A method and device for optimizing configuration of a green electricity-hydrogen-ammonia integrated delivery system

Abstract

The application discloses a kind of green electricity hydrogen ammonia integrated delivery system optimization configuration method and device, green electricity production, hydrogen production ammonia, power delivery, ammonia energy transport and terminal use are regarded as whole and are unified capacity planning, with terminal comprehensive energy cost minimum as target. Wind light timing data, equipment cost, operating parameter and delivery channel basic data are obtained;Optimization variable and change range of to-be-configured equipment scale are set;Cost model with terminal comprehensive energy cost minimum as target is constructed;Establishes the constraint set of multi-energy flow coupling of electricity, hydrogen, ammonia;Global optimal configuration is obtained by using mixed optimization algorithm solution.This application realizes electricity-hydrogen-ammonia multi-link integrated collaborative optimization, breaks through the single configuration limitation only for power delivery, can significantly improve new energy utilization, reduce terminal comprehensive energy cost, improve calculation efficiency, suitable for large wind light base green electricity hydrogen ammonia integrated delivery system capacity optimization configuration.

Description

Technical Field

[0001] This invention belongs to the field of new energy optimization configuration technology, and in particular relates to a method and device for optimizing the configuration of an integrated green electricity, hydrogen and ammonia transmission system. Background Technology

[0002] To achieve efficient utilization of renewable energy, there are currently two complementary pathways: one is to transmit green electricity to load centers in central and eastern China via ultra-high-voltage direct current (UHVDC) transmission lines; the other is to construct local green electricity-to-hydrogen-ammonia projects to convert unstable renewable energy into storable and transportable hydrogen and ammonia products, thus achieving diversified utilization of renewable energy. However, how to coordinate these two pathways to achieve global system optimization remains a pressing technical challenge.

[0003] Existing technologies mainly have the following three types of solutions and their shortcomings: The first type is a single power transmission configuration. This type of scheme uses ultra-high-voltage direct current (UHVDC) transmission as its core, and incorporates wind power, photovoltaic power, and electrochemical energy storage. Its drawback lies in considering only the transmission of electricity as a single energy form. When peak renewable energy output exceeds the transmission capacity, it can only rely on curtailment, resulting in a low overall utilization rate of renewable energy (typically only 70%-80%) and significant resource waste. Simultaneously, electrochemical energy storage is costly and has limited peak-shaving capabilities, making it difficult to adapt to the fluctuating demand from future high-proportion renewable energy integration.

[0004] The second category is a single on-site consumption solution. This type of solution involves constructing electrolyzers and synthesis towers on-site to convert green electricity into hydrogen and ammonia. However, the market for hydrogen and ammonia products is highly regional and seasonal. Without diversified support from external transmission channels, it will face the dilemma of narrow product consumption channels, insufficient market size, and long investment return cycles. In addition, constructing long-distance hydrogen / ammonia pipelines alone is constrained by both poor economics and high safety risks.

[0005] The third category is a simple parallel scheme of electricity transmission and hydrogen / ammonia production. While this type of scheme incorporates both types of facilities, their planning and design are fragmented. Electricity transmission is typically designed as a power source project, and hydrogen / ammonia production as a chemical project, then simply superimposed. This model lacks a description of the coupling relationship and a collaborative optimization mechanism between the electricity, hydrogen, and ammonia multi-energy flows, leading to redundancy or shortcomings in capacity configuration among subsystems. Specifically, the wasted electricity from the electricity transmission channel cannot be dynamically absorbed by the hydrogen production system, and when the electricity demand of the hydrogen production system does not match the fluctuations in renewable energy output, there is a lack of system-level energy storage coordination, causing hydrogen production equipment to operate at low loads or frequently start and stop, severely reducing equipment lifespan and conversion efficiency.

[0006] In summary, existing technologies lack a method for unified capacity planning that considers green electricity production, on-site hydrogen and ammonia production, electricity transmission, ammonia energy transmission, and end-use as a whole. In particular, existing technologies have failed to establish a cost model and constraint system for the coupling of multiple energy flows (electricity, hydrogen, and ammonia), and have also failed to adopt efficient solution algorithms suitable for multivariable, strongly coupled, and high-dimensional optimization scenarios, making it difficult to achieve the globally optimal configuration of an integrated green electricity, hydrogen, and ammonia transmission system.

[0007] In view of this, this application proposes an optimized configuration method and apparatus for an integrated green electricity, hydrogen, and ammonia delivery system, aiming to overcome the aforementioned technical bottlenecks. Summary of the Invention

[0008] To address the above technical problems, this invention provides an optimized configuration method and apparatus for an integrated green electricity, hydrogen, and ammonia delivery system.

[0009] The technical solution adopted by this invention to solve its technical problem is: An optimized configuration method for an integrated green electricity, hydrogen, and ammonia transmission system takes a multi-energy flow system encompassing green electricity production, on-site hydrogen and ammonia production, power and hydrogen / ammonia transmission, and end-user consumption as a unified optimization object, and performs overall capacity coordination planning, including the following steps: S100: Obtain basic data for the integrated green electricity, hydrogen, and ammonia transmission base. The basic data includes wind and solar resource time-series characteristics data, unit investment and operation and maintenance costs of each piece of equipment, operating parameters of each piece of equipment, and transmission channel parameters. S200: Set the optimization variables and their range of variation. The optimization variables are used to characterize the scale of the devices to be configured in the system. S300: Based on the unit investment and maintenance costs and operating parameters of each device in the basic data, a cost calculation model is constructed with the goal of minimizing the comprehensive energy cost of the terminal. S400: Based on the time-series characteristic data of wind and solar resources in the basic data, the operating parameters of each device and the parameters of the external transmission channel, a set of multi-energy flow coupling constraints is established. The constraints are used to ensure the supply and demand balance of electricity, hydrogen and ammonia in the system and the safe operation of the equipment. S500: The cost calculation model is solved by a hybrid optimization algorithm. Under the premise of substituting the basic data and satisfying the set of multi-energy flow coupling constraints, the optimal solution of the optimization variables that makes the overall energy cost of the terminal approach the global optimum is obtained, thereby determining the optimal configuration scheme of each device in the system.

