Hydrogen energy storage optimal configuration method

Abstract

The invention discloses a hydrogen energy storage optimal configuration method, which belongs to the technical field of hydrogen energy storage, and comprises the following steps: carrying out cluster division based on source load storage power coordination and uncertainty; a cluster division result is introduced, a power distribution network-cluster-node clustering double-layer planning model is constructed, an upper-layer decision variable is the hydrogen energy storage capacity and the grid connection position of the cluster, and a lower-layer decision variable is the charging and discharging power of hydrogen energy storage in the cluster; constructing an objective function of an upper-layer planning model according to an optimization objective of minimum annual comprehensive cost of the power distribution network; setting constraint conditions of the upper-layer planning model; constructing a target function of a lower-layer regulation and control model according to the optimization target with the minimum node deviation; and setting constraint conditions of the lower-layer regulation and control model. According to the method, the system planning cost can be effectively reduced, the voltage operation stability is improved, the network loss is reduced, and the method has higher adaptability and practical value.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogen energy storage, and in particular to a method for optimizing the configuration of hydrogen energy storage. Background Art

[0002] Distributed photovoltaics are becoming an increasingly important energy source in distribution networks. However, due to external environmental factors, photovoltaic output exhibits significant randomness and volatility, posing significant challenges to the safe and stable operation of distribution networks. Especially as photovoltaic penetration continues to increase, the timing mismatch between photovoltaic output and load demand is becoming increasingly prominent, leading to a series of operational risks such as voltage overshoot, reverse power flow, and difficulties in local power consumption.

[0003] Hydrogen energy storage, a new energy storage method with rapid response, environmental friendliness, and flexible charge and discharge power regulation, provides an effective solution for the timing mismatch between photovoltaic power generation and loads. Therefore, how to rationally optimize the configuration of hydrogen energy storage in distribution networks has become a key issue that requires urgent research.

[0004] At present, there are still many deficiencies in the planning and configuration of hydrogen energy storage in distribution networks, which are mainly reflected in the following aspects:

[0005] 1. Current hydrogen energy storage planning and configuration methods generally locate hydrogen energy storage at nodes with high voltage sensitivity, and these nodes are mostly located at the end of the network. When conducting group dispatch and control research in new power systems, the isolation and limitations of end nodes make it difficult for hydrogen energy storage to achieve coordinated control of the global operating state, nor can it effectively regulate the overall system voltage and network losses, thereby exacerbating node voltage fluctuations and increasing network losses.

[0006] 2. The cluster planning method can effectively reduce the computational complexity and enhance the operational flexibility, thus providing a new approach for hydrogen energy storage planning in modern distribution networks. This method relies on cluster division to distribute hydrogen energy storage to different clusters with close connections within the cluster and loose connections between clusters, and then achieves a reasonable configuration of hydrogen energy storage through model optimization. However, the cluster division method used in the existing cluster planning method has significant defects. Its division process is based on a static network structure under a specific operating state, and is only applicable to scenarios with fixed sources and loads. It ignores the randomness of photovoltaic output and load demand, as well as the influence of source-load-storage power coordination between clusters. Therefore, in order to improve the reliability and applicability of the hydrogen energy storage cluster planning method, the cluster division method should further consider the randomness and volatility of the source and load, and enhance the source-load-storage coordination capability between clusters.

[0007] 3. Existing configuration methods typically employ weighted summation and other methods for unified modeling and optimization when dealing with multiple mutually constrained and impactful objective functions. However, such methods are sensitive to weight parameters and struggle to balance voltage stability while ensuring system economics. This results in insufficient multi-objective coordination in the final planning results.

