :

[0103] (14)

[0104] Using matrices Characterization , , and ,Right now , Represents the transpose of a matrix. The feasible domain is The feasible region is used to characterize The range of values, The range of values, The range of values, The range of values ​​for is as follows, in this embodiment , , and The values ​​are all unknowns and need to be determined before voyage. Go to configuration , , and These four values, so that Minimize the value of . , , and Represent , , and The unit capacity cost coefficient. Battery capacity is... Configuration power includes , and .

[0105] S303, determine the motor power provided by the generator, the battery power provided by the energy storage battery, and the battery power provided by the fuel cell in the navigation power.

[0106] In other words, generators, energy storage batteries, and fuel cells are all power sources for ship navigation. Therefore, the power of the motor and the power of the two types of batteries are the navigation power used by the ship to move forward.

[0107] S304, with the motor power The battery power provided by the energy storage battery and the battery power provided by the fuel cell and the speed of travel Use variables to construct a navigation cost function.

[0108] Because the battery power provided by energy storage batteries includes Therefore, the sailing cost function :

[0109] (15)

[0110] In the formula, Represents the number of days the system is running. This represents the unit fuel cost coefficient. Represents the generator operating cost coefficient. This represents the generator operation and maintenance cost coefficient. This represents the coefficient of fuel cell operation and maintenance costs. Representing the operating and maintenance cost coefficient of energy storage batteries, using a matrix Characterizing the runtime variable, i.e. , The feasible domain is The feasible region is based on and Established Constraints Constraints Constraints Constraints and Constraints, Constraints Constraints Constraints and The constraints are those obtained from the above solution. The constraints are not only related to Related, The following constraints also need to be satisfied: ,in Represents the minimum permissible speed for a ship's navigation. This represents the maximum permissible speed for a ship's navigation.

[0111] This represents the volume of goods to be transported across all platforms. , This represents the set of all possible values ​​for the amount of material to be transported on each platform, i.e. , Representing the The minimum storage capacity of the materials to be transported as permitted by the platform. Representing the The maximum storage capacity of the materials to be transported allowed by the platform.

[0112] In the formula, Represents effective sailing time With berthing time The sum of .

[0113] because and Therefore, formula (15) implicitly contains the sailing speed. .

[0114] S305, Based on the planning cost function and the navigation cost function, construct the objective function: .

[0115] Solve for the expression that satisfies formula (16) Optimization target value and Optimization target value:

[0116] (16)

[0117] The steps for solving the optimization target value in formula (16) include: based on the power constraints of the generator, the energy storage battery, and the fuel cell, optimizing the configuration power value of the generator, the energy storage battery, and the fuel cell to optimize the value of the planning cost function, so as to minimize the planning cost function, thereby obtaining the optimization target value of the battery capacity and the optimization target value of the configuration power. The configuration power includes the configuration power of the generator, the configuration power of the energy storage battery, and the configuration power of the fuel cell; based on the optimization target value of the configuration power of the generator and the configuration power of the energy storage battery... The optimization target values ​​for the target values ​​of the fuel cell configuration power, the power constraints of the motor, the power constraints of the energy storage battery, and the power constraints of the fuel cell are combined with the constraint of the transported substance on the sailing speed. The value of the sailing cost function is optimized by optimizing the transport volume of the transported substance to minimize the value of the sailing cost function. The transport volume of the transported substance is updated, and the sailing cost function is iteratively optimized to determine the optimization target values ​​for the sailing speed, the motor power, the energy storage battery power, and the fuel cell power corresponding to the maximum transport volume of the transported substance.

[0118] The meaning of formula (16): First, calculate the formula that makes Get the minimum value , , and The optimization objective values ​​are determined based on these four optimization objective values. Constraints Constraints Constraints Constraints and The constraints, in Constraints Constraints Constraints Constraints and Within the constraint range formed by the constraints, determine The corresponding value for each possible value Given several values, select the smallest value from them. Each of the possible values ​​corresponds to Filter the largest value from the minimum value Corresponding The minimum value will be the maximum value. Corresponding The minimum value is used as The target value, The target value corresponding to The value is The optimization target value, The target value corresponding to The value is The optimization target value.

[0119] In another embodiment, this embodiment is based on the column and constraint generation algorithm to iteratively solve formula (16), and the solution steps include:

[0120] First, rewrite formula (16) as formula (17):

[0121] (17)

[0122] Solve equation (17) under the constraints of equation (18):

[0123] (18)

[0124] In the formula, , , , , , , , , for , , The matrix formed by the constraints of these three factors Representatives include only The set of inequality constraints; Representatives include only The set of equality constraints; represent and The corresponding set of inequality constraints; Representative includes and The corresponding set of equality constraints; This represents a set of equality constraints that include uncertain variables.

[0125] Where the matrix sum matrix as follows:

[0126] , .

