Alternative fuel demand planning method and system, electronic equipment and storage medium

Abstract

The invention discloses an alternative fuel demand planning method and system, electronic equipment and a storage medium, and relates to the technical field of safety, environmental protection and energy conservation, and the method comprises the steps: constructing a target function used for calculating the total cost variation in a preset time period; under the condition that the total CO2 emission reduction and emission amount in the preset time period is constrained, at least two solving algorithms are used for solving the target function, the minimum total cost variation corresponding to each solving algorithm is obtained, the minimum value is determined, and according to the substitution rate of each alternative fuel obtained by solving the solving algorithm corresponding to the minimum value, the total CO2 emission reduction and emission amount in the preset time period is determined. And the demand quantity of each alternative fuel in the preset time period is planned. According to the method, the total cost can be predicted more scientifically and reasonably, and different solving algorithms are utilized to minimize the total cost variation, so that loss caused by contingency can be reduced, it is ensured that the total cost actually needed to be invested is the lowest, and accurate data support is provided for ship fuel filling.

Description

Background Art

[0002] The candidate CO2 emission reduction measures mainly include two aspects: technical factors (i.e. target-based marine fuel standards, which are used to regulate the phased reduction of greenhouse gas intensity of marine fuels) and economic factors (i.e. pricing mechanism based on marine greenhouse gas emissions). Technical factors guide the shipping industry to reduce CO2 emissions through fuel transformation, while the economic evaluation results of economic factors play a decisive role in the choice of fuel transformation path for the shipping industry.

[0003] At present, the alternative fuels / energy sources suitable for marine use and relatively mature include biodiesel, LNG, green methanol, green ammonia and green hydrogen, etc. However, the existing forecasting methods often only one-sidedly evaluate the cost impact of a single factor on fuel transformation, and the results are only applicable to reference in the case of a single ship type or a single type of fuel, and it is difficult to promote and apply them to the overall forecast of the shipping industry. Summary of the invention

[0004] The technical problem to be solved by the present invention is to address the deficiencies of the prior art and specifically provide a method, system, electronic device and storage medium for alternative fuel demand planning, as follows:

[0005] 1) In the first aspect, the present invention provides a method for alternative fuel demand planning, and the specific technical solution is as follows:

[0006] Constructing an objective function for calculating the total cost change within a preset time period, wherein the total cost change within the preset time period includes: the change in the cost of all alternative fuels, the change in the cost of CO2 emissions, and the change in the cost of equipment investment within the preset time period;

[0007] Under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, the objective function is solved by using at least two solving algorithms to obtain the minimum total cost change corresponding to each solving algorithm;

[0008] The minimum value among all minimum total cost changes is determined, and the demand for each alternative fuel within a preset time period is planned based on the substitution rate of each alternative fuel obtained by the solution algorithm corresponding to the minimum value.

[0009] The beneficial effects of an alternative fuel demand planning method provided by the present invention are as follows:

[0010] On the one hand, taking into account multiple aspects such as fuel cost, CO2 emission cost and equipment investment cost, the total cost can be predicted more scientifically and reasonably; on the other hand, using different solution algorithms to minimize the change in total cost can reduce losses caused by contingency, ensure that the actual total cost required is the lowest, and ensure that fuel demand can meet actual needs, providing accurate data support for ship fuel refueling.

[0011] Based on the above solution, the alternative fuel demand planning method of the present invention can also be improved as follows.

[0012] Furthermore, under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, at least two solving algorithms are used to solve the objective function to obtain the minimum total cost change corresponding to each solving algorithm, including:

[0013] Under the condition of constraining the total amount of CO2 emission reduction within a preset time period, the trust region constrained optimization method and the BFGS method are used to solve the objective function respectively, and the minimum total cost change corresponding to the trust region constrained optimization method and the minimum total cost change corresponding to the BFGS method are obtained.