[0008] 4. Existing configuration methods require iterative calculations for all nodes in the distribution network, involving numerous decision variables and resulting in high solution complexity. Due to the large number of variables and complex constraints, the optimization algorithm converges slowly, affecting overall solution efficiency and making it difficult to meet the computational speed and real-time requirements of actual large-scale distribution network planning. Summary of the Invention

[0009] The present invention addresses the problems in existing hydrogen energy storage planning methods, such as the site selection being concentrated on network end nodes with high voltage sensitivity but weak regulation capability, and the failure to consider source-load-storage coordination and operational uncertainty. A hydrogen energy storage optimization configuration method is provided. A cluster division method that considers source-load-storage power coordination and uncertainty is adopted to form a distribution network-cluster-node grid structure; a distribution network-cluster-node clustering and hierarchical planning strategy is established to achieve efficient and safe configuration of hydrogen energy storage in the distribution network; and a two-layer planning model for hydrogen energy storage that includes the annual comprehensive cost of the distribution network and the node voltage deviation is constructed to ensure the safety of the distribution network while improving the economic efficiency of system operation.

[0010] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0011] A method for optimizing hydrogen energy storage configuration includes the following steps:

[0012] S1. Cluster division based on source-load-storage power coordination and uncertainty;

[0013] S2. Introduce the cluster division results and construct a two-level planning model of distribution network-cluster-node clustering. The upper-level decision variables are the cluster's hydrogen energy storage capacity and grid connection location, and the lower-level decision variables are the charging and discharging power of the hydrogen energy storage in the cluster.

[0014] S3. Construct the objective function of the upper-level planning model based on the optimization goal of minimizing the annual comprehensive cost of the distribution network;

[0015] S4. Set the constraints of the upper-level planning model;

[0016] S5. Construct the objective function of the lower-level control model based on the optimization goal of minimizing node deviation;

[0017] S6. Set the constraints of the lower-level control model.

[0018] A further improvement of the technical solution of the present invention is that: in S1, a cluster partitioning optimization model is constructed based on the partitioning characteristic indicators, the partitioning characteristic indicators include electrical distance modularity, cluster active and reactive balance and source-load-storage coordination, and the model is solved under source-load multi-scenario and robustness test conditions.

[0019] A further improvement of the technical solution of the present invention is that: in S2, the distribution network-cluster-node clustering two-layer planning model includes an upper-layer planning model and a lower-layer control model. The hydrogen energy storage capacity and location information obtained by the upper-layer model based on the planning objectives will become the initial conditions of the lower-layer model. Through parameter transfer, the hydrogen energy storage charging and discharging power connected to each cluster in the lower-layer model is determined based on the upper-layer planning results; the upper-layer model continues to optimize based on the optimization results of the lower-layer model, and finally determines the optimal solution of the distribution network-cluster-node clustering hierarchical planning model.

[0020] A further improvement of the technical solution of the present invention is that in S3, the upper model takes the minimum annual comprehensive cost of the distribution network as the objective function, and the hydrogen energy storage capacity and location of each cluster as the decision variable; the objective function is shown in formula (1):

[0021] minF=C inv +C om +C buy -C sub (18)

[0022] Where, F is the annual comprehensive cost of the distribution network; C inv is the equivalent annual investment cost of hydrogen energy storage; C om is the annual operation and maintenance cost of hydrogen energy storage; C buy The cost of purchasing electricity from the main grid; C sub Subsidies for photovoltaics;

[0023] The equivalent annual investment cost of hydrogen energy storage is shown in formula (2):

[0024]

[0025] Where N c is the number of clusters; r is the discount rate; y is the useful life of hydrogen energy storage; The unit capacity and unit power investment cost of hydrogen energy storage; The rated capacity and rated power of hydrogen energy storage configured for cluster i;

[0026] The annual operation and maintenance cost of hydrogen energy storage is shown in formula (3):

[0027]

[0028] Where, T is the running time 8760h; The operating and maintenance cost per unit charge and discharge volume of hydrogen energy storage; is the charging and discharging power of hydrogen energy storage in cluster i at time t, where positive values ​​represent discharging and negative values ​​represent charging;

[0029] The main grid electricity purchase cost is shown in formula (4):

[0030]

[0031] Where N con The number of branches connecting the busbar and the cluster, that is, the number of main network connection branches; is the real-time electricity price of the main network at time t; is the power of the main network tie branch l at time t;

[0032] The photovoltaic subsidy is shown in the following formula (5):

[0033]

[0034] Where C bt Provide photovoltaic subsidies for units; is the hydrogen energy storage output within cluster i at time t;

[0035] The hydrogen energy storage system includes a matching electrolyzer, a fuel cell and a converter.

