A planning and configuration optimization method for electric-hydrogen cooperative system based on LBBD algorithm

Abstract

The present invention relates to the technical field of integrated energy system planning and optimization, and discloses a method for planning and configuring an electric-hydrogen coordinated system based on the LBBD algorithm. First, data is collected to determine the basic operating parameters of the electric-hydrogen coordinated system; then, an electric-hydrogen coordinated planning model is established: based on the electric-hydrogen coordinated planning model, the objective function of the joint planning is constructed with the minimum investment cost and operating cost of the electric-hydrogen coordinated system at all stages and the maximum ammonia sales as the optimization goals; finally, the electric-hydrogen coordinated planning model is solved using the LBBD algorithm to obtain the site selection and capacity configuration of the hydrogen production station, energy storage station, and hydrogen storage station of the electric-hydrogen coordinated system, as well as the connection topology of the transmission line and the hydrogen transmission pipeline network. The present invention constructs an electric-hydrogen coordinated planning model, comprehensively considers the coordinated optimization of the electric-hydrogen system, avoids waste of resources, can fully improve the asset utilization efficiency of various resources, and has high accuracy and fast solution speed.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy system planning and optimization, and specifically to an electric-hydrogen collaborative system planning and configuration optimization method based on an LBBD (Logic-Based Benders Decomposition) algorithm. Background Art

[0002] Hydrogen energy has become a key direction for global energy transformation due to its high energy density, zero carbon emissions and long-term storage characteristics. Green electricity hydrogen production technology converts renewable energy (such as wind power and photovoltaics) into hydrogen through water electrolysis, which can not only greatly improve the clean energy consumption capacity, but also alleviate the problem of wind and light abandonment caused by the volatility of renewable energy. However, the current planning and design of green electricity hydrogen production systems face multiple technical bottlenecks: in terms of system synergy, electricity and hydrogen energy systems are often planned independently, resulting in an imbalance in equipment capacity configuration; at the same time, hydrogen storage facilities and energy storage battery capacity lack dynamic collaborative scheduling strategies, making it difficult to cope with multi-time scale supply and demand fluctuations, further exacerbating the low efficiency of system operation. In the study of electricity-hydrogen collaborative planning and configuration optimization, due to the large number of integer variables in the entire system and the existence of nonlinear constraints such as second-order cones, the solution time is long, the accuracy is low, and it is easy to not converge. The existing heuristic algorithms not only have a long solution time but also have the problem of being easily trapped in local optimality during the solution process. In summary, it is difficult to achieve efficient economic planning of the electric-hydrogen synergistic system with existing technologies. There is an urgent need for an innovative method that deeply integrates electricity and hydrogen energy systems and takes into account multi-time scale collaborative optimization and rapid solution to support large-scale hydrogen energy applications. Summary of the invention

[0003] In view of the above problems, the purpose of the present invention is to provide a method for planning and optimizing the configuration of an electric-hydrogen collaborative system based on the LBBD algorithm. By constructing an electric-hydrogen collaborative planning model and comprehensively considering the collaborative optimization of the electric-hydrogen system, it avoids resource waste, can fully improve the asset utilization efficiency of various resources, and has high accuracy and fast solution speed. The technical solution is as follows:

[0004] A method for planning and optimizing the configuration of an electric-hydrogen cooperative system based on an LBBD algorithm comprises the following steps:

[0005] Step S1: data collection to determine the basic operating parameters of the electric-hydrogen synergistic system;

[0006] Step S2: Establish an electricity-hydrogen collaborative planning model: including a hydrogen production station operation model, a hydrogen storage station operation model, an energy storage station operation model, an ammonia production station operation model, a transmission line planning model, and a hydrogen transmission pipeline planning model; and establish upper and lower limit constraints on the output of power generation equipment, electricity load balance constraints, and hydrogen load balance constraints for the electricity-hydrogen collaborative system at each moment;

[0007] Step S3: Based on the electricity-hydrogen collaborative planning model, the objective function of the joint planning is constructed with the minimum investment cost and operation cost of the electricity-hydrogen collaborative system at all stages and the maximum ammonia sales as the optimization goals;

[0008] Step S4: Use the LBBD algorithm to solve the electricity-hydrogen collaborative planning model to obtain the types and connection topologies of hydrogen pipelines and transmission lines planned and configured for the electricity-hydrogen collaborative system, as well as the node locations and capacities of hydrogen production stations, energy storage stations, and hydrogen storage stations.