[0014] Furthermore, it also includes:

[0015] When a solution algorithm is used to solve the objective function, the minimum total cost change corresponding to the solution algorithm is determined as the minimum value.

[0016] The beneficial effect of adopting the above-mentioned further technical solution is: in a scenario where there is no need to provide precise alternative fuel demand, for example, when the user only needs to understand the changing trend of alternative fuel demand, the objective function can be solved by a single solution algorithm, and the solution speed is fast, which can provide users with relatively rough data support.

[0017] Furthermore, the total amount of CO2 emission reduction is the total amount of CO2 emission reduction in the shipping industry.

[0018] 2) In the second aspect, the present invention also provides an alternative fuel demand planning system, and the specific technical solution is as follows:

[0019] It includes objective function building module, solution module and alternative fuel demand planning module;

[0020] The objective function construction module is used to: construct an objective function for calculating the total cost change within a preset time period, and the total cost change within the preset time period includes: the change in the cost of all alternative fuels, the change in CO2 emission cost, and the change in equipment investment cost within the preset time period;

[0021] The solution module is used to: solve the objective function using at least two solution algorithms under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, and obtain the minimum total cost change corresponding to each solution algorithm;

[0022] The alternative fuel demand planning module is used to determine the minimum value of all minimum total cost changes, and plan the demand for each alternative fuel within a preset time period based on the substitution rate of each alternative fuel obtained by the solution algorithm corresponding to the minimum value.

[0023] Based on the above solution, the alternative fuel demand planning system of the present invention can also be improved as follows.

[0024] Furthermore, the solution module is specifically used for:

[0025] Under the condition of constraining the total amount of CO2 emission reduction within a preset time period, the trust region constrained optimization method and the BFGS method are used to solve the objective function respectively, and the minimum total cost change corresponding to the trust region constrained optimization method and the minimum total cost change corresponding to the BFGS method are obtained.

[0026] Furthermore, the alternative fuel demand planning module is also used to:

[0027] When a solution algorithm is used to solve the objective function, the minimum total cost change corresponding to the solution algorithm is determined as the minimum value.

[0028] Furthermore, the total amount of CO2 emission reduction is the total amount of CO2 emission reduction in the shipping industry.

[0029] 3) In a third aspect, the present invention further provides an electronic device, comprising a processor, the processor being coupled to a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor so that the electronic device implements any of the above-mentioned alternative fuel demand planning methods.

[0030] 4) In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, any of the above-mentioned alternative fuel demand planning methods is implemented.

[0031] It should be noted that the beneficial effects achieved by the technical solutions of the second to fourth aspects of the present invention and the corresponding possible implementation methods can be found in the above-mentioned technical effects of the first aspect and its corresponding possible implementation methods, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments of the present invention:

[0033] Figure 1 A flowchart of an alternative fuel demand planning method according to an embodiment of the present invention;

[0034] Figure 2A schematic diagram of the structure of an alternative fuel demand planning system according to an embodiment of the present invention;

[0035] Figure 3 The figure is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0037] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0038] like Figure 1 As shown, a method for alternative fuel demand planning in an embodiment of the present invention includes the following steps:

[0039] S1. constructing an objective function for calculating the total cost change within a preset time period, wherein the total cost change within the preset time period includes: the change in the cost of all alternative fuels, the change in the cost of CO2 emissions, and the change in the cost of equipment investment within the preset time period;

[0040] The total amount of CO2 emission reduction refers to the total amount of CO2 emission reduction in the shipping industry, and may also be the total amount of CO2 emission reduction in other industries, and may be set according to actual conditions.

[0041] Among them, in the present invention, the alternative fuels used include: liquefied natural gas (LNG), bio-liquefied natural gas (bio-LNG), biodiesel (UCO-biodiesel), biomethanol (bio-methanol), electronic liquefied natural gas (e-LNG), electronic methanol (e-methanol), green ammonia (e-ammonia), green methanol and green hydrogen, etc., and the traditional fuel can also be set to heavy oil according to actual conditions.