[0010] Preferably, the overall system includes an electricity transmission network, a hydrogen / ammonia energy transmission network, and an end-user energy network. These networks are coupled together through the three energy flow forms of electricity, hydrogen, and ammonia, forming a unified green electricity-hydrogen-ammonia integrated transmission system. The power transmission network includes wind farms, photovoltaic power stations, electrochemical energy storage devices, ultra-high voltage direct current transmission lines and converter station equipment, which are used to transmit green electricity to load centers; The hydrogen / ammonia energy transmission network includes electrolyzers, synthesis towers, hydrogen storage tanks, ammonia storage tanks, and hydrogen / ammonia pipeline equipment, which are used to convert unstable new energy sources into storable and transportable hydrogen / ammonia products. The end-use energy network includes end-use electrical loads, ammonia cracking hydrogen production units, and hydrogen / ammonia end-users, enabling the end-use of multiple energy forms such as electricity, hydrogen, and ammonia.

[0011] Preferably, the time-series characteristic data of wind and solar resources in S100 includes the output coefficient of wind power and photovoltaic power for 8760 hours per year; the unit investment and operation and maintenance costs of each piece of equipment include the unit investment cost and annual operation and maintenance cost coefficient of wind power, photovoltaic power, electrochemical energy storage, electrolyzer, synthesis tower, hydrogen storage, ammonia storage, ultra-high voltage DC transmission, hydrogen pipeline, and ammonia pipeline; the operating parameters include the hydrogen production efficiency of electrolyzer, the ammonia synthesis efficiency of synthesis tower, the charge and discharge efficiency of electrochemical energy storage, the charge and discharge efficiency of hydrogen / ammonia storage, and the hydrogen production efficiency of ammonia cracking; the parameters of the external transmission channel include the ultra-high voltage DC transmission capacity and transmission loss rate, the transmission capacity and pipeline cost of hydrogen / ammonia pipeline, and the terminal demand scale of hydrogen and ammonia.

[0012] Preferably, the optimized variables in S200 include wind power installed capacity, photovoltaic installed capacity, electrochemical energy storage capacity, electrolyzer capacity, synthesis tower capacity, hydrogen storage capacity, ammonia storage capacity, and the scale of hydrogen / ammonia pipelines. Specifically, the wind power installed capacity is set within a range based on the wind and solar resource assessment results; the photovoltaic installed capacity is set within a range based on land resource constraints and solar energy resources; the electrochemical energy storage capacity is set within a range based on the fluctuation characteristics of new energy output and peak-shaving demand; the electrolyzer capacity is set within a range based on hydrogen production demand and new energy curtailment; the synthesis tower capacity is set within a range based on the synthetic ammonia production demand and hydrogen supply capacity; the hydrogen storage capacity is set within a range based on hydrogen supply and demand balance and buffering demand; the ammonia storage capacity is set within a range based on ammonia product supply and demand balance and seasonal demand; the scale of the ultra-high voltage direct current transmission line is set within a range based on the amount of new energy power transmitted; and the scale of the hydrogen and ammonia pipelines are set within a range based on the amount of hydrogen and ammonia products transmitted, respectively.

[0013] Preferably, the cost calculation model constructed in S300 specifically includes: The initial investment cost of the computing system includes investment in the power supply side, investment in hydrogen production and ammonia synthesis equipment, investment in ultra-high voltage direct current transmission, and investment in hydrogen and ammonia pipelines. The capital recovery factor is calculated based on the average social rate of return on capital and the total life cycle operating years of the green electricity-hydrogen-ammonia integrated project. The annual operation and maintenance cost of the system is calculated based on the scale of each piece of equipment and its operation and maintenance cost coefficient. The annual power transmission cost is calculated based on the annual external power volume, transmission loss rate, transmission price, and transmission cost per unit of power volume. Calculate the annual hydrogen / ammonia pipeline transportation cost based on the annual hydrogen / ammonia transport volume and unit transportation cost; Calculate the cost of hydrogen production from ammonia cracking at the terminal based on the terminal hydrogen demand and the unit hydrogen cracking cost. Based on the above costs, capital recovery coefficients, and energy revenues from electricity, hydrogen, and ammonia at the end, the comprehensive energy cost at the end is calculated.

[0014] Preferably, the initial investment cost is as follows: (1) In the formula, , , , , , , , , , These are the unit investment costs for wind power, photovoltaic power, electrochemical energy storage, electrolyzers, synthesis towers, hydrogen storage, ammonia storage, ultra-high voltage direct current transmission, hydrogen pipelines, and ammonia pipelines, respectively. , , , , , , , , , These are wind power installed capacity, photovoltaic installed capacity, electrochemical energy storage capacity, electrolyzer capacity, synthesis tower capacity, hydrogen storage capacity, ammonia storage capacity, ultra-high voltage direct current transmission line scale, hydrogen pipeline scale, and ammonia pipeline scale. The capital recovery factor is as follows: (2) In the formula, This is the capital recovery factor. The average rate of return on social capital. The total lifecycle operation period of the green electricity-hydrogen-ammonia integrated project; The annual operation and maintenance cost is calculated as follows: (3) In the formula, For the first Equipment size For the first The annual operation and maintenance cost coefficient for this type of equipment does not include ultra-high voltage direct current transmission and pipeline hydrogen / ammonia transportation; Calculate annual power transmission costs Specifically: (4) In the formula, For the annual electricity transmitted to other regions, The power transmission loss rate of ultra-high voltage direct current (UHVDC) For transmission price, Transmission cost per unit of electricity; Calculate the annual transportation costs of hydrogen and ammonia via pipelines. Specifically: (5) In the formula, Annual hydrogen transport volume For the unit cost of hydrogen transportation, This refers to the annual ammonia transport volume. Cost per unit of ammonia transport; Calculate the cost of hydrogen production from ammonia cracking at the terminal. Specifically: (6) In the formula, For end-user hydrogen demand, Cost per unit of hydrogen cracking; Calculate the comprehensive unit energy cost of the terminal Specifically: (7) In the formula, and This refers to the electrical equivalent values ​​of ammonia and hydrogen calculated based on their calorific value.