[0009] The beneficial effects of the present invention are:

[0010] 1) The present invention constructs an electric-hydrogen collaborative planning model, comprehensively considers the collaborative optimization of the electric-hydrogen system, avoids resource waste, and can fully improve the asset utilization efficiency of various resources;

[0011] 2) The present invention decomposes the electric-hydrogen collaborative planning model into a main problem and sub-problems by introducing a logic-based benders decomposition algorithm, placing complex variables in the main problem and relatively complex variables in the sub-problems, and interacting between the main and sub-problems through feasible cut sets and optimal cut sets, thereby effectively reducing the complexity of the model, achieving higher accuracy and faster solution speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a structural flow chart of the electric-hydrogen collaborative planning model of an embodiment of the present invention.

[0013] Figure 2 It is a flow chart of the electric-hydrogen coordinated system planning and configuration optimization method according to an embodiment of the present invention.

[0014] Figure 3 Schematic diagram of the Logic-based Benders decomposition algorithm according to an embodiment of the present invention.

[0015] Figure 4 A schematic diagram of the connection topology of the electric-hydrogen collaborative planning results according to an embodiment of the present invention.

[0016] Figure 5 Schematic diagram of hydrogen flow scheduling planning in a pipeline network according to an embodiment of the present invention.

[0017] Figure 6 Schematic diagram of the pipeline inventory in a quasi-steady state of a hydrogen transmission pipeline in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] like Figure 2In the implementation case shown, we can see a method for electric-hydrogen collaborative planning based on the Logic-based Benders decomposition algorithm, and its operation process is as follows:

[0020] The planning method of the present invention takes into account the electric hydrogen joint planning of hydrogen production, storage, transmission and ammonia synthesis, which includes hydrogen production, transmission, storage and use. The hydrogen production stage uses electrolyzers, the hydrogen transmission stage uses hydrogen transmission pipelines, the hydrogen storage stage uses hydrogen storage tanks, and the hydrogen use stage is industrial ammonia synthesis. The hydrogen production stage is located in the chemical park, and the power supply node for hydrogen production needs to be planned. Both the hydrogen production and hydrogen use sides are equipped with hydrogen buffer tanks, such as Figure 1 As shown. For the node information in any given area, including power generation nodes, candidate hydrogen production nodes, hydrogen storage nodes, energy storage nodes, the number of candidate transmission lines and the number of hydrogen pipelines, there are 9 nodes in total. Through the joint planning of electricity and hydrogen, the total cost of power grid lines, hydrogen network pipelines, hydrogen storage tanks, energy storage investment and operation and maintenance can be minimized while satisfying the material balance of hydrogen load and the power balance of power supply nodes. The electricity used for hydrogen production by electrolysis of water mainly adopts green electricity, with a certain capacity of thermal power, and the total amount of hydrogen used is used for ammonia production. The time planning scale is hours, which is 168 hours per week. Through the joint planning of electricity and hydrogen, the installed capacity of electrolyzers of N hydrogen production nodes and the capacity of hydrogen storage tanks of hydrogen production nodes, power supply line planning (there are 3 types of lines in this implementation case, with unit impedances of 0.0002 / km, 0.0003 / km, and 0.0004 / km, respectively), hydrogen pipelines (there are 3 types of pipelines in this implementation case, with diameters of 200mm, 600mm, and 800mm, respectively), N x The hydrogen storage tank capacity on the hydrogen load side and the daily hydrogen transportation scheduling plan.

[0021] The electric-hydrogen cooperative system planning and configuration optimization method based on the Logic-Based Benders decomposition algorithm of the present invention is as follows: Figure 2 As shown in the figure, the deep synergy between electricity and hydrogen energy systems is achieved through a hierarchical optimization framework, which includes the following steps:

[0022] Step S1: Data collection to determine the basic operating parameters of the electric-hydrogen synergistic system.

[0023] Step S2: Establish a planning model for the electric-hydrogen coordinated system: including the hydrogen production station operation model, the energy storage station operation model, the hydrogen storage station operation model, the ammonia production station operation model, the transmission line planning model, and the hydrogen transmission pipeline planning model; as well as comprehensive constraints such as the electric load balance, hydrogen load balance, and upper and lower limits of the power generation equipment output of the electric-hydrogen coordinated system at each moment.

[0024] Step S3: Hydrogen production station operation model. This includes the constraints on the number of candidate hydrogen production stations and operation constraints. For any i-th hydrogen production node, its dynamic operation power upper and lower limits must be met:

[0025] ;

[0026] In the formula, node e is the candidate node of the hydrogen production station and belongs to the candidate node set of the hydrogen production station , and are the minimum and maximum number of candidate hydrogen production stations, Indicates the decision variable of whether node e should build a hydrogen production station, is the hydrogen production power of the hydrogen production station built at node e at time t; is the variable of the operating hydrogen production station, indicating the start and stop status of the hydrogen production station built at node e at time t; Indicates the number of hydrogen generators in the hydrogen production station, is the hydrogen production capacity of the hydrogen production station built at node e at time t; is the minimum power consumed by the hydrogen production station when producing hydrogen; T is the time step.