[0042] The total cost change refers to the total cost when using alternative fuels minus the total cost when using traditional fuels.

[0043] The duration of the preset time period may be n years, where n may be 0.5, 1, 2 or 5, etc., and may be set according to actual conditions.

[0044] Taking "the total amount of CO2 emission reduction is the total amount of CO2 emission reduction in the shipping industry, and the duration of the preset time period is n years" as an example, the following explanation is given.

[0045] The change in the cost of all alternative fuels in year t is calculated using the following formula:

[0046]

[0047] Among them, ΔCOST Fuel,t Indicates: the change in the cost of all alternative fuels in the tth year; η j,t Indicates: the replacement rate of the jth alternative fuel in the tth year, C T,t Indicates: the total consumption of traditional fuels in the tth year, p j,t Indicates: the unit price of the jth alternative fuel in the tth year, p o,t It represents: the unit price of traditional fuel in the tth year, J represents: the number of alternative fuel types, the tth year represents: the tth year within the preset time period, for example, if the preset time period is 1 year, the value range of t is: 1, if the preset time period is 2 years, the value range of t is: 1 and 2, if the preset time period is 5 years, the value range of t is: 1, 2, 3, 4 and 5, when the preset time period is 0.5 years, the value of t is 0.5, and the 0.5th year represents: 6 months, i.e. half a year.

[0048] The change in CO2 emission cost in year t is calculated by the following formula:

[0049]

[0050] in, Indicates: the change in CO2 emission cost in the tth year, Denotes: CO2 emission factor of the jth alternative fuel, Indicates: CO2 emission factor of traditional fuels, p CO2,t Indicates: the unit price of CO2 emitted in the tth year.

[0051] Since in this embodiment, the total amount of CO2 emission reduction is the total amount of CO2 emission reduction in the shipping industry, the equipment investment cost is specifically the investment cost of ship modification / rebuilding, and the change in equipment investment cost in the tth year is calculated by the following formula:

[0052]

[0053] Among them, ΔCOST Fuel,t Indicates: the change in the investment cost of ship modification / rebuilding in the tth year, DWT k Indicates: the total DWT of the kth ship type, Δp DWT,k,j It represents the additional cost per unit DWT in the modification / reconstruction of a ship; DWT represents deadweight tonnage, and K represents the total number of ship types.

[0054] Used to calculate the total cost change ΔCOST in year t T,t The objective function is:

[0055]

[0056] The objective function for calculating the total cost change within a preset time period (the duration is n years) can be obtained by formula (1), formula (2), formula (3) and formula (4).

[0057] S2. Under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, the objective function is solved using at least two solving algorithms to obtain the minimum total cost change corresponding to each solving algorithm.

[0058] Among them, the following formula is used to calculate the total amount of CO2 emission reduction in the tth year:

[0059] The total amount of CO2 emission reduction within a preset time period (n years) can be calculated using formula (5).

[0060] The expression used to represent “constraining the total amount of CO2 emission reduction in year t” is:

[0061]

[0062] Indicates: CO2 intensity reduction target stipulated by the International Maritime Organization in the tth year.

[0063] Formula (6) can be used to obtain an expression for representing "constraining the total amount of CO2 emission reduction within a preset time period (the duration is n years)".

[0064] S3. Determine the minimum value among all minimum total cost changes, and plan the demand for each alternative fuel within a preset time period based on the substitution rate of each alternative fuel obtained by the solution algorithm corresponding to the minimum value.

[0065] Optionally, the NPV of the investment benefit within a preset time period is calculated by the following formula:

[0066]

[0067] Here, i represents the discount rate.