[0036] A further improvement of the technical solution of the present invention is that: in S4, the constraints of the upper-level planning model include cluster hydrogen energy storage grid connection location constraints, power balance constraints, node voltage constraints, power flow constraints, main network interconnection branch interaction power constraints, and intra-cluster branch transmission power constraints;

[0037] Cluster hydrogen energy storage grid connection location constraints:

[0038]

[0039] Where, is the hydrogen energy storage grid connection location, a value of 1 indicates that node i in cluster j is connected to hydrogen energy storage, and a value of 0 indicates that it is not connected to hydrogen energy storage;

[0040] Power balance constraints:

[0041]

[0042] Where N j is the number of nodes contained in cluster j; N SI is the number of distribution network branches; is the load power of node j at time t; is the branch network loss at time t;

[0043] Node voltage constraints:

[0044]

[0045] Where, are the upper and lower limits of the voltage amplitude of node j in cluster i;

[0046] Power flow constraints:

[0047]

[0048] Where, P i , Q i The active and reactive power injected into node i; U i 、U j is the voltage amplitude of nodes i and j; G ij 、B ij is the admittance of branch ij; θ ij is the voltage phase angle of nodes i and j;

[0049] Interactive power constraints of the main network tie branch:

[0050]

[0051] Where, The upper and lower limits of the interactive power allowed to pass through the main network contact branch l;

[0052] Transmission power constraints of branches within a group:

[0053]

[0054] Where, N is the upper and lower limits of the transmission power of branch l within cluster i; I,i is the number of branches in cluster i.

[0055] A further improvement of the technical solution of the present invention is that in S5, the lower model takes the minimum node voltage deviation as the objective function and the cluster hydrogen energy storage charging and discharging power as the decision variable, taking into account both the system voltage stability and the source-load-storage power coordination capability. The objective function is shown in formula (12):

[0056]

[0057] Where N bus is the number of distribution network nodes; U i,t is the voltage of node i at time t; U N is the rated voltage.

[0058] A further improvement of the technical solution of the present invention is that: in S6, the constraints of the lower-level control model include cluster hydrogen energy storage supply and demand coordination constraints, hydrogen energy storage charge and discharge power constraints, and hydrogen energy storage charge and discharge efficiency and charge state constraints;

[0059] Constraints on the coordination of supply and demand of cluster hydrogen energy storage:

[0060]

[0061] Where, It is the coordination index of cluster hydrogen energy storage supply and demand, showing the coordination ability of each cluster's source, load and storage adjustable resources with the system operation requirements; ΔP Ωx,t is the difference between the hydrogen storage energy and net power of cluster Ωx at time t; Φ e is the hydrogen energy storage supply and demand coordination indicator of cluster Ωx; It is an indicator of the coordination of hydrogen energy storage supply and demand in the distribution network as a whole;

[0062] Hydrogen energy storage charging and discharging power constraints:

[0063]

[0064] Where, is the maximum value of hydrogen energy storage charging and discharging power in cluster i;

[0065] Hydrogen energy storage charging and discharging efficiency and state of charge constraints:

[0066]

[0067] Where, SOC max , SOC min The upper and lower limits of the state of charge of hydrogen energy storage; SOC i,t is the state of charge of hydrogen energy storage in cluster i at time t; η i,t is the charge and discharge efficiency of hydrogen energy storage; η disc ,η char is the discharge and charge efficiency; It is the charge and discharge state, positive value indicates discharge, negative value indicates charge; SOC i,0 is the initial value of the state of charge.

