Comprehensive bearing capacity evaluation method for hydrogen energy of power distribution network

Abstract

The invention belongs to the technical field of power distribution network bearing capacity evaluation, and relates to a power distribution network hydrogen energy comprehensive bearing capacity evaluation method, which comprises the following steps: 1, enabling a hydrogen energy system to be equivalent to an internal source-containing energy hub, and constructing a green electricity-hydrogen energy power distribution system connected with a plurality of hydrogen production energy hubs; 2, establishing a power distribution network hydrogen energy comprehensive bearing capacity evaluation model; 3, aiming at a green electricity hydrogen energy system accessed in the power distribution network, taking the maximum hydrogen load access capacity of the power distribution network as a hydrogen energy comprehensive bearing capacity index, and analyzing the influence of the maximum hydrogen load bearing capacity of the power distribution network, the access capacity of an electrolytic bath, new energy development and the line capacity of the power distribution network on the comprehensive hydrogen load bearing capacity of the power distribution network; external characteristic modeling is carried out on the green electricity hydrogen energy system based on the energy hub, the green electricity hydrogen energy system can serve as a generalized node to be connected to the power distribution network, and the problem that multi-energy system coordinated dispatching is difficult is solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power distribution network carrying capacity evaluation, and particularly relates to a comprehensive carrying capacity evaluation method for hydrogen energy of a power distribution network. BACKGROUND

[0002] As an important carrier of green transformation of energy terminal, the hydrogen energy industry is developing rapidly. At present, the hydrogen energy industry in China is developing rapidly. Wind and solar energy electrolytic hydrogen production is an important path for decarbonization in the energy industry. Its operation mode, capacity planning, peak shaving and frequency modulation capability have been widely studied. Green electricity hydrogen energy system participating in the distribution network is a typical multi-energy coupled system. In the prior art, the energy hub is usually used as an input-output port model to describe the exchange and coupling relationship between energy, load and network in the multi-energy system.

[0003] The traditional carrying capacity is defined as: under the conditions of continuous overload of equipment, short-circuit current, voltage deviation and non-exceeding harmonic, the maximum capacity of the power grid to accommodate power and load. The number of electric vehicles or the installed capacity of new energy is usually selected as the carrying capacity index of electric vehicles and new energy in the distribution network. However, the traditional carrying capacity only considers the maximum carrying capacity of the distribution network under the physical limit, and does not consider the actual operating state of the power grid, resulting in an overly extreme carrying capacity result. At the same time, the carrying capacity evaluation result of a single scenario cannot reflect the influence of the development of the distribution network connected with the green electricity hydrogen energy system on the hydrogen energy carrying capacity. The existing carrying capacity evaluation mainly considers one or several aspects of system economy, flexibility and safety. However, system operation economy, flexibility, safety and line capacity all have important influence on the hydrogen energy carrying capacity of the distribution network. Therefore, the evaluation result considering only part of the aspects cannot fully reflect the carrying capacity of the distribution network for hydrogen energy, and a more comprehensive evaluation method is urgently needed.

[0004] The existing hydrogen energy carrying capacity evaluation of the distribution network has the following defects: first, the research on hydrogen energy carrying capacity is still in the blank stage in the existing research on the carrying capacity of the distribution network. Second, the existing carrying capacity evaluation result is too extreme, and the influence of system development on the carrying capacity is not considered.

[0005] Therefore, an evaluation method for the comprehensive carrying of the green electricity hydrogen energy system in the distribution network is needed to solve the technical problem of difficult coordination and scheduling of the existing multi-energy system. SUMMARY

[0006] The application provides the following technical scheme: a comprehensive carrying capacity evaluation method for hydrogen energy of a power distribution network, comprising the following steps: Step 1: equivalent the hydrogen energy system to an energy hub containing source inside, and construct a green electricity-hydrogen energy distribution system connected with multiple hydrogen production energy hubs.

[0007] Step 2, a hydrogen energy comprehensive bearing capacity evaluation model of the power distribution network is established, a target function of the evaluation model includes: economy, flexibility and safety of the green electricity hydrogen energy system, constraint conditions of the evaluation model include: energy hub constraint, electrolyzer operation constraint, fuel cell operation constraint, power distribution network operation constraint, hydrogen storage tank constraint and new energy unit output constraint.