[0127] The second step is to set the iteration counter. The upper limit of the amount of material to be transported. Lower bound of the amount of material to be transported Convergence tolerance First, an initial set of uncertain scenarios is generated.

[0128] The third step is to solve the main problem: the main problem is solved in a given set of finite uncertainties. The following optimization is performed, and its mathematical form is:

[0129] (19)

[0130] The following constraints must be met:

[0131] (20)

[0132] in, This represents an auxiliary variable used to approximate the worst-case operating cost, which is the maximum operating cost. It is for the scenario The second stage decision variables are: the first term in formula (17) is the first stage, and the second term is the second stage. That is, the planning cost is the first stage and the operating cost is the second stage.

[0133] Solve this main problem to obtain the current optimal configuration scheme. and objective function value Update the Nether , It represents the worst-case operating cost in the k-th iteration.

[0134] The fourth step is to solve the subproblems. Given a solution to the main problem... Under these conditions, the subproblem is used to find the most unfavorable uncertainty scenario. The subproblem is a max-min problem, in the following form:

[0135] ;(twenty one)

[0136] in, Indicates the first The worst-case scenario obtained in the next iteration yes The optimal solution to the main problem in the next iteration Subproblem variables were defined The feasible domain. , , , , The five dual variables corresponding to each constraint after dual transformation of the second-stage min problem. This means that the variable on the right is the dual variable of the formula on the left.

[0137] The fifth step is to transform the internal linear programming problem (min problem) into its dual form and merge it with the external max problem to form a single maximization problem (i.e., reconstructing the subproblem) as shown in formula (22) for solving.

[0138] ;(twenty two)

[0139] Solve this reconstruction subproblem to obtain the most unfavorable scenario. Update the upper boundary

[0140] Step 6, Convergence check: Calculate the relative gap between the upper and lower bounds. ,like If the algorithm converges, proceed to step seven; otherwise, let The newly found worst-case scenario Add to scene collection Then return to step three for the next iteration.

[0141] Step 7, Output Results: Output the final optimal capacity configuration scheme. And its corresponding robust execution strategy. The execution strategy includes optimal configuration. Under the most unfavorable hydrogen storage scenario At that time, the ship's speed planning and the power scheduling scheme of each power unit.

[0142] The iterative convergence result generated by the column and constraint generation algorithm in this embodiment, which iteratively solves formula (16), is as follows: Figure 3As shown, with the increase of the number of iterations, the objective values ​​of the main problem and the subproblems gradually converge, and the difference between them continuously decreases. When the number of iterations reaches a certain number, the difference between the optimal values ​​of the main problem and the subproblems is less than a preset threshold, the algorithm stops iterating and outputs the final solution. This result shows that the solution method proposed in this invention can achieve stable convergence within a finite number of steps, thereby obtaining the optimal capacity configuration and corresponding robust operation strategy of the hybrid energy storage ship energy system, ensuring the economy and feasibility of the system under the condition of uncertain hydrogen storage.

[0143] In summary, this invention, considering the uncertainty of hydrogen storage capacity on hydrogen production platforms, constructs an energy-navigation system model, defines the uncertainty set, establishes a two-stage robust optimization model, and employs a column and constraint generation algorithm for solution. This achieves coordinated optimization of capacity configuration and operational scheduling for hybrid energy storage vessels. This invention ensures the system remains feasible and economical even under the most unfavorable scenario, effectively improving the efficiency, stability, and reliability of hydrogen transportation. This method is not only applicable to ocean-going hydrogen transportation scenarios but also has good scalability, allowing for application to energy system optimization and scheduling problems of other new energy vessels, demonstrating broad application prospects and significant engineering value.

[0144] Based on the above embodiments, the present invention also provides a terminal device, the principle block diagram of which can be as follows: Figure 4 As shown, the terminal device includes a processor, memory, network interface, and display screen connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for optimizing energy configuration and navigation operations of a transport vessel. The display screen of the terminal device can be a liquid crystal display (LCD) or an e-ink display.

[0145] Those skilled in the art will understand that Figure 4 The schematic diagram shown is only a partial structural diagram related to the present invention and does not constitute a limitation on the terminal device to which the present invention is applied. The specific terminal device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0146] In one embodiment, a terminal device is provided, comprising a memory, a processor, and an energy configuration and navigation operation optimization program for a transport vessel stored in the memory and executable on the processor. When the processor executes the energy configuration and navigation operation optimization program for the transport vessel, it implements the following operation instructions:

[0147] The total voyage distance to be traversed by the ship and the total voyage time set in advance are obtained. Based on the constraints of the ship's berthing time on the transported material, as well as the total voyage distance and the total voyage time, the constraints of the transported material on the sailing speed are constructed. The transported material affects the ship's berthing time to affect the sailing speed required for the ship to complete the total voyage distance within the total voyage time.