[0068] Optionally, in S2, when the total amount of CO2 emission reduction within a preset time period is constrained, at least two solution algorithms are used to solve the objective function to obtain the minimum total cost change corresponding to each solution algorithm, including:

[0069] Under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, the objective function is solved by using the trust region constraint optimization method and the BFGS method, respectively, to obtain the minimum total cost change corresponding to the trust region constraint optimization method and the minimum total cost change corresponding to the BFGS method, specifically:

[0070] 1) The solution method of the trust region constrained optimization method is to input the relevant parameter information of the use of marine fuel (including alternative fuels and traditional fuels), set the objective function, formulate constraints, preset the initial guess of the fuel substitution rate combination of alternative fuels, and limit the boundary conditions of the problem.

[0071] 2) The BFGS solution method is to input relevant parameter information of marine fuel use, set penalty terms according to the objective function to approximate the equality constraints, define the constraints and boundaries, preset the initial guess fuel substitution rate combination, and define the optimization parameter terms.

[0072] Optionally, the method further includes: when a solution algorithm is used to solve the objective function, determining the minimum total cost corresponding to the solution algorithm as the minimum value.

[0073] Optionally, after the preset ship is refueled according to the ratio between the planned demand for each alternative fuel and the demand for traditional fuel, the planned driving path of the preset ship is obtained, and the planned driving path is segmented according to the hydrological conditions. Specifically, the planned driving path is segmented according to parameters such as water temperature, wave height, seawater flow rate in the hydrological conditions to obtain multiple sub-paths, and the water temperature, wave height, seawater flow rate, total weight of the ship (including hull and load), ship's driving speed, and fuel consumption at multiple historical moments are used to fit the change relationship curve between the ship's driving speed and fuel consumption under different water temperatures, wave heights, seawater flow rates, and total weights of the ship. The water temperature, wave height, seawater flow rate, and total weight of each sub-path are used, and combined with the change relationship curve between the ship's driving speed and fuel consumption, under the constraint of the maximum travel time set for each sub-path, the optimal driving speed of the preset ship corresponding to each sub-path is calculated, and the preset ship is controlled to maintain the corresponding optimal driving speed when passing through each sub-path.

[0074] Optionally, in the above technical solution, when the preset ship travels according to the travel path, the actual travel route and the planned travel route of the preset ship are superimposed in real time on the same image, and the position points are collected at the preset distance in the actual travel route and the planned travel route of the preset ship, and the actual longitude and latitude coordinates and the planned longitude and latitude coordinates of each collected position point are obtained, and the position deviation between the actual longitude and latitude coordinates and the planned longitude and latitude coordinates of each position point is calculated, and the proportion of the position points with a position deviation greater than the preset position deviation is used as the overlap between the actual travel route and the planned travel route of the preset ship. When the overlap is less than the preset overlap threshold, an early warning is issued, and the beneficial effects are:

[0075] In the current early warning method, the deviation between the actual route and the planned route of the preset ship is monitored in real time. When the deviation is too large, an alarm will be directly issued. However, due to the influence of severe hydrological conditions such as high winds and waves during the navigation of the preset ship, a brief deviation will inevitably occur. However, according to the existing alarm method, an alarm will be directly issued, which will affect the mood of the crew and cause panic. Therefore, the overlap between the actual route and the planned route of the preset ship is calculated in a discrete manner, which is more flexible and will not cause unnecessary panic.

[0076] In another embodiment, the total cost of fuel use in the shipping industry is calculated by using parameters such as fuel cost, CO2 emissions, CO2 emission costs, and ship modification / reconstruction investment costs. The penetration rate of each type of fuel is used as an optimization variable, and the trust-region constrained optimization method (trust-region constrained optimization) and the BFGS (Broyden-Fletcher-Goldfarb-Shanno method) are used to solve the minimum fuel use cost and fuel demand for the shipping industry to achieve the International Maritime Organization's CO2 target emissions.