[0008] Step 3, based on the evaluation model in step 2, for the green electricity hydrogen energy system connected to the power distribution network, the maximum hydrogen load connection capacity of the power distribution network is taken as the hydrogen energy comprehensive bearing capacity index; starting from the optimal electrolyzer connection capacity that can be borne by the existing power distribution network structure and the hydrogen load of the power distribution network, different scenarios are selected for sensitivity analysis, and the influence of the maximum hydrogen load bearing capacity of the power distribution network and the electrolyzer connection capacity, new energy development and power distribution network line capacity on the comprehensive hydrogen load bearing capacity of the power distribution network is analyzed.

[0009] Preferably, in step 1, the energy hub includes: wind turbine generator set, photovoltaic generator set, proton exchange membrane electrolyzer, fuel cell, hydrogen storage tank and hydrogen load; the input energy of the energy hub is the electric energy injected into the energy hub by the power distribution network through the electrolyzer; the output energy of the energy hub is the hydrogen gas meeting the hydrogen load, the electric energy provided by the fuel cell to the power distribution network and the new energy electric energy sent out by the energy hub; the internal energy source of the energy hub is the wind power and photovoltaic power generation.

[0010] Preferably, in step 1, the mathematical model of the wind-solar hydrogen production system of the energy hub is: (1) In formula (1), is the power exchanged between the energy hub connected to the power distribution network node i at time t , , , are the fuel cell power, hydrogen load and electrolyzer power of the energy hub at node i at time t , is the internal new energy power generation of the energy hub at node i at time t , , are the hydrogen storage tank hydrogen input and output amount of the energy hub at node i at time t , is the electrolyzer hydrogen conversion coefficient, is the fuel cell hydrogen conversion coefficient, , are the input energy conversion matrix and internal source energy conversion matrix respectively, O, S and I are output matrix, internal source matrix and input matrix respectively.

[0011] More preferably, in step 2, the objective function is: (2) In formula (2): 、 、 are economic index, flexibility index and safety index, respectively, 、 、 are economic index weight, flexibility index weight and safety index weight, respectively, is the comprehensive scheduling target.

[0012] The energy hub constraint is formula (1); the electrolyzer operation constraint is: (14) (15) In formula (14), (15), is the rated power of the electrolyzer connected to the i node.

[0013] The fuel cell operation constraint is: (16) (17) (18) In formula (16)-(18), is the fuel cell efficiency, is the hydrogen consumption amount of the fuel cell connected to the i node at time t, is the high value of hydrogen heat, is the rated power of the fuel cell connected to the i node.

[0014] The distribution network operation constraint is: (19) (20) (21) (22) (23) (24) In formula (19)-(24), 、 are the active power and reactive power of the line ij at time t, 、 are the active power and reactive power transmitted from the upper grid to the distribution network at time t, , is the reactive load of node i at time t, is the active load shedding power, , is the voltage of node i and j at time t, is the impedance of line ij, is the maximum allowed power of branch ij, is the active power of branch ij at time t; , is the active and reactive power of branch kj at time t, , is the maximum value of the transmission capacity of branch ij at time t, is the upper limit of the line capacity, is the percentage limit of the allowed excess; The hydrogen storage tank constraint is: (25) (26) (27) (28) In formula (25) to (28), , is the upper and lower limits of the input and output hydrogen amount of the hydrogen storage tank, , is the hydrogen content of the hydrogen storage tank of node i at time t and t+1, , is the hydrogen content of the hydrogen storage tank of node i at the beginning and end of scheduling, is the initial hydrogen content of the hydrogen storage tank.

[0015] The new energy unit output constraint is: (29) (30) In formula (29) to (30), is the predicted output of the new energy unit of node i at time t, is the i node t at time t.

[0016] More preferably, the economic index , the flexibility index , and the safety index are respectively: (3) (9) (13) in formula (3), (9), (13), is the installation cost, is the operation cost, is the load shedding penalty cost; is the system up and down flexibility, is the new energy accommodation flexibility; S is a branch set of the power distribution network, is the time variation, is the system congestion penalty coefficient.

[0017] Preferably, the step 3 comprises the following sub-steps: Step 3-1: Given the wind power installed capacity and the photovoltaic installed capacity of each energy hub node, using the power distribution network carrying capacity optimization model, the electrolyzer access capacity and the hydrogen load that can be carried by the power distribution network at this time are decision variables, and the optimal electrolyzer installed capacity of the given power distribution network is obtained.