[0027] The hydrogen production flow rate of the hydrogen production station meets the following constraints:

[0028] ;

[0029] In the formula, The minimum adjustment coefficient of the operating power of the hydrogen production station; is the capacity of the hydrogen production station; is the maximum capacity of the hydrogen production station.

[0030] Step S4: Hydrogen storage station operation model. The planned number of hydrogen storage stations; the daily balance of hydrogen production and use; the hydrogen storage tank needs to meet the material balance under continuous storage and long-term scales; the hydrogen storage links on the hydrogen production side and the hydrogen use side must meet the following constraints:

[0031] ;

[0032] In the formula, node h is the candidate node of the hydrogen storage station and belongs to the candidate node set of the hydrogen storage station ; is the decision variable of the hydrogen storage station, indicating whether node h will build a hydrogen storage station; represents the capacity of the planned hydrogen storage station, i.e., the continuous variable of the hydrogen storage station; Indicates the hydrogen storage capacity of the hydrogen storage tank at time t; and They represent the amount of hydrogen flowing in and out of the hydrogen storage station built at node h at time t; and They represent the operating variables of the inflow and outflow of hydrogen at the hydrogen storage station built at node h at time t; and They represent the charging and discharging rate and the self-charging and discharging rate of hydrogen storage respectively; and are the minimum and maximum numbers of candidate hydrogen storage stations respectively; is the maximum capacity of the hydrogen storage station; is the maximum capacity of the hydrogen storage station.

[0033] Step S5: Energy storage station operation model. The planned number of energy storage stations; the energy storage station needs to meet the material balance under continuous storage and long-term scales; the charging and discharging links of energy storage must meet the following constraints:

[0034] ;

[0035] In the formula, node s is the candidate node of the energy storage station and belongs to the candidate node set of the energy storage station ; is the decision variable of the energy storage station, indicating whether node s builds an energy storage station; represents the planned capacity of the energy storage station, i.e., the continuous variable of the hydrogen storage station; Indicates the maximum capacity of the energy storage station; and They represent the charging and discharging flow of the energy storage station built at node s respectively; and They represent the charging and discharging operation decisions under the construction of the hydrogen storage station at node s; represents the flow energy of the sth energy storage station when it is operating at time t; and are the minimum and maximum numbers of candidate energy storage stations respectively.

[0036] Step S6: Run the ammonia production station model. As a downstream industry in the hydrogen supply chain, the ammonia production station needs to ensure a balance between hydrogen production and transportation as well as the operation constraints of ammonia production:

[0037] ;

[0038] In the formula, represents the hydrogen flow rate used in synthesizing ammonia at time t, Indicates the electrical power consumed by the synthetic ammonia plant when producing ammonia; is the synthetic ammonia capacity of the synthetic ammonia plant, , and Respectively represent the operation state, standby state and shutdown state of the ammonia production station, M is an arbitrarily large and non-infinite positive number, and in this embodiment, it is 100000; , , , and They are the power consumption coefficient of the synthetic ammonia station, the operation coefficient during synthetic ammonia, the maintenance coefficient during shutdown, and the upward and downward climbing rates of synthetic ammonia; It is the minimum coefficient of ammonia reserves when synthesizing ammonia.

[0039] Step S7: The transmission line planning model includes the planning of the number of transmission lines and the operation constraints of the transmission lines:

[0040] ;

[0041] In the formula, represents the node power of the power node in the power network at time t, represents the power flowing through line ij at time t, and They represent the upper and lower limits of the line flow power, respectively. It represents the unit impedance of the line under k types. There are three types of lines in this implementation case.

[0042] Step S8: Model the hydrogen transport link. The hydrogen transport link uses pipelines to transport hydrogen, considering the number constraints of pipelines and the constraints on the hydrogen inventory in the pipelines:

[0043] ;

[0044] In the formula, represents the flow rate of node u in the hydrogen pipeline at time t, represents the hydrogen flow rate transported by the pipeline from node u to node v, is a ternary decision variable, indicating whether the hydrogen pipeline type w from node u to node v is constructed; Indicates the type of hydrogen pipeline, that is, w types of hydrogen pipeline diameters; in this embodiment, there are three types of pipeline diameters; represents the length of the hydrogen pipeline from node u to node v, in kilometers; and Indicates the maximum and minimum values ​​of the pipeline flow. represents the pressure of pipeline node u at time t, is the pipeline inventory from node u to node v at time t in the hydrogen pipeline, and is the Weymouth characteristic parameter of the hydrogen pipeline; is the average flow rate of the pipe connecting node u and node v.