[0068] Due to the adoption of the above technical solution, the technical advancements achieved by the present invention are:

[0069] 1. The present invention adopts a cluster division method that takes into account the coordination and uncertainty of source, load and storage power to form a grid structure of distribution network-cluster-node.

[0070] 2. The present invention establishes a distribution network-cluster-node clustering and hierarchical planning strategy, which distributes hydrogen energy storage to each cluster and realizes its coordinated planning and configuration through a two-layer model.

[0071] 3. The present invention constructs a two-layer planning model for hydrogen energy storage that includes the annual comprehensive cost of the distribution network and the node voltage deviation. The upper and lower models respectively aim to minimize the annual comprehensive cost of the distribution network and the node voltage deviation, and rationally configure hydrogen energy storage in each cluster. This not only overcomes the limitation of traditional hydrogen energy storage site selection that is concentrated at the terminal node, but also balances the economy and safety of the system.

[0072] 4. The present invention introduces cluster hydrogen energy storage grid connection location constraints and cluster hydrogen energy storage supply and demand coordination constraints to ensure the practicality and reliability of the optimized configuration. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 It is a flow chart of a hydrogen energy storage optimization configuration method. DETAILED DESCRIPTION

[0074] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments:

[0075] like Figure 1 As shown, a hydrogen energy storage optimization configuration method includes the following steps:

[0076] S1. Cluster division based on source-load-storage power coordination and uncertainty;

[0077] A cluster partitioning optimization model is constructed based on the partitioning characteristic indicators, which include electrical distance modularity, cluster active and reactive power balance, and source-load-storage coordination. The model is then solved under multiple source-load scenarios and robustness test conditions.

[0078] This method not only fully considers the uncertainty of source and load, but also improves the source-load-storage coordination capability of each cluster, thereby constructing a distribution network-cluster-node network structure.

[0079] S2. Introduce the cluster division results and construct a two-level planning model of distribution network-cluster-node clustering. The upper-level decision variables are the cluster's hydrogen energy storage capacity and grid connection location, and the lower-level decision variables are the charging and discharging power of the hydrogen energy storage in the cluster.

[0080] The cluster division results are introduced into the two-level planning model. The two-level planning model includes the hydrogen energy storage grid connection location constraints and the cluster hydrogen energy storage supply and demand coordination constraints, which together constitute the constraints of the two-level planning model.

[0081] The distribution network-cluster-node clustering two-level planning model includes an upper-level planning model and a lower-level control model. The upper-level planning model and the lower-level planning model are both independent of each other and influence each other. The upper-level planning model and the lower-level control model have their own complete objective functions, decision variables, and constraints. The hydrogen energy storage capacity and location information obtained by the upper-level model based on the planning objectives will become the initial conditions of the lower-level model. Through parameter transfer, the hydrogen energy storage charging and discharging power of each cluster connected to the lower-level model is determined based on the upper-level planning results. At the same time, the upper model continues to optimize based on the optimization results of the lower-level model, and finally determines the optimal solution of the distribution network-cluster-node clustering hierarchical planning model.

[0082] It can be seen that the optimization processes between the upper and lower layers are closely linked and mutually constrained. Through continuous iterative optimization between models, the annual comprehensive cost is minimized and tends to be stable, thus achieving the optimal configuration and efficient operation of hydrogen energy storage in the distribution network.

[0083] S3. Construct the objective function of the upper-level planning model based on the comprehensive optimization goal of source-load-storage power coordination;

[0084] The hydrogen energy storage system includes supporting electrolyzers, fuel cells, converters and other devices;

[0085] Considering the economic efficiency of the hydrogen energy storage planning process, the upper-level model takes the minimum annual comprehensive cost of the distribution network as the objective function and the hydrogen energy storage capacity and location of each cluster as the decision variables; the objective function is shown in formula (1):

[0086] minF=C inv +C om +C buy -C sub (35)

[0087] Where, F is the annual comprehensive cost of the distribution network; C inv is the equivalent annual investment cost of hydrogen energy storage; C om is the annual operation and maintenance cost of hydrogen energy storage; C buy The cost of purchasing electricity from the main grid; C sub Subsidies for photovoltaics;