[0015] Preferably, the multi-energy flow coupling constraints established in S400 include: real-time power balance constraints, power balance constraints, hydrogen balance constraints, ammonia balance constraints, external transmission channel capacity constraints, hydrogen / ammonia pipeline capacity constraints, and equipment operation constraints. The specific real-time power balance constraints are as follows: (8) In the formula, For the first Heavenly Hourly power transmission load For the first Heavenly Hourly hydrogen production electrolyzer load size, For the first Heavenly Hourly load of ammonia synthesis tower For the first Heavenly Hourly wind power output coefficient For the first Heavenly Hourly photovoltaic power output coefficient For the first Heavenly Hourly energy storage charging and discharging status, For the first Heavenly Hourly energy storage charge and discharge power coefficient For the first Heavenly Hourly power curtailment; The specific power balance constraints are as follows: (9) (10) In the formula, The annual electricity consumption for producing synthetic ammonia The annual electricity consumption for producing synthetic ammonia Electricity storage consumes electricity. This represents the total amount of abandoned electricity. This refers to the annual equivalent full-load utilization hours of wind power. The equivalent full-load utilization hours of photovoltaic power per year; The hydrogen balance constraints are as follows: (11) In the formula, For the first Heavenly The hourly hydrogen consumption of the synthesis tower For the first Heavenly The hourly hydrogen production capacity of a hydrogen electrolyzer. For the first Heavenly The amount of hydrogen stored and released in the hydrogen storage tank per hour; The specific ammonia balance constraint is as follows: (12) (13) In the formula, For the first Heavenly Hourly ammonia demand For the first Heavenly The hourly ammonia production rate of the synthesis tower For the first Heavenly The amount of ammonia stored and released in the ammonia storage tank per hour; The specific capacity constraints for the external transmission channels are as follows: (14) In the formula, This represents the maximum transmission capacity of the ultra-high voltage direct current transmission channel. The specific capacity constraints for hydrogen / ammonia pipelines are as follows: (15) (16) In the formula, and This represents the maximum transport capacity of hydrogen and ammonia pipelines. The specific constraints on equipment operation are as follows: The operating status of each piece of equipment must meet its technical parameter constraints, including: Electrolytic cell load rate constraint: The operating load of the electrolytic cell should be between 20% and 110% of the rated capacity; Synthesis tower load rate constraint: The operating load of the synthesis tower should be between 30% and 110% of its rated capacity; Energy storage SOC constraint: The state of charge of electrical energy storage, hydrogen storage, and ammonia storage should be within the safe operating range; Ramp-up rate constraint: The power adjustment rate of each device should meet the technical specifications.

[0016] Preferably, the hybrid optimization algorithm in S500 is a simulated annealing particle swarm optimization algorithm. When using the simulated annealing particle swarm optimization algorithm for optimization, the fitness function is specifically as follows: (17) in, For the fitness function value, Based on the objective function, the corresponding terminal comprehensive unit energy cost in formula (7) is... The sum of the equality constraint penalty terms. The sum of the inequality constraint penalty terms. The weights are for the equality constraint penalties. The penalty weights are for inequality constraints; The penalty item is defined as: (18) (19) in For the first The penalties for violating the equality constraints include penalties for real-time power balance constraints, hydrogen balance constraints, and ammonia balance constraints. The penalty index is the equality constraint. For the first Penalty weights for each equality constraint, For the first The penalties for violating the inequality constraints include penalties for the capacity constraints of the external transmission channel, hydrogen pipeline, ammonia pipeline, electrolyzer load rate, synthesis tower load rate, energy storage SOC, and ramp rate. The inequality constraint penalty index is... For the first Penalty weights for each inequality constraint, , >0.

[0017] An optimization configuration device for an integrated green electricity, hydrogen, and ammonia transmission system, comprising the steps of an optimization configuration method for an integrated green electricity, hydrogen, and ammonia transmission system, including: The basic data acquisition module is used to acquire basic data of the green electricity-hydrogen-ammonia integrated transmission base. The basic data includes wind and solar resource time-series characteristic data, unit investment and operation and maintenance costs of each piece of equipment, operating parameters of each piece of equipment, and transmission channel parameters. The optimization variable setting module is used to set optimization variables and their range of variation. Optimization variables are used to characterize the scale of the devices to be configured in the system. The cost calculation model building module is used to build a cost calculation model with the optimization objective of minimizing the comprehensive energy consumption cost of the terminal based on the unit investment and operation and maintenance costs and operating parameters of each equipment in the basic data. The constraint set establishment module is used to establish a set of multi-energy flow coupling constraints based on the time-series characteristic data of wind and solar resources, the operating parameters of each device, and the parameters of the transmission channel in the basic data. The constraints are used to ensure the supply and demand balance of electricity, hydrogen and ammonia in the system and the safe operation of the equipment. The optimal configuration scheme determination module is used to solve the cost calculation model using a hybrid optimization algorithm. Under the premise of substituting basic data and satisfying the set of multi-energy flow coupling constraints, it obtains the optimal solution of the optimization variables that makes the overall energy cost of the terminal approach the global optimum, thereby determining the optimal configuration scheme of each device in the system.

[0018] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of an optimized configuration method for an integrated green electricity, hydrogen, and ammonia delivery system.

[0019] The method of this invention can flexibly adapt to the characteristics of wind and solar resources in different regions, different end-user energy demand structures, and different hydrogen and ammonia market price environments. By adjusting the cost model and constraint parameters, the optimal configuration scheme adapted to different scenarios can be generated, providing a scientific basis for investment decisions.