[0045] Step S9: Modeling of power nodes. The electricity used for hydrogen production and synthetic ammonia comes from renewable energy sources such as wind power and photovoltaic power generation, as well as a certain capacity of thermal power. Renewable energy penetration constraints Unit operation constraints and thermal power unit operation constraints. For any power generation node i, including photovoltaic power generation nodes, wind power generation nodes and thermal power, it is necessary to meet the following requirements:

[0046] ;

[0047] In the formula, is the output of the wind power node, is the output of the photovoltaic node, To support the output of thermal power units; , and They respectively represent the maximum output of wind power nodes, photovoltaic nodes and supporting thermal power units.

[0048] The thermal power units also need to meet the thermal power ramp constraints:

[0049] ;

[0050] In the formula, and They represent the maximum upward climbing rate and the minimum downward climbing rate of the thermal power unit respectively. is the output of the i-th thermal power unit at time t.

[0051] Step S10: The electric load balance constraint needs to satisfy the following relationship:

[0052] ;

[0053] In the formula, represents the power generation node power of node i at time t, Indicates the power consumption required for hydrogen production at the hydrogen production station. Indicates the charging and discharging power of the energy storage station during operation. Indicates the electricity consumed when synthesizing ammonia.

[0054] Step S11: The hydrogen load balance constraint needs to satisfy the following relationship:

[0055] ;

[0056] In the formula, represents the hydrogen production flow rate of the hydrogen production station at time t, Indicates the hydrogen flow rate of the hydrogen storage station. Indicates the hydrogen flow rate consumed in synthesizing ammonia, is the hydrogen flow rate flowing from node u to node v in the hydrogen pipeline at time t.

[0057] Step S12: Construct the objective function of joint planning, which includes the construction cost and operation and maintenance cost of hydrogen production station, energy storage station, hydrogen storage station, synthetic ammonia, lines and pipelines, and the revenue from ammonia sales. Therefore, based on the planning model of the electric-hydrogen synergistic system, the investment cost and operation cost of the electric-hydrogen synergistic system at all stages are minimized and the ammonia sales are maximized as the optimization goals, and the location and capacity of the system's hydrogen production station, energy storage station, and hydrogen storage station are determined; the type and selection of hydrogen pipelines and transmission lines are:

[0058] ;

[0059] ;

[0060] Where X is the set of decision variables and continuous variables of the model, the decision variables are integer variables, and the continuous variables are capacity planning; They are the decision variables of the line, the decision variables of the hydrogen transmission pipeline, the decision variables of the hydrogen production station, the decision variables and continuous variables of the hydrogen storage station, the construction variables and continuous variables of the energy storage station, and the continuous variables of synthetic ammonia; N is the node set, , , , , and They are the candidate node sets of candidate lines, pipelines, hydrogen production stations, hydrogen storage stations, energy storage stations and synthetic ammonia stations; , , , , and are the total costs of power grid transmission lines, hydrogen network pipelines, hydrogen production stations, energy storage stations, hydrogen storage stations and synthetic ammonia plants, and c represents the profit from selling ammonia. is the amortized cost conversion factor, where is the depreciation rate, n is the service life of the equipment, INV is the investment cost of the equipment, and operation and maintenance (O&M) is the operation and maintenance cost.

[0061] For the above objective function, since the electric-hydrogen collaborative planning model is a MIQCP (Mixed Integer Quadratically Constrained Program) model, which contains decision variables, constraints and objective functions, this problem is difficult to solve quickly and efficiently due to its numerous variables and complex constraints. In order to improve the speed of solving this problem, the model can be decomposed. Among the existing decomposition methods, Logic-based Benders decomposition is a technique for decomposing complex problems into simple sub-problems for solution. It can be used to solve optimization problems involving a large number of integer variables, and is particularly suitable for two-stage decision problems, in which the decision variables in the first stage are continuous variables, and the decision variables in the second stage can include discrete variables and continuous variables. The present invention also proposes a planning model based on a logic-based benders decomposition algorithm, including a problem reconstruction module, a cutting plane design module, and a main-subproblem iterative update module. The following are the specific steps for solving the electric-hydrogen collaborative planning model using Logic-based Benders decomposition:

[0062] (1) Define the main problem and subproblems: First, we need to clearly define the main problem and subproblems. The main problem includes decision variables, objective functions, and constraints; the subproblem is a subset of the main problem, including constraints and some more complex variables.