[0077] The present invention comprises the following key steps: quantification of the International Maritime Organization's CO2 intensity reduction target, conversion of shipping industry fuel consumption and CO2 emissions, calculation of fuel use costs (including fuel costs, CO2 emission costs, and ship modification / rebuilding investment costs), and solution using trust-region constrained optimization and BFGS (Broyden-Fletcher-Goldfarb-Shanno method).

[0078] Among them, the International Maritime Organization's CO2 emission reduction target is quantified: based on the demand for shipping business, the International Maritime Organization's latest CO2 emission intensity reduction target requirements are converted into the total CO2 emission reduction target for the shipping industry.

[0079] Among them, the conversion of fuel consumption and CO2 emissions in the shipping industry: use the penetration rate of various types of fuel to determine the consumption of various types of fuel, calculate the CO2 emissions of various types of fuel through the CO2 emission conversion coefficients of various types of fuel, and add them up to determine the total CO2 emissions of the shipping industry.

[0080] Among them, fuel use cost forecast: The comprehensive fuel use cost is the algebraic sum of fuel cost, CO2 emission cost, and ship modification / rebuilding investment cost. Fuel cost is the sum of the costs of various types of fuels, and the costs of various types of fuels are determined by their usage and prices. CO2 emission cost is the sum of the CO2 emission costs of various types of fuels, and the CO2 emission costs of various types of fuels are determined by their CO2 emissions and unit CO2 emission prices. The investment cost of ship modification / rebuilding in the shipping industry is determined by the substitution rate of various types of fuels and the investment cost of ship modification / rebuilding of various types of fuel-powered ships.

[0081] Among them, the comprehensive solution method: the problem of solving the combination of fuel substitution rates is a nonlinear problem with complex constraints. The present invention proposes a more efficient and robust optimization strategy, combining the use of trust region constrained optimization method and BFGS method, and obtaining the minimum cost through comparative analysis between methods. The solution method of the trust region constrained optimization method is to input the relevant parameter information of the use of marine fuel, set the objective function, formulate constraints, preset the initial guess fuel substitution rate combination, and limit the boundary conditions of the problem to be solved, and use the trust region constrained optimization method (trust-region constrained optimization) to solve the problem. The BFGS solution method is to input the relevant parameter information of the use of marine fuel, set the penalty term according to the objective function for approximate processing of equality constraints, define constraints and boundaries, preset the initial guess fuel substitution rate combination, define optimization parameter terms, and use the BFGS (Broyden-Fletcher-Goldfarb-Shanno method) method to solve the problem. The optimal solutions obtained by the two solution methods are compared again to obtain the minimum cost of fuel transformation in the shipping industry.

[0082] The present invention can be applied to predict the fuel demand under the minimum cost constraint based on the international shipping greenhouse gas emission reduction policy. It can also be further combined with the carbon intensity and cost assessment of the ship fuel throughout its life cycle, as well as the distribution of ship fuel consumption on major routes around the world and my country, to scientifically and rationally determine the future global ship fuel demand and distribution, provide data support for the fuel refueling demand and LNG refueling demand of international ships, and provide reference for the company's LNG ocean refueling business positioning, development goals, and layout decisions. Compared with the existing technology, it has the following advantages:

[0083] 1) For the current forecasting methods of the shipping industry, fuel industry and shipping companies, it has more comprehensive ship types, DWT, fuel types, fuel & carbon emissions & ship repair cost algorithms, more accurate policy quantitative data, and parameter settings are determined based on exclusive DCS data and industry data. It has technical advantages in boundary condition setting, algorithm and parameter assignment, and result optimization.

[0084] 2) The present invention solves the problem that the current CO2 emission prediction model for the shipping industry lacks a comprehensive economic evaluation, predicts fuel costs, CO2 emission costs, and investment costs for ship modification / rebuilding, and establishes a comprehensive cost calculation method for fuel transformation in the shipping industry.

[0085] 3) Taking the IMO CO2 emission reduction target, fuel price and CO2 price as constraints, an innovative hybrid solution system is constructed using trust-region constrained optimization and BFGS (Broyden-Fletcher-Goldfarb-Shanno method) to solve the problem of large-scale solution with many fuel types.