[0018] Step 3-2: On the basis of the scenario in step 3-1, 20%, 40%, 60%, 80% and 100% of the electrolyzer installed capacity growth are selected, and 20%, 40%, 60%, 80% and 100% of the new energy installed capacity growth are selected to construct the scene for sensitivity analysis, and the comprehensive influence of the electrolyzer installed capacity growth and the new energy installed capacity growth on the comprehensive hydrogen energy carrying capacity of the power distribution network is obtained.

[0019] Step 3-3: On the basis of the scenario in step 3-1, 20%, 40%, 60%, 80% and 100% of the electrolyzer installed capacity growth are selected for sensitivity analysis; further analysis is made on the influence of the electrolyzer installed capacity growth on the comprehensive hydrogen energy carrying capacity of the power distribution network under the condition of a given new energy installed capacity, and the hydrogen energy comprehensive carrying capacity of the power distribution network based on the built wind power and photovoltaic of the power distribution network and the corresponding electrolyzer installed capacity are obtained.

[0020] Step 3-4: On the basis of the scenario in step 3-3, the electrolyzer installed capacity corresponding to the maximum hydrogen load carrying capacity of the power distribution network is selected, and 20%, 40%, 60%, 80% and 100% of the new energy installed capacity growth are selected to analyze the influence of the new energy installed capacity growth on the hydrogen energy comprehensive carrying capacity of the power distribution network.

[0021] The beneficial effects of the present application are: 1. The present application models the external characteristics of the green electricity hydrogen energy system based on the energy hub, which can be connected to the power distribution network as a generalized node, and solves the problem of coordinated scheduling of multi-energy systems.

[0022] 2.The application proposes a green electricity hydrogen energy system comprehensive bearing capacity index in a power distribution network, and takes the maximum hydrogen load access capacity as the comprehensive bearing capacity index of the green electricity hydrogen energy system in the power distribution network, filling the research gap of hydrogen energy bearing capacity in the existing technology.

[0023] 3.The application proposes a power distribution network comprehensive hydrogen energy bearing capacity evaluation method considering economy, flexibility and safety at the same time, and further analyzes the influence of new energy and electrolyzer capacity development on the comprehensive hydrogen energy bearing capacity of the power distribution network; starting from the optimal electrolyzer access capacity that the existing power distribution network structure can bear and the hydrogen load of the power distribution network, different scenarios are selected for sensitivity analysis to analyze the influence of the maximum hydrogen load bearing capacity of the power distribution network, the electrolyzer access capacity, the development of new energy and the line capacity of the power distribution network on the comprehensive hydrogen load bearing capacity of the power distribution network; therefore, the application solves the problem that the results obtained by the existing bearing capacity evaluation technology are too extreme and the influence of system development on the bearing capacity is not considered. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 A green electricity-hydrogen energy power distribution system diagram for multiple green electricity hydrogen energy hubs accessed by the comprehensive bearing capacity evaluation method of the hydrogen energy of the power distribution network of the application; Figure 2 A method step schematic diagram of the application. DETAILED DESCRIPTION

[0025] The related technologies in the application will be described clearly and completely in combination with the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor belong to the protection scope of the application.

[0026] As shown in the drawings, Figures 1-2 The comprehensive bearing capacity evaluation method of the hydrogen energy of the power distribution network of the embodiment includes: Step 1, according to the evaluation needs and actual situation, the hydrogen energy system is equivalent to an internal energy hub containing a source. A green electricity-hydrogen energy power distribution system with multiple hydrogen energy hubs is constructed, and its structure is as shown in the drawings. Figure 1

[0027] The green electricity hydrogen energy system energy hub includes a wind turbine generator set, a photovoltaic generator set, a proton exchange membrane (PEM) electrolyzer, a fuel cell, a hydrogen storage tank and a hydrogen load. The input energy of the energy hub is the electric energy injected into the energy hub by the power distribution network through the electrolyzer, the output energy of the energy hub is hydrogen (to meet the hydrogen load), the electric energy provided by the fuel cell to the power distribution network and the new energy electric energy sent out by the energy hub, and the internal energy source of the energy hub is wind power and photovoltaic power generation.​