[0063] The main problem of this embodiment includes the construction variables and capacity planning of hydrogen production stations, hydrogen storage stations, energy storage stations, and synthetic ammonia stations, the construction variables of hydrogen network pipelines, and some related constraints. The sub-problem is a subset of the main problem, including the construction variables of transmission lines, the operation variables and constraints of hydrogen production stations, energy storage stations, hydrogen storage stations, and synthetic ammonia.

[0064] (2) Initialization of the problem: In order to start decomposition, it is necessary to initialize the main problem and subproblems. Set the variables of the main problem and subproblems to the same initial values, calculate the initial objective function value of the main problem, and initialize the upper bound UB and lower bound LB, respectively. and , initialize the number of iterations K and set the allowable error E.

[0065] (3) Solve the main problem: Use the initial variable values ​​to solve the main problem and obtain a set of topological solutions for hydrogen production stations, energy storage stations, hydrogen storage stations, and hydrogen transmission pipelines.

[0066] (4) Solve the subproblems: Use the current topology of the main problem to optimize the operation mode of the hydrogen production station, the operation mode of the synthetic ammonia station, the topology of the transmission line, and the scheduling strategy of charging and discharging in the subproblems. If there is at least one feasible solution that satisfies all the constraints in the subproblem, return the current solution and end the algorithm process. Otherwise, continue to execute the subproblem and use different algorithms and solutions to solve it.

[0067] (5) Construct Logic Benders cuts: For each subproblem, calculate a Logic Benders cut and add it to the constraints of the main problem. A Logic Benders cut is generally a linear inequality that constrains the solution to the main problem based on the solution to the subproblem. Adding a cut can help the main problem better approach the optimal solution. For this example, the following Logic Benders cuts can be constructed:

[0068] ;

[0069] In the formula, is an integer variable in the system, representing the selection of hydrogen production stations, hydrogen storage stations, energy storage stations, lines and pipelines; for formula A, and Represent sets of integer variables 0 and 1 respectively. Formula A is used to cut off the solution set that made the subproblem infeasible last time. For formula B: If a node selects a hydrogen production station, a hydrogen storage station, or ammonia synthesis, then at least one pipeline connected to it is selected, and the same applies to the line.

[0070] If the submodel is feasible, then , the following Logic benders cut is added to the main problem, namely formula C, where Represents a lower bound, which is the lower bound of the projection problem of the original problem on the subproblem. It is used to improve z The lower bound of Indicates that in a given The lower bound of time.

[0071] Main problem update and iteration: First, calculate the main problem, solve the main problem to get the solution X, and update the lower bound LB. Use the equipment capacity and pipeline selection scheme calculated by the main problem as input parameters to verify the sub-problem and input it into the sub-problem. If all constraints are met, it means that the current solution is feasible, record the total cost, and update the upper bound UB, otherwise generate a Logic Benders cut.

[0072] Finally, repeat steps (3) to (5), use the new constraints to solve the relaxed main problem again, and use the new solution to solve the subproblem. If the objective function value of the main problem has converged, the optimization can be stopped and the final solution can be returned. The above steps can be summarized as the algorithm structure as follows Figure 3 shown.

[0073] The operating environment of this embodiment is: operating system Windows 11, 64 bit, processor 12th Gen Intel (R) Core (TM) i7-11800H @ 2.30 GHz, memory 128.0 GB, software platform Pycharm, solver Gurobi 12.0.0.

[0074] The connection topology diagram of the electric-hydrogen collaborative planning result calculated by the embodiment of the present invention is as follows Figure 4 As shown, the final hydrogen production station is selected at node 4, node 5, node 6, and node 9, the synthetic ammonia station is planned at node 7, the hydrogen storage station is planned at node 7, and the energy storage station is planned at node 5. There are 4 hydrogen pipelines, which are from node 9 to node 4, node 4 to node 5, node 6 to node 5, and node 5 to node 7. The selected models are all type 2 (diameter 600mm), and all nodes are connected through the power network and hydrogen pipelines. The schematic diagram of the pipeline network hydrogen flow scheduling plan is as follows Figure 5 As shown in the figure, the schematic diagram of the hydrogen pipeline inventory under quasi-steady state is as follows Figure 6 shown.