[0020] This invention overcomes the limitations of existing technologies that only address power configuration for single power transmission scenarios. It treats green electricity production, on-site hydrogen and ammonia production, power transmission, ammonia energy transmission, and end-use as a unified system for capacity planning. By constructing a cost calculation model aimed at minimizing the overall end-use energy cost and establishing multi-energy flow coupling constraints, combined with a hybrid optimization algorithm, it achieves coordinated optimization of wind power, photovoltaics, energy storage, hydrogen production, synthetic ammonia, hydrogen storage, ammonia storage, and the scale of transmission channels. This method effectively solves the problem of new energy consumption, significantly reducing the overall end-use energy cost while meeting the supply and demand balance of electricity, hydrogen, and ammonia and ensuring safe equipment operation. Furthermore, in multi-variable, strongly coupled, and high-dimensional optimization scenarios, the hybrid optimization algorithm exhibits high computational performance, quickly converging to the global optimum. This provides a scientific and efficient decision-making basis for the planning and construction of integrated green electricity, hydrogen, and ammonia transmission systems in large-scale wind and solar power bases, maximizing the green value of energy bases. Attached Figure Description

[0021] Figure 1 This is a flowchart of an optimized configuration method for an integrated green electricity, hydrogen, and ammonia delivery system according to an embodiment of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0023] In this embodiment, the integrated green electricity-hydrogen-ammonia power transmission system consists of three coupled parts, with each network interconnected through three energy flow forms: electricity, hydrogen, and ammonia. Power transmission network: including wind farms, photovoltaic power stations, electrochemical energy storage devices, ultra-high voltage direct current transmission lines and converter station equipment, used to transmit green electricity to load centers; The hydrogen / ammonia energy transmission network includes electrolyzers, synthesis towers, hydrogen storage tanks, ammonia storage tanks, and hydrogen / ammonia pipeline equipment, which are used to convert unstable new energy sources into storable and transportable hydrogen / ammonia products. The end-use energy network includes end-use electrical loads, ammonia cracking hydrogen production units, and hydrogen / ammonia end-users, enabling the end-use of multiple energy forms such as electricity, hydrogen, and ammonia.

[0024] This method considers green electricity production, on-site hydrogen and ammonia production, electricity transmission, ammonia transmission, and end-use as a single electricity... hydrogen The ammonia multi-energy flow coupled overall system is used for unified capacity planning and collaborative operation optimization, rather than designing each component in isolation.

[0025] The overall process of the optimized configuration method in this embodiment is as follows: Figure 1 As shown.

[0026] (I) S100: Obtain basic data of the green electricity, hydrogen and ammonia integrated external transmission base. The basic data includes wind and solar resource time series characteristics data, unit investment and operation and maintenance costs of each equipment, operating parameters of each equipment, and external transmission channel parameters.

[0027] In one embodiment, the time-series characteristic data of wind and solar resources in S100 includes the output coefficients of wind power and photovoltaic power for 8760 hours per year; the unit investment and operation and maintenance costs of each piece of equipment include the unit investment cost and annual operation and maintenance cost coefficients of wind power, photovoltaic power, electrochemical energy storage, electrolyzer, synthesis tower, hydrogen storage, ammonia storage, ultra-high voltage direct current transmission, hydrogen pipeline, and ammonia pipeline; the operating parameters include the hydrogen production efficiency of the electrolyzer, the ammonia synthesis efficiency of the synthesis tower, the charge and discharge efficiency of the electrochemical energy storage, the charge and discharge efficiency of the hydrogen / ammonia storage, and the hydrogen production efficiency of ammonia cracking; the external transmission channel parameters include the ultra-high voltage direct current transmission capacity and transmission loss rate, the transmission capacity and pipeline cost of the hydrogen / ammonia pipeline, and the terminal demand scale for hydrogen and ammonia.

[0028] (ii) S200: Set the optimization variables and their range of variation. The optimization variables are used to characterize the scale of the equipment to be configured in the system.

[0029] In one embodiment, the optimization variables in S200 include wind power installed capacity, photovoltaic installed capacity, electrochemical energy storage capacity, electrolyzer capacity, synthesis tower capacity, hydrogen storage capacity, ammonia storage capacity, and hydrogen / ammonia pipeline scale. Among them, the wind power installed capacity is set within a range based on the wind and solar resource assessment results; the photovoltaic installed capacity is set within a range based on land resource constraints and solar energy resources; the electrochemical energy storage capacity is set within a range based on the fluctuation characteristics of new energy output and peak-shaving demand; the electrolyzer capacity is set within a range based on hydrogen production demand and new energy curtailment; the synthesis tower capacity is set within a range based on ammonia synthesis production demand and hydrogen supply capacity; the hydrogen storage capacity is set within a range based on hydrogen supply and demand balance and buffering demand; the ammonia storage capacity is set within a range based on ammonia product supply and demand balance and seasonal demand; the scale of ultra-high voltage direct current transmission lines is set within a range based on the amount of new energy power transmitted; and the scale of hydrogen transmission pipelines and ammonia transmission pipelines are set within a range based on the amount of hydrogen and ammonia products transmitted, respectively.

[0030] (III) S300: Based on the unit investment and operation and maintenance costs and operating parameters of each equipment in the basic data, construct a cost calculation model with the goal of minimizing the comprehensive energy cost of the terminal.

[0031] In one embodiment, the cost calculation model constructed in S300 specifically includes: The initial investment cost of the computing system includes investment in the power supply side, investment in hydrogen production and ammonia synthesis equipment, investment in ultra-high voltage direct current transmission, and investment in hydrogen and ammonia pipelines. The capital recovery factor is calculated based on the average social rate of return on capital and the total life cycle operating years of the green electricity-hydrogen-ammonia integrated project. The annual operation and maintenance cost of the system is calculated based on the scale of each piece of equipment and its operation and maintenance cost coefficient. The annual power transmission cost is calculated based on the annual external power volume, transmission loss rate, transmission price, and transmission cost per unit of power volume. Calculate the annual hydrogen / ammonia pipeline transportation cost based on the annual hydrogen / ammonia transport volume and unit transportation cost; Calculate the cost of hydrogen production from ammonia cracking at the terminal based on the terminal hydrogen demand and the unit hydrogen cracking cost. Based on the above costs, capital recovery coefficients, and energy revenues from electricity, hydrogen, and ammonia at the end, the comprehensive energy cost at the end is calculated.