[0028] according to Figure 1 Modeling the energy hub structure of the green electric hydrogen energy system in China. First, establish the input ( I Energy conversion matrix and internal sources ( I Energy conversion matrix Then, based on the energy conversion matrix, an energy hub input-output ( I / O The energy conversion relationship of the matrix. This invention models hydrogen energy storage as an internal energy source and modifies the internal energy source generated by internal renewable energy power generation. The mathematical model of the wind-solar hydrogen production system is obtained as follows: (1) In the formula: To connect to the distribution network node i Energy hub in t The power exchanged with the distribution network at all times. , , They are nodes i energy hub t The fuel cell power, hydrogen load, and electrolyzer power at any given time. For nodes i energy hub t Internal renewable energy power generation capacity at any given time , Points i energy hub t Real-time hydrogen inflow and outflow from the hydrogen storage tank The electro-hydrogen conversion coefficient of the electrolyzer is . The hydrogen-to-electric conversion coefficient of the fuel cell. , These are the input energy conversion matrix and the internal source energy conversion matrix, respectively, while O, S, and I are the output matrix, the internal source matrix, and the input matrix, respectively.

[0029] Step 2: Establish a comprehensive hydrogen energy carrying capacity assessment model for the power distribution network. The objective function includes the economy, flexibility, and safety of the green electricity hydrogen energy system. Constraints include: energy hub constraints, electrolyzer operation constraints, fuel cell operation constraints, power distribution network operation constraints, hydrogen storage tank constraints, and new energy unit output constraints.

[0030] (1) Objective function Simultaneously considering the economy, flexibility, and safety of the electro-hydrogen coupled distribution network system, a comprehensive dispatching objective is achieved. .

[0031] (2) In the formula: 、 、 are economic index, flexibility index, safety index, respectively, 、 、 are economic index, flexibility index, safety index weight, respectively.

[0032] 1) Economic index The economic index includes: installation cost , operation cost , load shedding penalty cost , hydrogen sales revenue , upper grid electricity purchase cost .

[0033] (3) Wherein, the installation cost is: (4) In the formula: is the set of distribution network nodes connected to the energy hub, , are the installation prices of fuel cells and electrolyzers, respectively, , are the installation capacities of fuel cells and electrolyzers at nodes i , respectively, r is the annual interest rate, n is the operation life.

[0034] The operation cost is: (5) In the formula: T is the number of optimization periods, is the dispatching step length, , , are the operation cost coefficients of fuel cells, electrolyzers and hydrogen storage tanks, respectively.

[0035] The load shedding penalty cost is: (6) In the formula: I is the set of distribution network nodes, , are the costs of shedding electric load and hydrogen load, respectively, , are the amounts of electric load shedding and hydrogen load shedding at nodes i at time t .

[0036] The hydrogen sales revenue is: (7) wherein: is the hydrogen sales price.

[0037] The upper grid electricity purchase cost is: (8) wherein: is the electricity purchase cost, is t the amount of electricity purchased by the distribution grid from the upper grid at time t.

[0038] 2) Flexibility index The flexibility index includes system up-down regulation flexibility and new energy consumption flexibility .

[0039] (9) The system up-down regulation flexibility can be defined by equations (9-10): (10) (11) wherein: is the node i up-down regulation flexibility, is the node i electrolyzer climbing coefficient, is the system up-down regulation flexibility, is the up-down regulation flexibility weighting parameter.

[0040] The system new energy consumption flexibility is represented by the new energy curtailment cost: (12) wherein: is the new energy curtailment penalty coefficient, is i the node t new energy curtailment amount at time t.

[0041] 3) Safety index (13) wherein S is the branch set of the distribution grid, , and are the positive and negative branch power exceeding the safety threshold of branch ij (with node i as the first node and node j as the last node) at time t, is the system congestion penalty coefficient.

[0042] (2) Constraint conditions 1) Energy Hub Operation Constraints The Energy Hub Operation Constraints have been given in equation (1).

[0043] 2) Electrolyzer Operation Constraints Equation (14) is the upper and lower bounds of electrolyzer operation, and equation (15) is the electrolyzer access capacity constraint.