[0088] The equivalent annual investment cost of hydrogen energy storage is shown in formula (2):

[0089]

[0090] Where N c is the number of clusters; r is the discount rate; y is the useful life of hydrogen energy storage; The unit capacity and unit power investment cost of hydrogen energy storage; The rated capacity and rated power of hydrogen energy storage configured for cluster i;

[0091] The annual operation and maintenance cost of hydrogen energy storage is shown in formula (3):

[0092]

[0093] Where, T is the running time 8760h; The operating and maintenance cost per unit charge and discharge volume of hydrogen energy storage; is the charging and discharging power of hydrogen energy storage in cluster i at time t, where positive values ​​represent discharging and negative values ​​represent charging;

[0094] The main grid electricity purchase cost is shown in formula (4):

[0095]

[0096] Where N con The number of branches connecting the busbar and the cluster, that is, the number of main network connection branches; is the real-time electricity price of the main network at time t; is the power of the main network tie branch l at time t;

[0097] The photovoltaic subsidy is shown in formula (5).

[0098]

[0099] Where C bt Provide photovoltaic subsidies for units; is the hydrogen energy storage output in cluster i at time t.

[0100] S4. Set the constraints of the upper-level planning model;

[0101] The constraints of the upper-level planning model include:

[0102] A cluster hydrogen energy storage grid connection location constraints:

[0103]

[0104] Where, is the hydrogen energy storage grid connection location, a value of 1 indicates that node i in cluster j is connected to hydrogen energy storage, and a value of 0 indicates that it is not connected to hydrogen energy storage;

[0105] B Power balance constraint:

[0106]

[0107] Where N j is the number of nodes contained in cluster j; N SI is the number of distribution network branches; is the load power of node j at time t; is the branch network loss at time t;

[0108] C node voltage constraint:

[0109]

[0110] Where, are the upper and lower limits of the voltage amplitude of node j in cluster i;

[0111] D power flow constraint:

[0112]

[0113] Where, P i , Q i The active and reactive power injected into node i; U i 、U j is the voltage amplitude of nodes i and j; G ij 、B ij is the admittance of branch ij; θ ij is the voltage phase angle of nodes i and j;

[0114] E main network interconnection branch interactive power constraints:

[0115]

[0116] Where, The upper and lower limits of the interactive power allowed to pass through the main network contact branch l;

[0117] Transmission power constraints of branches within group F:

[0118]

[0119] Where, N is the upper and lower limits of the transmission power of branch l within cluster i; I,i is the number of branches in cluster i.

[0120] S5. Construct the objective function of the lower-level control model based on the optimization goal of minimizing node deviation;

[0121] The lower model takes the minimum node voltage deviation as the objective function and the cluster hydrogen energy storage charging and discharging power as the decision variable, taking into account the system voltage stability and the source-load-storage power coordination ability. The objective function is shown in formula (12):

[0122]

[0123] Where N bus is the number of distribution network nodes; U i,t is the voltage of node i at time t; U N is the rated voltage.

[0124] S6. Set the constraints of the lower-level control model;

[0125] The constraints of the lower-level control model include:

[0126] A Cluster Hydrogen Energy Storage Supply and Demand Coordination Constraints:

[0127]

[0128] Where, It is the coordination index of cluster hydrogen energy storage supply and demand, showing the coordination ability of each cluster's source, load and storage adjustable resources with the system operation requirements; ΔP Ωx,t is the difference between the hydrogen storage energy and net power of cluster Ωx at time t; Φ e is the hydrogen energy storage supply and demand coordination indicator of cluster Ωx; It is an indicator of the coordination of hydrogen energy storage supply and demand in the distribution network as a whole;

[0129] B. Hydrogen energy storage charging and discharging power constraints:

[0130]

[0131] Where, is the maximum value of hydrogen energy storage charging and discharging power in cluster i;

[0132] C Hydrogen energy storage charging and discharging efficiency and state of charge constraints:

[0133]

[0134]

[0135] Where, SOC max , SOC min The upper and lower limits of the state of charge of hydrogen energy storage; SOC i,t is the state of charge of hydrogen energy storage in cluster i at time t; η i,t is the charge and discharge efficiency of hydrogen energy storage; η disc ,η char is the discharge and charge efficiency; It is the charge and discharge state, positive value indicates discharge, negative value indicates charge; SOC i,0 is the initial value of the state of charge.