[0032] In one embodiment, the initial investment cost is specifically: (1) In the formula, , , , , , , , , , These are the unit investment costs for wind power, photovoltaic power, electrochemical energy storage, electrolyzers, synthesis towers, hydrogen storage, ammonia storage, ultra-high voltage direct current transmission, hydrogen pipelines, and ammonia pipelines, respectively. , , , , , , , , , These are wind power installed capacity, photovoltaic installed capacity, electrochemical energy storage capacity, electrolyzer capacity, synthesis tower capacity, hydrogen storage capacity, ammonia storage capacity, ultra-high voltage direct current transmission line scale, hydrogen pipeline scale, and ammonia pipeline scale. The capital recovery factor is as follows: (2) In the formula, This is the capital recovery factor. The average rate of return on social capital. The total lifecycle operation period of the green electricity-hydrogen-ammonia integrated project; The annual operation and maintenance cost is calculated as follows: (3) In the formula, For the first Equipment size For the first The annual operation and maintenance cost coefficient for this type of equipment does not include ultra-high voltage direct current transmission and pipeline hydrogen / ammonia transportation; Calculate annual power transmission costs Specifically: (4) In the formula, For the annual electricity transmitted to other regions, The power transmission loss rate of ultra-high voltage direct current (UHVDC) For transmission price, Transmission cost per unit of electricity; Calculate the annual transportation costs of hydrogen and ammonia via pipelines. Specifically: (5) In the formula, Annual hydrogen transport volume For the unit cost of hydrogen transportation, This refers to the annual ammonia transport volume. Cost per unit of ammonia transport; Calculate the cost of hydrogen production from ammonia cracking at the terminal. Specifically: (6) In the formula, For end-user hydrogen demand, Cost per unit of hydrogen cracking; Calculate the comprehensive unit energy cost of the terminal Specifically: (7) In the formula, and This refers to the electrical equivalent values ​​of ammonia and hydrogen calculated based on their calorific value.

[0033] (iv) S400: Based on the time-series characteristic data of wind and solar resources in the basic data, the operating parameters of each device and the parameters of the external transmission channel, a set of multi-energy flow coupling constraints is established. The constraints are used to ensure the supply and demand balance of electricity, hydrogen and ammonia in the system and the safe operation of the equipment.

[0034] In one embodiment, the multi-energy flow coupling constraints established in S400 include: real-time power balance constraints, power balance constraints, hydrogen balance constraints, ammonia balance constraints, external transmission channel capacity constraints, hydrogen / ammonia pipeline capacity constraints, and equipment operation constraints. The specific real-time power balance constraints are as follows: (8) In the formula, For the first Heavenly Hourly power transmission load For the first Heavenly Hourly hydrogen production electrolyzer load size, For the first Heavenly Hourly load of ammonia synthesis tower For the first Heavenly Hourly wind power output coefficient For the first Heavenly Hourly photovoltaic power output coefficient For the first Heavenly Hourly energy storage charging and discharging status, For the first Heavenly Hourly energy storage charge and discharge power coefficient For the first Heavenly Hourly power curtailment; The specific power balance constraints are as follows: (9) (10) In the formula, The annual electricity consumption for producing synthetic ammonia The annual electricity consumption for producing synthetic ammonia Electricity storage consumes electricity. This represents the total amount of abandoned electricity. This refers to the annual equivalent full-load utilization hours of wind power. The equivalent full-load utilization hours of photovoltaic power per year; The hydrogen balance constraints are as follows: (11) In the formula, For the first Heavenly The hourly hydrogen consumption of the synthesis tower For the first Heavenly The hourly hydrogen production capacity of a hydrogen electrolyzer. For the first Heavenly The amount of hydrogen stored and released in the hydrogen storage tank per hour; The specific ammonia balance constraint is as follows: (12) (13) In the formula, For the first Heavenly Hourly ammonia demand For the first Heavenly The hourly ammonia production rate of the synthesis tower For the first Heavenly The amount of ammonia stored and released in the ammonia storage tank per hour; The specific capacity constraints for the external transmission channels are as follows: (14) In the formula, This represents the maximum transmission capacity of the ultra-high voltage direct current transmission channel. The specific capacity constraints for hydrogen / ammonia pipelines are as follows: (15) (16) In the formula, and This represents the maximum transport capacity of hydrogen and ammonia pipelines. The specific constraints on equipment operation are as follows: The operating status of each piece of equipment must meet its technical parameter constraints, including: Electrolytic cell load rate constraint: The operating load of the electrolytic cell should be between 20% and 110% of the rated capacity; Synthesis tower load rate constraint: The operating load of the synthesis tower should be between 30% and 110% of its rated capacity; Energy storage SOC constraint: The state of charge of electrical energy storage, hydrogen storage, and ammonia storage should be within the safe operating range; Ramp-up rate constraint: The power adjustment rate of each device should meet the technical specifications.

[0035] (v) S500: The cost calculation model is solved by using a hybrid optimization algorithm. Under the premise of substituting the basic data and satisfying the set of multi-energy flow coupling constraints, the optimal solution of the optimization variables that makes the overall energy cost of the terminal approach the global optimum is obtained, thereby determining the optimal configuration scheme of each device in the system.

[0036] Specifically, using the comprehensive unit energy cost at the terminal as the fitness function, a penalty function is introduced to handle constraint out-of-bounds issues, and a simulated annealing particle swarm optimization algorithm is used for iterative optimization: Initialize the particle swarm, where each particle represents a set of device capacity configuration schemes; Calculate the fitness value of each particle, i.e., the unit energy cost; A penalty term is introduced to penalize solutions that violate constraints, thus ensuring the feasibility of the solution; Simulated annealing is used to avoid local optima and improve global search capabilities. After reaching the maximum number of iterations, the system outputs the globally optimal configuration scheme that minimizes the overall energy cost of the terminal, including the optimal scale of wind power, photovoltaics, energy storage, electrolyzers, synthesis towers, hydrogen storage, ammonia storage, the proportion of external power transmission, and hydrogen / ammonia transmission pipelines.