[0044] (14) (15) 3) Fuel Cell Operation Constraints Equation (15) is the fuel cell power generation constraint, equation (16) is the upper and lower bounds of fuel cell operation, and equation (17) is the fuel cell capacity constraint. In order to ensure the efficient conversion of electricity-hydrogen-electricity, the fuel cell capacity is configured to be 1.4 times the electrolyzer capacity.

[0045] (16) (17) (18) In the formula: is the fuel cell efficiency, is the amount of hydrogen consumed by the fuel cell at i node t, is the high value of hydrogen heat, is the rated power of the fuel cell accessed by i node.

[0046] 4) Distribution Network Operation Constraints The present application uses the DistFlow model to describe the radial distribution network power flow constraints. Equation (19) is the line active power balance, equation (20) is the line reactive power balance, and equation (21) is the line voltage constraint. The safe operation of the distribution network allows the line flow to exceed the upper limit of the line transmission capacity in emergency situations. is the percentage upper limit of the allowed excess. Equations (22-24) are the relaxed upper and lower bounds of the line capacity constraints.

[0047] (19) (20) (21) (22) (23) (24) In the formula: , are the line ij active and reactive power flow at i node t, , Qi, t is the active power delivered by the i-th node to the distribution network at time t, , Qi, t is the reactive power delivered by the i-th node to the distribution network at time t, Qi, t is the active power delivered by the i-th node to the distribution network at time t, Vi, t is the voltage at the i-th node at time t, Zij is the impedance of the line ij. Pmax, ij is the maximum allowed power of the branch ij, Pi, j, t is the active power of the branch ij at time t; , Qi, j, t is the active and reactive power of the branch kj at time t, , Pmax, ij, t is the maximum value of the transmission capacity of the branch ij at time t that is allowed to exceed the upper and lower limits, Pmax, ij, t is the upper limit of the line capacity, Pmax, ij, t is the percentage upper limit of the allowed limit.

[0048] 5) Hydrogen storage tank operation constraints (25) (26) (27) (28) In the formula: , Pmin, i, t and Pmax, i, t are the upper and lower limits of the input and output hydrogen amount of the hydrogen storage tank, Hi, t is the hydrogen content of the i-th node at time t, , Hi, t0 and Hi, t1 are the hydrogen content of the i-th node at the beginning and end of the dispatch, Hi, 0 is the initial hydrogen content of the hydrogen storage tank.

[0049] 6) New energy unit output constraints (29) (30) In the formula, Pi, t is the predicted output of the new energy unit at the i-th node at time t.

[0050] Step 3, on the basis of the built-in wind power and photovoltaic of the power distribution network, based on the power distribution network hydrogen comprehensive bearing capacity evaluation model put forward in step 2, for the green electricity hydrogen energy system accessed in the power distribution network, the present application puts forward the maximum hydrogen load access capacity of the power distribution network as the hydrogen comprehensive bearing capacity index. From the optimal electrolytic tank access capacity that the existing power distribution network structure can bear and the hydrogen load of the power distribution network, select different scenes for sensitivity analysis, analyze the influence of the maximum hydrogen load bearing capacity of the power distribution network, the electrolytic tank access capacity, the development of new energy and the line capacity of the power distribution network on the comprehensive hydrogen load bearing capacity of the power distribution network.

[0051] Step 3-1: given the wind power installed capacity and photovoltaic installed capacity of each energy hub node, using the power distribution network bearing capacity optimization model put forward by the present application, the electrolytic tank access capacity and the hydrogen load that the power distribution network can bear at this time are decision variables. The optimal electrolytic tank installed capacity of the given power distribution network is obtained.

[0052] Step 3-2: on the basis of the scene of step 3-1, select electrolytic tank installed capacity growth of 20%, 40%, 60%, 80%, 100% and select new energy installed capacity growth of 20%, 40%, 60%, 80%, 100% to build 36 scenes for sensitivity analysis. The comprehensive influence of electrolytic tank installed capacity growth and new energy installed capacity growth on the comprehensive hydrogen energy bearing capacity of the power distribution network is obtained.

[0053] Step 3-3: on the basis of the scene of step 3-1, select electrolytic tank installed capacity growth of 20%, 40%, 60%, 80%, 100% for sensitivity analysis. Further analyze the comprehensive influence of electrolytic tank installed capacity growth on the comprehensive hydrogen energy bearing capacity of the power distribution network under the condition of given new energy installed capacity. And obtain the comprehensive hydrogen energy bearing capacity of the power distribution network on the basis of the built-in wind power and photovoltaic of the power distribution network and the corresponding electrolytic tank installed capacity researched by the present application.