[0136] In summary, the cluster division method proposed in the present invention comprehensively considers multiple indicators such as electrical distance modularity and cluster hydrogen energy storage supply and demand coordination, fully considers the uncertainty of source and load, and improves the source-load-storage coordination capability of each cluster, providing basic support for the reasonable access of hydrogen energy storage in the distribution network; the "distribution network-cluster-node" clustering and hierarchical planning strategy constructed by the present invention, the said two-layer model includes a planning model based on the upper-layer hydrogen energy storage grid connection location and capacity configuration, and a control model based on the lower-layer hydrogen energy storage charging and discharging power optimization, which overcomes the limitation of traditional hydrogen energy storage site selection being concentrated at the terminal node, and takes into account the source-load-storage coordination capability, thereby achieving a coordinated improvement in system economy and voltage stability; the present invention can optimize the configuration of the hydrogen energy storage system in an integrated manner.

Claims

1. A method for optimizing hydrogen energy storage configuration, characterized by: The following steps are involved: S1. Cluster division based on source-load-storage power coordination and uncertainty; S2. Introduce the cluster division results and construct a two-level planning model of distribution network-cluster-node clustering. The upper-level decision variables are the cluster's hydrogen energy storage capacity and grid connection location, and the lower-level decision variables are the charging and discharging power of the hydrogen energy storage in the cluster. S3. Construct the objective function of the upper-level planning model based on the optimization goal of minimizing the annual comprehensive cost of the distribution network; S4. Set the constraints of the upper-level planning model; S5. Construct the objective function of the lower-level control model based on the optimization goal of minimizing node deviation; S6. Set the constraints of the lower-level control model.

2. A hydrogen energy storage optimization configuration method according to claim 1, characterized in that: In S1, a cluster partitioning optimization model is constructed based on the partitioning characteristic indicators, which include electrical distance modularity, cluster active and reactive power balance, and source-load-storage coordination. The model is then solved under multiple source-load scenarios and robustness test conditions.

3. The hydrogen energy storage optimization configuration method according to claim 1, characterized in that: In S2, the distribution network-cluster-node clustering two-layer planning model includes an upper-layer planning model and a lower-layer control model. The hydrogen energy storage capacity and location information obtained by the upper-layer model based on the planning objectives will become the initial conditions of the lower-layer model. Through parameter transfer, the hydrogen energy storage charging and discharging power connected to each cluster in the lower-layer model is determined based on the upper-layer planning results; the upper model continues to optimize based on the optimization results of the lower-layer model, and finally determines the optimal solution of the distribution network-cluster-node clustering hierarchical planning model.

4. The method for optimizing hydrogen energy storage configuration according to claim 1, characterized in that: In S3, the upper model takes the minimum annual comprehensive cost of the distribution network as the objective function and the hydrogen energy storage capacity and location of each cluster as the decision variables; the objective function is shown in formula (1): minF=C inv +C om +C buy -C sub (1) Where, F is the annual comprehensive cost of the distribution network; C inv is the equivalent annual investment cost of hydrogen energy storage; C om is the annual operation and maintenance cost of hydrogen energy storage; C buy The cost of purchasing electricity from the main grid; C sub Subsidies for photovoltaics; The equivalent annual investment cost of hydrogen energy storage is shown in formula (2): Where N c is the number of clusters; r is the discount rate; y is the useful life of hydrogen energy storage; The unit capacity and unit power investment cost of hydrogen energy storage; The rated capacity and rated power of hydrogen energy storage configured for cluster i; The annual operation and maintenance cost of hydrogen energy storage is shown in formula (3): Where, T is the running time 8760h; The operating and maintenance cost per unit charge and discharge volume of hydrogen energy storage; is the charging and discharging power of hydrogen energy storage in cluster i at time t, where positive values ​​represent discharging and negative values ​​represent charging; The main grid electricity purchase cost is shown in formula (4): Where N con The number of branches connecting the busbar and the cluster, that is, the number of main network connection branches; is the real-time electricity price of the main network at time t; is the power of the main network tie branch l at time t; The photovoltaic subsidy is shown in the following formula (5): Where C bt Provide photovoltaic subsidies for units; is the hydrogen energy storage output within cluster i at time t; The hydrogen energy storage system includes a matching electrolyzer, a fuel cell and a converter.