[0086] In another embodiment, the steps include:

[0087] S11. Use DCS (data collection system) data and industry data to set parameters, specifically:

[0088] 1) Types of alternative fuels, including bio-LNG (bio-liquefied natural gas), UCO-biodiesel,

[0089] bio-methanol, e-LNG, e-methanol, e-ammonia;

[0090] 2) Assign parameters such as substitution rate (eta_j), unit cost (p_j), and carbon dioxide emission coefficient (CF_j) to each alternative fuel;

[0091] 3) Set the total fuel consumption forecast value (C_T), benchmark fuel cost (p_0), benchmark CO2 emission factor (CF_0), CO2 price (p_CO2) and CO2 emission requirement (E_CO2Required).

[0092] S12. Set the objective function:

[0093] 1) Convert the IMO greenhouse gas emission intensity target into an objective function to be solved, taking into account the price of alternative fuels and the price of carbon dioxide emissions;

[0094] 2) The objective function includes calculation of fuel cost and carbon dioxide emission related costs;

[0095] 3) CO2 emission costs are calculated based on the difference between the CO2 emissions of the alternative fuel and the baseline emissions;

[0096] The program code of the objective function is as follows:

[0097] def cost_function(eta_j):

[0098] delta_COST_Fuel=np.sum(eta_j*C_T*p_j)-np.sum(C_T*p

[0099] _0*eta_j)

[0100] delta_COST_CO2eq=(np.sum(eta_j*C_T*CF_j)-np.sum(C_

[0101] T*CF_0*eta_j))*p_CO2

[0102] return delta_COST_Fuel+delta_COST_CO2eq

[0103] S13. Processing Equality Constraints: Identify and process the equality constraints in the optimization problem, including fuel supply, demand balance and other restrictions. The code for the constraint conditions is as follows:

[0104] eta_min = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # minimum value of 6 fuel substitution rates

[0105] eta_max = [1.0, 1.0, 1.0, 1.0, 1.0] # Maximum value of 6 fuel substitution rates

[0106] def constraint1(eta_j):

[0107] return eta_j-eta_min

[0108] def constraint2(eta_j):

[0109] return eta_max-eta_j

[0110] def constraint3(eta_j):

[0111] return 1-np.sum(eta_j)

[0112] def constraint4(eta_j):

[0113] # Ensure that CO2 emissions do not exceed E_CO2Required

[0114] return E_CO2Required-np.sum(eta_j*C_T*CF_j)-C_T*CF_0*

[0115] (1-np.sum(eta_j))

[0116] S14. Preset initial fuel substitution rate combination: set an initial value (eta_j_initial) for the fuel substitution rate.

[0117] S15. Execute optimization algorithm:

[0118] 1) The fuel substitution rate combination is obtained through different optimization algorithms, and the trust region constrained optimization method and BFGS (Broyden-Fletcher-Goldfarb-Shanno) method are used to solve in parallel;

[0119] 2) Define the algorithm parameters and options before execution, such as the number of iterations, convergence criteria, etc.

[0120] 3) The optimization process may involve multiple iterations to find the best fuel substitution rate combination that satisfies all constraints.

[0121] S16. Fuel substitution rate optimization:

[0122] The selected optimization algorithm is used to find the optimal solution for the fuel substitution rate to minimize the total cost after fuel substitution.

[0123] S17, cost comparison:

[0124] 1) Compare the total costs of different optimal fuel substitution rate combinations, including fuel costs and costs related to CO2 emissions.

[0125] 2) Determine which fuel substitution rate combination can achieve the lowest total cost while meeting IMO's emission reduction environmental goals.

[0126] S18. Output results:

[0127] The minimized total cost of alternative marine fuels is obtained by analyzing the demand for each alternative marine fuel to support the decision-making process and resource allocation.