[0148] Based on the constraints on the sailing speed imposed by the transported material, constraints on propulsion power are constructed, and based on the constraints on propulsion power, constraints on sailing power are constructed. The constraints on sailing power are used to constrain the power of the equipment that provides power to the ship.

[0149] Based on the constraints on the speed of the transported material and the constraints on the power of the transport, the objective function is used as the optimization objective to optimize the speed of the transport, the power of the transport, and the configuration parameters of the equipment. The variables of the objective function are the speed of the transport, the power of the transport, and the configuration parameters.

[0150] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing energy configuration and navigation operation of a transport vessel, characterized in that, include: The total voyage distance to be traversed by the ship and the total voyage time set in advance are obtained. Based on the constraints of the ship's berthing time on the transported material, as well as the total voyage distance and the total voyage time, the constraints of the transported material on the sailing speed are constructed. The transported material affects the ship's berthing time to affect the sailing speed required for the ship to complete the total voyage distance within the total voyage time. Based on the constraints on the sailing speed imposed by the transported material, constraints on propulsion power are constructed, and based on the constraints on propulsion power, constraints on sailing power are constructed. The constraints on sailing power are used to constrain the power of the equipment that provides power to the ship. Based on the constraints on the sailing speed and the sailing power of the transported material, the sailing speed, the sailing power, and the equipment configuration parameters are optimized using an objective function as the optimization objective. The variables of the objective function are the sailing speed, the sailing power, and the configuration parameters. Methods for constructing constraints on ship berthing time related to the transported goods include: The preparation time required to load the transported material onto the ship is obtained, as well as the loading rate of the transported material is obtained. Based on the preparation time and the loading rate, a constraint is constructed on the transport volume of the transported material on the ship's berthing time, and the constraint on the transport volume of the transported material on the ship's berthing time is used as the constraint on the transported material on the ship's berthing time. The equipment that powers a ship includes generators, energy storage batteries, and fuel cells. The construction of the objective function includes: The configuration parameters are determined, including the configuration power and battery capacity. The configuration power includes the maximum power of the generator, the maximum power of the energy storage battery, and the maximum power of the fuel cell. The battery capacity is the capacity of the energy storage battery. Using the configured power and the battery capacity as variables, construct a planning cost function; The motor power provided by the generator, the battery power provided by the energy storage battery, and the battery power provided by the fuel cell are determined in the navigation power; A navigation cost function is constructed using the motor power, the battery power provided by the energy storage battery, the battery power provided by the fuel cell, and the navigation speed as variables. Based on the planning cost function and the navigation cost function, an objective function is constructed.

2. The energy configuration and navigation operation optimization method for transport vessels as described in claim 1, characterized in that, Based on the constraints on sailing speed and sailing power imposed by the transported material, and with the objective function as the optimization goal, the sailing speed, sailing power, and equipment configuration parameters are optimized, including: The power constraints of the generator and the battery in the navigation power constraints of the ship are determined. The power constraint of the generator is related to the configured power of the generator. The power constraint of the battery includes the power constraint of the energy storage battery and the power constraint of the fuel cell. The power constraint of the energy storage battery is related to the battery capacity and the configured power of the energy storage battery. The power constraint of the fuel cell is related to the configured power of the fuel cell. Based on the power constraints of the generator, the energy storage battery, and the fuel cell, the value of the planning cost function is optimized by optimizing the configuration power values ​​of the generator, the energy storage battery, and the fuel cell, so as to minimize the planning cost function and obtain the optimization target values ​​of the battery capacity and the configuration power. The configuration power includes the configuration power of the generator, the energy storage battery, and the fuel cell. Based on the optimized target values ​​of the generator's configured power, the energy storage battery's configured power, the fuel cell's configured power, the power constraints of the motor, the energy storage battery, and the fuel cell, and in conjunction with the constraints of the transported material on the sailing speed, the value of the sailing cost function is optimized by optimizing the transport volume of the transported material, so that the value of the sailing cost function is minimized. Update the transport volume of the material to be transported, continue to iteratively optimize the navigation cost function, and determine the optimization target values ​​of the navigation speed, the motor power, the energy storage battery power, and the fuel cell power corresponding to the maximum transport volume of the material to be transported.

3. A terminal device, characterized in that, The terminal device includes a memory, a processor, and a transport vessel energy configuration and navigation operation optimization program stored in the memory and executable on the processor. When the processor executes the transport vessel energy configuration and navigation operation optimization program, it implements the steps of the transport vessel energy configuration and navigation operation optimization method as described in any one of claims 1-2.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program for optimizing the energy configuration and navigation operation of a transport vessel. When the program is executed by a processor, it implements the steps of the method for optimizing the energy configuration and navigation operation of a transport vessel as described in any one of claims 1-2.

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