Claims

1. A method for planning and optimizing the configuration of an electric-hydrogen cooperative system based on the LBBD algorithm, characterized in that: The following steps are involved: Step S1: data collection to determine the basic operating parameters of the electric-hydrogen synergistic system; Step S2: Establish an electricity-hydrogen collaborative planning model: including a hydrogen production station operation model, a hydrogen storage station operation model, an energy storage station operation model, an ammonia production station operation model, a transmission line planning model, and a hydrogen pipeline quasi-steady-state model; and establish upper and lower limit constraints on the output of power generation equipment, electricity load balance constraints, and hydrogen load balance constraints for the electricity-hydrogen collaborative system at each moment; Step S3: Based on the electricity-hydrogen collaborative planning model, the objective function of the joint planning is constructed with the minimum investment cost and operation cost of the electricity-hydrogen collaborative system at all stages and the maximum ammonia sales as the optimization goals; Step S4: using the LBBD algorithm to solve the electricity-hydrogen collaborative planning model, obtaining the site selection and capacity configuration of the hydrogen production station, energy storage station, and hydrogen storage station of the electricity-hydrogen collaborative system, as well as the connection topology of the power transmission line and the hydrogen transmission pipeline network; Step S2 specifically includes: Step S21: Establishing a hydrogen production station operation model; Including the constraints on the number of candidate hydrogen production stations and operation constraints, for nodes that serve as hydrogen production stations, their dynamic operating power upper and lower limits need to be met, as shown below: ； In the formula, node e is the candidate node of the hydrogen production station and belongs to the candidate node set of the hydrogen production station , and are the minimum and maximum number of candidate hydrogen production stations, Indicates the decision variable of whether node e should build a hydrogen production station, is the hydrogen production power of the hydrogen production station built at node e at time t; is the variable of the operating hydrogen production station, indicating the start and stop status of the hydrogen production station built at node e at time t; Indicates the number of hydrogen generators in the hydrogen production station, is the hydrogen production capacity of the hydrogen production station built at node e at time t; is the minimum power consumed by the hydrogen production station when producing hydrogen; T is the time step; The hydrogen production flow rate of the hydrogen production station meets the following constraints: ； In the formula, The minimum adjustment coefficient of the operating power of the hydrogen production station; is the capacity of the hydrogen production station; is the maximum capacity of the hydrogen production station; Step S22: Establishing a hydrogen storage station operation model; The candidate quantity constraints of hydrogen storage stations and the operation constraints of hydrogen storage equipment are as follows: ； In the formula, node h is the candidate node of the hydrogen storage station and belongs to the candidate node set of the hydrogen storage station ; is the decision variable of the hydrogen storage station, indicating whether node h will build a hydrogen storage station; represents the capacity of the planned hydrogen storage station, i.e., the continuous variable of the hydrogen storage station; Indicates the hydrogen storage capacity of the hydrogen storage tank at time t; and They represent the amount of hydrogen flowing in and out of the hydrogen storage station built at node h at time t; and They represent the operating variables of the inflow and outflow of hydrogen at the hydrogen storage station built at node h at time t; and They represent the charging and discharging rate and the self-charging and discharging rate of hydrogen storage respectively; and are the minimum and maximum numbers of candidate hydrogen storage stations respectively; is the maximum capacity of the hydrogen storage station; Step S23: Establishing an energy storage station operation model; the candidate quantity constraints and operation constraints of the energy storage station are as follows: ； In the formula, node s is the candidate node of the energy storage station and belongs to the candidate node set of the energy storage station ; is the decision variable of the energy storage station, indicating whether node s builds an energy storage station; represents the planned capacity of the energy storage station, i.e., the continuous variable of the hydrogen storage station; Indicates the maximum capacity of the energy storage station; and They represent the charging and discharging flow of the energy storage station built at node s respectively; and They represent the charging and discharging operation decisions under the construction of the hydrogen storage station at node s; represents the flow energy of the sth energy storage station when it is operating at time t; and are the minimum and maximum number of candidate energy storage stations respectively; Step S24: establishing an ammonia production station operation model; The balance between hydrogen production and transportation in the ammonia production station and the operating constraints are as follows: ； In the formula, represents the hydrogen flow rate used in synthesizing ammonia at time t, Indicates the electrical power consumed by the synthetic ammonia plant when producing ammonia; is the ammonia capacity of the ammonia plant, i.e., the continuous variable of the ammonia plant; , and They represent the operation, standby and shutdown states of the ammonia plant respectively. M is an arbitrarily large and non-infinite positive number. , , , and They are the power consumption coefficient of the synthetic ammonia station, the operation coefficient during synthetic ammonia, the maintenance coefficient during shutdown, and the upward and downward climbing rates of synthetic ammonia; is the minimum coefficient of ammonia reserves when synthesizing ammonia; Step S25: Establishing a transmission line planning model; The transmission line planning model includes the planning of the number of transmission lines and the operation constraints of transmission lines, as shown below: ； In the formula, represents the node power of the power node in the power network at time t, represents the power flowing through line ij at time t, and They represent the upper