[0037] In one embodiment, the hybrid optimization algorithm in S500 is a simulated annealing particle swarm optimization algorithm. When using the simulated annealing particle swarm optimization algorithm for optimization, the fitness function is specifically as follows: (17) in, For the fitness function value, Based on the objective function, the corresponding terminal comprehensive unit energy cost in formula (7) is... The sum of the equality constraint penalty terms. The sum of the inequality constraint penalty terms. The weights are for the equality constraint penalties. The penalty weights are for inequality constraints; The penalty item is defined as: (18) (19) in For the first The penalties for violating the equality constraints include penalties for real-time power balance constraints, hydrogen balance constraints, and ammonia balance constraints. The penalty index is the equality constraint. For the first Penalty weights for each equality constraint, For the first The penalties for violating the inequality constraints include penalties for the capacity constraints of the external transmission channel, hydrogen pipeline, ammonia pipeline, electrolyzer load rate, synthesis tower load rate, energy storage SOC, and ramp rate. The inequality constraint penalty index is... For the first Penalty weights for each inequality constraint, , >0.

[0038] This method breaks through the limitations of existing technologies that only configure power sources for a single power transmission scenario. It integrates and coordinates the modeling of multiple energy links, such as wind power, photovoltaics, energy storage, hydrogen production, hydrogen storage, ammonia synthesis, ammonia storage, power transmission, and ammonia transportation, to achieve unified and optimized configuration of "electricity-hydrogen-ammonia" multi-energy products. This enables more efficient absorption of unstable new energy sources and maximizes the green value of energy bases.

[0039] The following example illustrates this using a green electricity-hydrogen-ammonia integrated project in a certain region: A region plans to build a green electricity, hydrogen, and ammonia integrated transmission base. Based on the wind power and photovoltaic power output coefficients provided by the region, the annual equivalent full-load utilization hours of wind power and photovoltaic power are calculated to be 2850h and 2100h, respectively.

[0040] Based on the actual situation at the time, the unit investment construction cost, annual operation and maintenance cost, and end-user energy demand for wind power, photovoltaic, electric energy storage, hydrogen energy storage, hydrogen production electrolyzer, and synthesis tower equipment in the integrated green electricity-hydrogen-ammonia project are shown in Table 1 below: The optimized configuration system of this integrated green electricity, hydrogen, and ammonia transmission system uses unit energy cost as the fitness function. After reaching the maximum number of iterations, the final output of wind power scale, photovoltaic scale, energy storage scale, electrolyzer scale, hydrogen storage scale, synthesis tower scale, and ammonia storage scale is the optimal solution obtained in the simulated annealing intelligent algorithm, as shown in Table 2 below. In this example, there are 7 unknown elements to be optimized, saving more than 60% of the computation time compared to the traditional traversal algorithm.

[0041] The method described in this embodiment enables integrated and coordinated optimization of multiple stages, including green electricity generation, hydrogen production, ammonia production, energy storage, and power transmission. Compared to traditional single-configuration methods that only focus on power transmission, this approach significantly improves the utilization rate of new energy sources and reduces the overall energy cost at the end-user level. In multi-variable, strongly coupled, and high-dimensional scenarios, the computational efficiency is improved by more than 60% compared to traditional traversal algorithms, providing a scientific and efficient capacity configuration basis for integrated green electricity, hydrogen, and ammonia transmission systems in large-scale wind and solar power bases.

[0042] In one embodiment, an optimized configuration device for an integrated green electricity-hydrogen-ammonia transmission system is also provided, for performing the steps of an optimized configuration method for an integrated green electricity-hydrogen-ammonia transmission system, including: The basic data acquisition module is used to acquire basic data of the green electricity-hydrogen-ammonia integrated transmission base. The basic data includes wind and solar resource time-series characteristic data, unit investment and operation and maintenance costs of each piece of equipment, operating parameters of each piece of equipment, and transmission channel parameters. The optimization variable setting module is used to set optimization variables and their range of variation. Optimization variables are used to characterize the scale of the devices to be configured in the system. The cost calculation model building module is used to build a cost calculation model with the optimization objective of minimizing the comprehensive energy consumption cost of the terminal based on the unit investment and operation and maintenance costs and operating parameters of each equipment in the basic data. The constraint set establishment module is used to establish a set of multi-energy flow coupling constraints based on the time-series characteristic data of wind and solar resources, the operating parameters of each device, and the parameters of the transmission channel in the basic data. The constraints are used to ensure the supply and demand balance of electricity, hydrogen and ammonia in the system and the safe operation of the equipment. The optimal configuration scheme determination module is used to solve the cost calculation model using a hybrid optimization algorithm. Under the premise of substituting basic data and satisfying the set of multi-energy flow coupling constraints, it obtains the optimal solution of the optimization variables that makes the overall energy cost of the terminal approach the global optimum, thereby determining the optimal configuration scheme of each device in the system.

[0043] Specific limitations regarding the optimized configuration device for an integrated green electricity, hydrogen, and ammonia transmission system can be found in the above-described limitations regarding the optimized configuration method for such a system, and will not be repeated here. Each module in the aforementioned optimized configuration device for an integrated green electricity, hydrogen, and ammonia transmission system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0044] In one embodiment, a computer device is also provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of an optimized configuration method for an integrated green electricity, hydrogen, and ammonia delivery system.

[0045] In one embodiment, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the steps of an optimized configuration method for an integrated green electricity, hydrogen, and ammonia delivery system.

[0046] 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, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0047] The above provides a detailed description of the optimized configuration method and apparatus for an integrated green electricity, hydrogen, and ammonia delivery system provided by this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the core ideas of this invention. It should be noted that those skilled in the art can make various improvements and modifications to this invention without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this invention.