[0128] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given by the present invention. Those skilled in the art may adjust the execution order of S1, S2, etc. according to actual conditions, which is also within the protection scope of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0129] like Figure 2 As shown, an alternative fuel demand planning system 200 according to an embodiment of the present invention includes an objective function building module 201, a solving module 202 and an alternative fuel demand planning module 203;

[0130] The objective function construction module 201 is used to: construct an objective function for calculating the total cost change within a preset time period, and the total cost change within the preset time period includes: the change in the cost of all alternative fuels, the change in the cost of CO2 emissions, and the change in the cost of equipment investment within the preset time period;

[0131] The solution module 202 is used to: solve the objective function using at least two solution algorithms under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, and obtain the minimum total cost change corresponding to each solution algorithm;

[0132] The alternative fuel demand planning module 203 is used to determine the minimum value of all minimum total cost changes, and plan the demand for each alternative fuel within a preset time period according to the substitution rate of each alternative fuel obtained by the solution algorithm corresponding to the minimum value.

[0133] Optionally, in the above technical solution, the solving module 202 is specifically used for:

[0134] Under the condition of constraining the total amount of CO2 emission reduction within a preset time period, the trust region constrained optimization method and the BFGS method are used to solve the objective function respectively, and the minimum total cost change corresponding to the trust region constrained optimization method and the minimum total cost change corresponding to the BFGS method are obtained.

[0135] Optionally, in the above technical solution, the alternative fuel demand planning module 203 is further used for:

[0136] When a solution algorithm is used to solve the objective function, the minimum total cost change corresponding to the solution algorithm is determined as the minimum value.

[0137] Optionally, in the above technical solution, the total amount of CO2 emission reduction is the total amount of CO2 emission reduction in the shipping industry.

[0138] It should be noted that the beneficial effects of the alternative fuel demand planning system 200 provided in the above embodiment are the same as the beneficial effects of the above alternative fuel demand planning method, which will not be described in detail here. In addition, when the system provided in the above embodiment realizes its functions, it only uses the division of the above functional modules as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the system can be divided into different functional modules according to actual conditions to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be described in detail here.

[0139] Among them, the alternative fuel demand planning system of the present invention can be a computer program (including program code) running in a computer device. For example, the alternative fuel demand planning system of the present invention is an application software that can be used to execute the corresponding steps in the alternative fuel demand planning method of the present invention.

[0140] In some embodiments, the alternative fuel demand planning system of the present invention can be implemented in a combination of software and hardware. As an example, the alternative fuel demand planning system of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the alternative fuel demand planning method of the present invention. For example, the processor in the form of a hardware decoding processor can adopt one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs) or other electronic components.

[0141] The modules involved in the embodiments of the present invention may be implemented in software or hardware. The name of a module does not limit the module itself in some cases.

[0142] An electronic device according to an embodiment of the present invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, any one of the above-mentioned alternative fuel demand planning methods is implemented. That is to say, an electronic device according to an embodiment of the present invention may include but is not limited to: a processor and a memory; a memory for storing a computer program; a processor for executing the alternative fuel demand planning method shown in any embodiment of the present invention by calling a computer program.

[0143] In an alternative embodiment, an electronic device is provided, such as Figure 3 As shown, Figure 3 The electronic device 4000 shown includes: a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, such as through a bus 4002. Optionally, the electronic device 4000 may also include a transceiver 4004, which may be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0144] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 4001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0145] The bus 4002 may include a path to transmit information between the above components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 In the figure, only one thick line is used to represent the bus 4002, but this does not mean that there is only one bus or one type of bus.

[0146] The memory 4003 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to this.

[0147] The memory 4003 is used to store the application code (computer program) for executing the solution of the present invention, and the execution is controlled by the processor 4001. The processor 4001 is used to execute the application code stored in the memory 4003 to implement the content shown in the above method embodiment.