and lower limits of the line flow power, respectively. Indicates the unit impedance of the line under k types; and They are the node power angles of node i and node j in the transmission line at time t, ranging between between; and are the line impedance value and line length between node i and node j respectively, is a ternary decision variable, indicating that the line type of node i and node j is k. If line ij is selected and the line type is k, it is 1, otherwise it is 0; Step S26: establishing a quasi-steady-state model of the hydrogen transmission pipeline; The hydrogen pipeline planning model includes the constraints on the number of hydrogen pipelines and the hydrogen inventory in the hydrogen pipelines, as shown below: ； In the formula, represents the flow rate of node u in the hydrogen pipeline at time t, represents the hydrogen flow rate transported by the pipeline from node u to node v; is a ternary decision variable, indicating whether the hydrogen pipeline type w from node u to node v is constructed; represents the length of the hydrogen pipeline from node u to node v; Indicates the type of hydrogen pipeline, that is, the diameter of w types of hydrogen pipelines; and Indicates the maximum and minimum values ​​of the uv flow rate of the hydrogen pipeline; and They represent the pressures at nodes u and v in the hydrogen pipeline at time t, is the pipeline inventory from node u to node v in the hydrogen pipeline at time t; It represents the flow rate of hydrogen pipeline uv at time t, It represents the flow rate of hydrogen pipeline vu at time t; and are Weymouth characteristic parameters of the hydrogen pipeline; and are the upper and lower limits of the pressure at node u in the hydrogen pipeline; is a node set in the hydrogen pipeline; For Node u and nodes v Average flow rate of connected pipes; Step S27: Establishing upper and lower limit constraints on power generation equipment output; For any power generation node, including photovoltaic nodes, wind power nodes and thermal power units, the following conditions must be met: ； In the formula, is the output of the wind power node, is the output of the photovoltaic node, To support the output of thermal power units; , and Respectively represent the maximum output of wind power nodes, photovoltaic nodes and supporting thermal power units; The thermal power units also need to meet the thermal power ramp constraints: ； In the formula, and They represent the maximum upward climbing rate and the minimum downward climbing rate of the thermal power unit respectively. is the output of the thermal power unit at time t; is the time difference between the current moment and the previous moment; Step S28: establishing electric load balance constraints; The electrical load balance satisfies the following relationship: ； In the formula, represents the power of the power generation node at time t, Indicates the power consumption required for hydrogen production at the hydrogen production station. It represents the charging and discharging power of the energy storage station during operation at time t, represents the electricity consumed in synthesizing ammonia at time t; Step S29: establishing hydrogen load balance constraints; The hydrogen load balance satisfies the following relationship: ； In the formula, represents the hydrogen production flow rate of the hydrogen production station at time t, represents the hydrogen flow rate charged and discharged at the hydrogen storage station at time t, represents the hydrogen flow rate consumed in synthesizing ammonia at time t, is the hydrogen flow rate flowing from node u to node v in the hydrogen pipeline at time t; The objective function in step S3 includes the construction cost and operation and maintenance cost of the hydrogen production station, energy storage station, hydrogen storage station, synthetic ammonia, lines and pipelines, and the income from ammonia sales; the location and capacity of the system hydrogen production station, energy storage station, and hydrogen storage station are determined according to the objective function, and the type and selection of hydrogen pipelines and power transmission lines are determined; The objective function is expressed as follows: ； ； Where X is the set of decision variables and continuous variables of the model, the decision variables are integer variables, and the continuous variables are capacity planning; They are the decision variables of the line, the decision variables of the hydrogen transmission pipeline, the decision variables of the hydrogen production station, the decision variables and continuous variables of the hydrogen storage station, the construction variables and continuous variables of the energy storage station, and the continuous variables of synthetic ammonia; N is the node set, , , , , and They are the candidate node sets of power grid transmission lines, hydrogen network pipelines, hydrogen production stations, energy storage stations, hydrogen storage stations and synthetic ammonia plants; , , , , and They are the total costs of power grid transmission lines, hydrogen network pipelines, hydrogen production stations, energy storage stations, hydrogen storage stations and synthetic ammonia plants; A collection of types for power transmission lines and hydrogen pipelines; , , , , and They are the cost conversion coefficients for power grid transmission lines, hydrogen network pipelines, hydrogen production stations, energy storage stations, hydrogen storage stations and synthetic ammonia plants; , , , , , They are the equipment investment costs for power grid transmission lines, hydrogen network pipelines, hydrogen production stations, energy storage stations, hydrogen storage stations, and synthetic ammonia plants; and are the distances to the power transmission line and hydrogen pipeline, respectively; , , and They are the operation and maintenance costs of the hydrogen production station, energy storage station, hydrogen storage station and ammonia plant; and They are the power angle coefficient of the power transmission line and the pressure difference coefficient of the hydrogen transmission pipeline respectively; is the power angle of node i at the selected k type at time t, and are the inflow and outflow pressures of the hydrogen pipeline at node u, respectively; and They are the flow rate of hydrogen produced by the hydrogen production station and the flow rate of hydrogen required for ammonia production at the synthetic ammonia station; The amount of water required for hydrogen production; and They are the start-up and shutdown costs of the synthetic ammonia station; and They are the start and stop decision variables of the ammonia production station; is the price at which ammonia is sold; hour Indicates time.