Claims

1. An optimized configuration method for an integrated green electricity, hydrogen, and ammonia transmission system, characterized in that, Taking the system encompassing green electricity production, on-site hydrogen and ammonia production, power and hydrogen / ammonia transmission, and end-user consumption as a unified optimization target, overall capacity coordination planning is carried out, including the following steps: S100: Obtain basic data for the integrated green electricity, hydrogen, and ammonia transmission base. The basic data includes wind and solar resource time-series characteristics data, unit investment and operation and maintenance costs of each piece of equipment, operating parameters of each piece of equipment, and transmission channel parameters. S200: Set the optimization variables and their range of variation. The optimization variables are used to characterize the scale of the devices to be configured in the system. S300: Based on the unit investment and maintenance costs and operating parameters of each device in the basic data, a cost calculation model is constructed with the goal of minimizing the comprehensive energy cost of the terminal. S400: Based on the time-series characteristic data of wind and solar resources in the basic data, the operating parameters of each device and the parameters of the external transmission channel, a set of multi-energy flow coupling constraints is established. The constraints are used to ensure the supply and demand balance of electricity, hydrogen and ammonia in the system and the safe operation of the equipment. S500: The cost calculation model is solved by a hybrid optimization algorithm. Under the premise of substituting the basic data and satisfying the set of multi-energy flow coupling constraints, the optimal solution of the optimization variables that makes the overall energy cost of the terminal approach the global optimum is obtained, thereby determining the optimal configuration scheme of each device in the system.

2. The method according to claim 1, characterized in that, The overall system comprises an electricity transmission network, a hydrogen / ammonia energy transmission network, and an end-user energy network. These networks are interconnected through the coupling of electricity, hydrogen, and ammonia energy flows, forming a unified green electricity-hydrogen-ammonia integrated transmission system. The power transmission network includes wind farms, photovoltaic power stations, electrochemical energy storage devices, ultra-high voltage direct current transmission lines and converter station equipment, which are used to transmit green electricity to load centers; The hydrogen / ammonia energy transmission network includes electrolyzers, synthesis towers, hydrogen storage tanks, ammonia storage tanks, and hydrogen / ammonia pipeline equipment, which are used to convert unstable new energy sources into storable and transportable hydrogen / ammonia products. The end-use energy network includes end-use electrical loads, ammonia cracking hydrogen production units, and hydrogen / ammonia end-users, enabling the end-use of multiple energy forms such as electricity, hydrogen, and ammonia.

3. The method according to claim 2, characterized in that, The S100 data on the time-series characteristics of wind and solar resources includes the output coefficients of wind power and photovoltaics for 8760 hours per year; the unit investment and operation and maintenance costs of each piece of equipment include the unit investment costs and annual operation and maintenance cost coefficients of wind power, photovoltaics, electrochemical energy storage, electrolyzers, synthesis towers, hydrogen storage, ammonia storage, UHVDC transmission, hydrogen pipelines, and ammonia pipelines; the operating parameters include the hydrogen production efficiency of electrolyzers, the ammonia synthesis efficiency of synthesis towers, the charge and discharge efficiency of electrochemical energy storage, the charge and discharge efficiency of hydrogen / ammonia storage, and the hydrogen production efficiency of ammonia cracking; the parameters of the external transmission channels include the capacity and transmission loss rate of UHVDC transmission, the transmission capacity and pipeline cost of hydrogen / ammonia pipelines, and the scale of terminal demand for hydrogen and ammonia.

4. The method according to claim 3, characterized in that, The optimization variables in S200 include wind power installed capacity, photovoltaic installed capacity, electrochemical energy storage capacity, electrolyzer capacity, synthesis tower capacity, hydrogen storage capacity, ammonia storage capacity, external power transmission ratio, and hydrogen / ammonia pipeline scale. Among them, the wind power installed capacity is set with a range of variation based on the wind and solar resource assessment results; the photovoltaic installed capacity is set with a range of variation based on land resource constraints and solar energy resources; the electrochemical energy storage capacity is set with a range of variation based on the fluctuation characteristics of new energy output and peak-shaving demand; the electrolyzer capacity is set with a range of variation based on hydrogen production demand and new energy curtailment; the synthesis tower capacity is set with a range of variation based on the synthetic ammonia production demand and hydrogen supply capacity; the hydrogen storage capacity is set with a range of variation based on hydrogen supply and demand balance and buffer demand; the ammonia storage capacity is set with a range of variation based on ammonia product supply and demand balance and seasonal demand; the scale of UHVDC transmission lines is set with a range of variation based on the amount of new energy power transmitted externally; and the scale of hydrogen and ammonia pipelines are set with ranges of variation based on the amount of hydrogen and ammonia products transmitted externally, respectively.

5. The method according to claim 4, characterized in that, The cost calculation model constructed in S300 specifically includes: The initial investment cost of the computing system includes investment in the power supply side, investment in hydrogen production and ammonia synthesis equipment, investment in ultra-high voltage direct current transmission, and investment in hydrogen and ammonia pipelines. The capital recovery factor is calculated based on the average social rate of return on capital and the total life cycle operating years of the green electricity-hydrogen-ammonia integrated project. The annual operation and maintenance cost of the system is calculated based on the scale of each piece of equipment and its operation and maintenance cost coefficient. The annual power transmission cost is calculated based on the annual external power volume, transmission loss rate, transmission price, and transmission cost per unit of power volume. Calculate the annual hydrogen / ammonia pipeline transportation cost based on the annual hydrogen / ammonia transport volume and unit transportation cost; Calculate the cost of hydrogen production from ammonia cracking at the terminal based on the terminal hydrogen demand and the unit hydrogen cracking cost. Based on the above costs, capital recovery costs, and energy revenue from electricity, hydrogen, and ammonia at the end, the comprehensive energy cost at the end is calculated.

6. The method according to claim 5, characterized in that, The initial investment cost is as follows: （1） In the formula, , , , , , , , , , These are the unit investment costs for wind power, photovoltaic power, electrochemical energy storage, electrolyzers, synthesis towers, hydrogen storage, ammonia storage, ultra-high voltage direct current transmission, hydrogen pipelines, and ammonia pipelines, respectively. , , , , , , , , , These are wind power installed capacity, photovoltaic installed capacity, electrochemical energy storage capacity, electrolyzer capacity, synthesis tower capacity, hydrogen storage capacity, ammonia storage capacity, ultra-high voltage direct current transmission line scale, hydrogen pipeline scale, and ammonia pipeline scale. The capital recovery factor is as follows: （2） In the formula, This is the capital recovery factor. The average rate of return on social capital. The total lifecycle operation period of the green electricity-hydrogen-ammonia integrated project; The annual operation and maintenance cost is calculated as follows: （3） In the formula, For the first Equipment size For the first The annual operation and maintenance cost coefficient for this type of equipment does not include ultra-high voltage direct current transmission and pipeline hydrogen / ammonia transportation; Calculate annual power transmission costs Specifically: （4） In the formula, For the annual electricity transmitted to other regions, The power transmission loss rate of ultra-high voltage direct current (UHVDC) For transmission price, Transmission cost per unit of electricity; Calculate the annual transportation costs of hydrogen and ammonia via pipelines. Specifically: （5） In the formula, Annual hydrogen transport volume For the unit cost of hydrogen transportation, This refers to the annual ammonia transport volume. Cost per unit of ammonia transport; Calculate the cost of hydrogen production from ammonia cracking at the terminal. Specifically: （6） In the formula, For end-user hydrogen demand, Cost per unit of hydrogen cracking; Calculate the comprehensive unit energy cost of the terminal Specifically: （7） In the formula, and This refers to the electrical equivalent values ​​of ammonia and hydrogen calculated based on their calorific value.