[0054] Step 3-4: on the basis of the scene of step 3-3, select the electrolytic tank installed capacity corresponding to the maximum hydrogen load bearing capacity of the power distribution network, select new energy installed capacity growth of 20%, 40%, 60%, 80%, 100%. Analyze the influence of the development of the power distribution network and the growth of new energy installed capacity on the comprehensive hydrogen energy bearing capacity of the power distribution network.

[0055] In summary, the present application models the external characteristics of the green electricity hydrogen energy system based on the energy hub, which can be accessed into the power distribution network as a generalized node, solves the problem of coordinated scheduling of multi-energy system, and the present application puts forward the comprehensive bearing capacity index of the green electricity hydrogen energy system in the power distribution network, taking the maximum hydrogen load access capacity as the comprehensive bearing capacity index of the green electricity hydrogen energy system in the power distribution network, and fills the research gap of the hydrogen bearing capacity of the power distribution network in the prior art.

[0056] It should be pointed out that the above is only the preferred embodiment of the present application, and does not limit the present application in any form. Any simple modification, equivalent change and modification of the above embodiment according to the technical essence of the present application still belongs to the scope of the technical solution of the present application.

Claims

1. A method for comprehensively assessing the hydrogen energy carrying capacity of a power distribution network, characterized in that, Includes the following steps: Step 1: Equivalently treat the hydrogen energy system as an internal energy hub containing energy sources, and construct a green electricity-hydrogen energy distribution system that connects multiple hydrogen production energy hubs; Step 2: Establish a comprehensive hydrogen energy carrying capacity assessment model for the power distribution network. The objective function of the assessment model includes the economy, flexibility and safety of the green hydrogen energy system. The constraints of the assessment model include: energy hub constraints, electrolyzer operation constraints, fuel cell operation constraints, power distribution network operation constraints, hydrogen storage tank constraints and new energy unit output constraints. Step 3: Based on the evaluation model described in Step 2, for the green electricity hydrogen energy system connected to the distribution network, the maximum hydrogen load access capacity of the distribution network is used as the comprehensive hydrogen energy carrying capacity index. Starting from the optimal electrolyzer access capacity that the existing distribution network structure can support and the hydrogen load of the distribution network, different scenarios are selected for sensitivity analysis to analyze the impact of the maximum hydrogen load carrying capacity of the distribution network, the electrolyzer access capacity, the development of new energy sources, and the capacity of distribution network lines on the comprehensive hydrogen load carrying capacity of the distribution network.

2. The method for assessing the comprehensive carrying capacity of hydrogen energy in a power distribution network according to claim 1, characterized in that, In step 1, the energy hub includes: a wind turbine generator set, a photovoltaic generator set, a proton exchange membrane electrolyzer, a fuel cell, a hydrogen storage tank, and a hydrogen load; the input energy of the energy hub is the electrical energy injected into the energy hub by the power distribution network through the electrolyzer; the output energy of the energy hub is the hydrogen to meet the hydrogen load, the electrical energy provided to the power distribution network by the fuel cell, and the new energy electrical energy sent out by the energy hub; the energy source inside the energy hub is wind power generation and photovoltaic power generation.

3. The method for assessing the comprehensive carrying capacity of hydrogen energy in a power distribution network according to claim 1, characterized in that, In step 1, the mathematical model of the wind-solar hydrogen production system of the energy hub is as follows: （1） In equation (1), To connect to the distribution network node i Energy hub in t The power exchanged with the distribution network at all times. , , They are nodes i energy hub t The fuel cell power, hydrogen load, and electrolyzer power at any given time. For nodes i energy hub t Internal renewable energy power generation capacity at any given time , Points i energy hub t Real-time hydrogen inflow and outflow from the hydrogen storage tank The electro-hydrogen conversion coefficient of the electrolyzer is . The hydrogen-to-electric conversion coefficient of the fuel cell. , These are the input energy conversion matrix and the internal source energy conversion matrix, respectively, while O, S, and I are the output matrix, the internal source matrix, and the input matrix, respectively.