5. The hydrogen energy storage optimization configuration method according to claim 1, characterized in that: In S4, the constraints of the upper-level planning model include cluster hydrogen energy storage grid connection location constraints, power balance constraints, node voltage constraints, power flow constraints, main network interconnection branch interaction power constraints, and intra-cluster branch transmission power constraints; Cluster hydrogen energy storage grid connection location constraints: Where, is the hydrogen energy storage grid connection location, a value of 1 indicates that node i in cluster j is connected to hydrogen energy storage, and a value of 0 indicates that it is not connected to hydrogen energy storage; Power balance constraints: Where N j is the number of nodes contained in cluster j; N SI is the number of distribution network branches; is the load power of node j at time t; is the branch network loss at time t; Node voltage constraints: Where, are the upper and lower limits of the voltage amplitude of node j in cluster i; Power flow constraints: Where, P i , Q i The active and reactive power injected into node i; U i 、U j is the voltage amplitude of nodes i and j; G ij 、B ij is the admittance of branch ij; θ ij is the voltage phase angle of nodes i and j; Interactive power constraints of the main network tie branch: Where, The upper and lower limits of the interactive power allowed to pass through the main network contact branch l; Transmission power constraints of branches within a group: Where, N is the upper and lower limits of the transmission power of branch l within cluster i; I,i is the number of branches in cluster i.

6. The hydrogen energy storage optimization configuration method according to claim 1, characterized in that: In S5, the lower model takes the minimum node voltage deviation as the objective function and the cluster hydrogen energy storage charging and discharging power as the decision variable, taking into account the system voltage stability and the source-load-storage power coordination ability. The objective function is shown in formula (12): Where N bus is the number of distribution network nodes; U i,t is the voltage of node i at time t; U N is the rated voltage.

7. The hydrogen energy storage optimization configuration method according to claim 1, characterized in that: In S6, the constraints of the lower-level control model include cluster hydrogen energy storage supply and demand coordination constraints, hydrogen energy storage charge and discharge power constraints, and hydrogen energy storage charge and discharge efficiency and charge state constraints; Constraints on the coordination of supply and demand of cluster hydrogen energy storage: Where, It is the coordination index of cluster hydrogen energy storage supply and demand, showing the coordination ability of each cluster's source, load and storage adjustable resources with the system operation requirements; ΔP Ωx,t is the difference between the hydrogen storage energy and net power of cluster Ωx at time t; Φ e is the hydrogen energy storage supply and demand coordination indicator of cluster Ωx; It is an indicator of the coordination of hydrogen energy storage supply and demand in the distribution network as a whole; Hydrogen energy storage charging and discharging power constraints: Where, is the maximum value of hydrogen energy storage charging and discharging power in cluster i; Hydrogen energy storage charging and discharging efficiency and state of charge constraints: Where, SOC max , SOC min The upper and lower limits of the state of charge of hydrogen energy storage; SOC i,t is the state of charge of hydrogen energy storage in cluster i at time t; η i,t The charging and discharging efficiency of hydrogen energy storage; η disc ,η char is the discharge and charge efficiency; It is the charge and discharge state, positive value indicates discharge, negative value indicates charge; SOC i,0 is the initial value of the state of charge.

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