7. The method according to claim 6, characterized in that, The multi-energy flow coupling constraints established in S400 include: real-time power balance constraints, power balance constraints, hydrogen balance constraints, ammonia balance constraints, external transmission channel capacity constraints, hydrogen / ammonia pipeline capacity constraints, and equipment operation constraints. The specific real-time power balance constraints are as follows: （8） In the formula, For the first Heavenly Hourly power transmission load For the first Heavenly Hourly hydrogen production electrolyzer load size, For the first Heavenly Hourly load of ammonia synthesis tower For the first Heavenly Hourly wind power output coefficient For the first Heavenly Hourly photovoltaic power output coefficient For the first Heavenly Hourly energy storage charging and discharging status, For the first Heavenly Hourly energy storage charge and discharge power coefficient For the first Heavenly Hourly power curtailment; The specific power balance constraints are as follows: （9） (10) In the formula, The annual electricity consumption for producing synthetic ammonia The annual electricity consumption for producing synthetic hydrogen, Electricity storage consumes electricity. This represents the total amount of abandoned electricity. This refers to the annual equivalent full-load utilization hours of wind power. The equivalent full-load utilization hours of photovoltaic power per year; The hydrogen balance constraints are as follows: (11) In the formula, For the first Heavenly The hourly hydrogen consumption of the synthesis tower For the first Heavenly The hourly hydrogen production capacity of a hydrogen electrolyzer. For the first Heavenly The amount of hydrogen stored and released in the hydrogen storage tank per hour; The specific ammonia balance constraint is as follows: (12) (13) In the formula, For the first Heavenly Hourly ammonia demand For the first Heavenly The hourly ammonia production rate of the synthesis tower For the first Heavenly The amount of ammonia stored and released in the ammonia storage tank per hour; The specific capacity constraints for the external transmission channels are as follows: (14) In the formula, This represents the maximum transmission capacity of the ultra-high voltage direct current transmission channel. The specific capacity constraints for hydrogen / ammonia pipelines are as follows: (15) (16) In the formula, and This represents the maximum transport capacity of hydrogen and ammonia pipelines. The specific constraints on equipment operation are as follows: The operating status of each piece of equipment must meet its technical parameter constraints, including: Electrolytic cell load rate constraint: The operating load of the electrolytic cell should be between 20% and 110% of the rated capacity; Synthesis tower load rate constraint: The operating load of the synthesis tower should be between 30% and 110% of its rated capacity; Energy storage SOC constraint: The state of charge of electrical energy storage, hydrogen storage, and ammonia storage should be within the safe operating range; Ramp-up rate constraint: The power adjustment rate of each device should meet the technical specifications.

8. The method according to claim 1, characterized in that, The hybrid optimization algorithm in S500 is the simulated annealing particle swarm optimization algorithm. When using the simulated annealing particle swarm optimization algorithm for optimization, the fitness function is as follows: (17) in, For the fitness function value, Based on the objective function, the corresponding terminal comprehensive unit energy cost in formula (7) is... The sum of the equality constraint penalty terms. The sum of the inequality constraint penalty terms. The weights are for the equality constraint penalties. The penalty weights are for inequality constraints; The penalty item is defined as: (18) (19) in For the first The penalties for violating the equality constraints include penalties for real-time power balance constraints, hydrogen balance constraints, and ammonia balance constraints. The penalty index is the equality constraint. For the first Penalty weights for each equality constraint, For the first The penalties for violating the inequality constraints include penalties for the capacity constraints of the external transmission channel, hydrogen pipeline, ammonia pipeline, electrolyzer load rate, synthesis tower load rate, energy storage SOC, and ramp rate. The inequality constraint penalty index is... For the first Penalty weights for each inequality constraint, , >

0.

9. An optimized configuration device for an integrated green electricity, hydrogen, and ammonia delivery system, used to perform the steps of the method as described in any one of claims 1-8, characterized in that, include: The basic data acquisition module is used to acquire basic data of the green electricity-hydrogen-ammonia integrated transmission base. The basic data includes wind and solar resource time-series characteristic data, unit investment and operation and maintenance costs of each piece of equipment, operating parameters of each piece of equipment, and transmission channel parameters. The optimization variable setting module is used to set optimization variables and their range of variation. Optimization variables are used to characterize the scale of the devices to be configured in the system. The cost calculation model building module is used to build a cost calculation model with the optimization objective of minimizing the comprehensive energy consumption cost of the terminal based on the unit investment and operation and maintenance costs and operating parameters of each equipment in the basic data. The constraint set establishment module is used to establish a set of multi-energy flow coupling constraints based on the time-series characteristic data of wind and solar resources, the operating parameters of each device, and the parameters of the transmission channel in the basic data. The constraints are used to ensure the supply and demand balance of electricity, hydrogen and ammonia in the system and the safe operation of the equipment. The optimal configuration scheme determination module is used to solve the cost calculation model using a hybrid optimization algorithm. Under the premise of substituting basic data and satisfying the set of multi-energy flow coupling constraints, it obtains the optimal solution of the optimization variables that makes the overall energy cost of the terminal approach the global optimum, thereby determining the optimal configuration scheme of each device in the system.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

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