[0148] Among them, the electronic device can also be a terminal device, and the terminal device can be any device that can install applications, including at least one of a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, a smart TV, and a smart car device.

[0149] It should be noted that Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0150] A computer-readable storage medium according to an embodiment of the present invention stores a computer program, and when the computer program is executed by a processor, any of the above-mentioned alternative fuel demand planning methods is implemented.

[0151] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0152] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device performs any of the above-mentioned alternative fuel demand planning methods.

[0153] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0154] It should be understood that the flow charts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the module, the program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0155] The computer-readable storage medium provided by the embodiment of the present invention may be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or component.

[0156] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the method shown in the above embodiment.

[0157] The above description is only a preferred embodiment of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the disclosure scope involved in the present invention is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present invention (but not limited to) by each other.

[0158] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects and represent the definition of a specific order or sequence. The order of use of similar objects can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than the order shown or described.

[0159] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0160] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for planning alternative fuel demand, characterized in that: include: Constructing an objective function for calculating the total cost change within a preset time period, wherein the total cost change within the preset time period includes: the change in the cost of all alternative fuels, the change in the cost of CO2 emissions, and the change in the cost of equipment investment within the preset time period; Under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, the objective function is solved by using at least two solving algorithms to obtain the minimum total cost change corresponding to each solving algorithm; The minimum value among all the minimum total cost changes is determined, and the demand for each alternative fuel within a preset time period is planned according to the substitution rate of each alternative fuel obtained by the solution algorithm corresponding to the minimum value.

2. The alternative fuel demand planning method according to claim 1, characterized in that: Under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, the objective function is solved by using at least two solving algorithms to obtain the minimum total cost change corresponding to each solving algorithm, including: Under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, the objective function is solved respectively using the trust region constrained optimization method and the BFGS method to obtain the minimum total cost change corresponding to the trust region constrained optimization method and the minimum total cost change corresponding to the BFGS method.

3. The alternative fuel demand planning method according to claim 1, characterized in that: Also includes: When a solution algorithm is used to solve the objective function, the minimum total cost change corresponding to the solution algorithm is determined as the minimum value.

4. A method for planning alternative fuel demand according to any one of claims 1 to 3, characterized in that: The total amount of CO2 emission reduction is the total amount of CO2 emission reduction in the shipping industry.

5. An alternative fuel demand planning system, characterized in that: It includes objective function building module, solution module and alternative fuel demand planning module; The objective function construction module is used to construct an objective function for calculating the total cost change within a preset time period, and the total cost change within the preset time period includes: the change in the cost of all alternative fuels, the change in CO2 emission cost, and the change in equipment investment cost within the preset time period; The solution module is used to: solve the objective function using at least two solution algorithms under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, and obtain the minimum total cost change corresponding to each solution algorithm; The alternative fuel demand planning module is used to determine the minimum value of all minimum total cost changes, and plan the demand for each alternative fuel within a preset time period based on the substitution rate of each alternative fuel obtained by the solution algorithm corresponding to the minimum value.

6. The alternative fuel demand planning system according to claim 5, characterized in that: The solution module is specifically used for: Under the condition that the total amount of CO2 emission reduction within a preset time period is constrained, the objective function is solved respectively using the trust region constrained optimization method and the BFGS method to obtain the minimum total cost change corresponding to the trust region constrained optimization method and the minimum total cost change corresponding to the BFGS method.

7. The alternative fuel demand planning system according to claim 5, characterized in that: The alternative fuel demand planning module is also used to: When a solution algorithm is used to solve the objective function, the minimum total cost change corresponding to the solution algorithm is determined as the minimum value.

8. An alternative fuel demand planning system according to any one of claims 5 to 7, characterized in that: The total amount of CO2 emission reduction is the total amount of CO2 emission reduction in the shipping industry.

9. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, an alternative fuel demand planning method as claimed in any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for planning demand for alternative fuels according to any one of claims 1 to 4 is implemented.

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