4. The method for assessing the comprehensive carrying capacity of hydrogen energy in a power distribution network according to claim 3, characterized in that, In step 2, the objective function is: （2） In formula (2): , , These are economic indicators, flexibility indicators, and safety indicators. , , The weights for the indicators are economy, flexibility, and safety, respectively. For the overall scheduling objective; The energy hub constraint is given by equation (1). The operating constraints of the electrolytic cell are: （14） （15） In equations (14) and (15), The rated power of the electrolytic cell connected to node i; The operating constraints of the fuel cell are: （16） （17） （18） In equations (16) to (18), For fuel cell efficiency, Let be the amount of hydrogen consumed by the fuel cell at time t at node i. The calorific value of hydrogen is high. The rated power of the fuel cell connected to the i-node; The operating constraints of the power distribution network are: （19） （20） （21） （22） （23） （24） In equations (19) to (24), , Let i be the reactive power flow of line ij at time t, and i be the reactive power flow of line ij. , These represent the reactive power transmitted from the upstream power grid to the distribution network at time t, i.e., node i. , Let i represent the reactive load at time t. For active load shedding power, , The voltages at nodes i and j at time t are respectively. Let ij be the impedance of the line. The maximum allowable power of branch line ij is Let be the active power of branch ij at time t; , Let Kj be the reactive power of branch Kj at time t. , Let be the maximum value allowed for the ij branch to exceed the upper and lower limits of its transmission capacity at time t. This is the upper limit of line capacity. To allow a percentage exceeding the limit; The constraints of the hydrogen storage tank are: （25） （26） （27） （28） In equations (25) to (28), , These are the upper and lower limits for the input and output hydrogen volume of the hydrogen storage tank. , Let i be the hydrogen content in the hydrogen storage tank at time t and time t+1. , The hydrogen content of the hydrogen storage tank at node i at the start and end of the scheduling process. This represents the initial hydrogen content of the hydrogen storage tank. The output constraint of the new energy unit is: （29） （30） In equations (29) to (30), Predicted output of new energy generating units at time t of node i. for i node t Constantly monitor the amount of electricity wasted from renewable energy sources.

5. The method for assessing the comprehensive carrying capacity of hydrogen energy in a power distribution network according to claim 4, characterized in that, The economic indicators Flexibility indicators Safety indicators They are respectively: （3） （9） （13） In equations (3), (9), and (13), For installation costs, For operating costs, To incur cost penalties for load shedding; To improve the flexibility of system adjustments, For the flexibility of new energy consumption; S is the set of distribution network branches. For the time change, This represents the system congestion penalty coefficient.

6. The method for assessing the comprehensive carrying capacity of hydrogen energy in a power distribution network according to claim 1, characterized in that, Step 3 includes the following sub-steps: Step 3-1: Given the wind power capacity and photovoltaic capacity of each energy hub node, use the distribution network carrying capacity optimization model, with the electrolyzer access capacity and the hydrogen load that the distribution network can carry at this time as decision variables, to obtain the optimal electrolyzer capacity for a given distribution network. Step 3-2: Based on the scenario in Step 3-1, select scenarios with electrolyzer installed capacity growth of 20%, 40%, 60%, 80%, and 100% and new energy installed capacity growth of 20%, 40%, 60%, 80%, and 100% to construct a sensitivity analysis, and obtain the comprehensive impact of electrolyzer installed capacity growth and new energy installed capacity growth on the overall hydrogen energy carrying capacity of the power distribution network. Step 3-3: Based on the scenario in Step 3-1, sensitivity analysis is performed on electrolyzer installed capacity increases of 20%, 40%, 60%, 80%, and 100%. Further analysis is conducted on the comprehensive impact of electrolyzer installed capacity increases on the overall hydrogen energy carrying capacity of the distribution network under a given new energy installed capacity, to obtain the overall hydrogen energy carrying capacity of the distribution network based on the existing wind and solar power and the corresponding electrolyzer installed capacity. Step 3-4: Based on the scenario in Step 3-3, select the electrolyzer capacity corresponding to the maximum hydrogen load carrying capacity of the distribution network, and select the growth of new energy installed capacity of 20%, 40%, 60%, 80%, and 100% to analyze the impact of distribution network development and the growth of new energy installed capacity on the comprehensive hydrogen energy carrying capacity of the distribution network.

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