2. The method for planning and optimizing the configuration of an electric-hydrogen coordinated system based on the LBBD algorithm according to claim 1, characterized in that: Step S4 specifically includes: Step S41: Define the main problem and sub-problems: The main problem includes the decision variables of the hydrogen production station, hydrogen storage station and energy storage station , capacity planning of hydrogen storage stations, energy storage stations and synthetic ammonia stations , the decision variables of the hydrogen pipeline , and related quantity constraints; the subproblem is a subset of the main problem, including the decision variables of the transmission line , operating variables and constraints of hydrogen production stations, energy storage stations, hydrogen storage stations and synthetic ammonia; Step S42: Initialize the problem: Decompose the model into a main problem and sub-problems according to its complexity. The complex decision variables, such as the site selection and capacity configuration of hydrogen production stations, energy storage stations, hydrogen storage stations, and synthetic ammonia stations, and the selection and type of hydrogen transmission pipelines, are classified as the main problem, and the operating variables, line selection and type of hydrogen production stations, energy storage stations, hydrogen storage stations, and synthetic ammonia stations are classified as sub-problems; set the variables of the main problem and the sub-problems to the same initial values, calculate and record the initial objective function value of the main problem, and initialize the upper bound UB and lower bound LB of the entire problem respectively. and , initialize the number of iterations K and set the allowable error E; Step S43: Solve the main problem: use the initial variables to solve the main problem; generate a feasible integer solution , namely the selection and capacity ratio candidate plans of hydrogen production stations, hydrogen storage stations, energy storage stations and pipelines; Step S44: Solve the subproblem: Use the currently feasible integer solution to the main problem It is passed into the subproblem as a parameter to check whether all the constraints of the subproblem are met, including the operation constraints of the hydrogen production station, energy storage station, hydrogen storage station and ammonia production station, and the quasi-steady-state model constraints of the hydrogen pipeline, and the objective function value of the subproblem is calculated as the upper bound UB of the entire problem; Step S45: constructing a Logic benders cut: for the information of the sub-problem, based on the nature of the sub-problem, construct a Logic benders cut, and add it to the constraint condition of the main problem; the Logic benders cut is a linear inequality, which constrains the solution of the main problem according to the solution of the sub-problem; ； In the formula, is an integer variable in the system, indicating the selection of hydrogen production station, hydrogen storage station, energy storage station, lines and pipelines; for formula A, and Respectively represent the sets of integer variables 0 and 1. Formula A is used to cut off the solution set that caused the subproblem to be infeasible last time. For formula B: If a node selects a hydrogen production station, a hydrogen storage station or ammonia synthesis, then at least one pipeline connected to it is selected, and the same applies to the line. are the relevant lines and pipelines of the constructed hydrogen production station, energy storage station, hydrogen storage station, and ammonia synthesis station; z is the upper bound of the sub-problem; Related power transmission lines and hydrogen pipelines; The values ​​of the decision variables solved for the main problem; If the submodel is feasible, then , then add a third Logic benders cut to the main problem, namely formula C, where Represents a lower bound, which is the lower bound of the projection problem of the original problem on the subproblem, used to improve z The lower bound Indicates that in a given The lower bound of time; Main problem update and iteration: First, calculate the main problem, solve the main problem to get the solution X0, and update the lower bound LB. Use the equipment capacity and pipeline selection scheme calculated by the main problem as input parameters to verify the sub-problem. If all constraints are met, it means that the current solution is feasible, record the total cost, and update the upper bound UB. Otherwise, generate the Logic Benders cut. Step S46: Repeat steps S43-S45, use the new constraints to re-solve the relaxed main problem, and use the new solution to solve all sub-problems; if the objective function value of the main problem has converged, that is, UB-LB≤E, stop the optimization and return the final solution, and finally obtain the node locations and capacities of the hydrogen production station, hydrogen storage station, and energy storage station of the electric-hydrogen collaborative system, as well as the connection topology of the transmission lines and hydrogen pipelines.

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