Electric-hydrogen fusion energy system operation method, device, storage medium and electronic equipment

Abstract

The present application relates to an operation method, device, storage medium and electronic equipment of an electric-hydrogen fusion energy system, including: establishing an electric-hydrogen fusion energy system node network in a target area; confirming modularity index based on node electrical distance, modularity index based on hydrogen flow coefficient, functional index based on electric energy self-consistency rate and functional index based on hydrogen energy self-consistency rate; dividing to obtain the balance zone division result; establishing a typical energy supply architecture and an electric-hydrogen coupling model. The present application constructs a structural and functional division index system for the balance zone of an electric-hydrogen fusion energy system, and proposes a dynamic division method for the balance zone. It constructs a typical architecture of an electric-hydrogen fusion energy system based on the electric-hydrogen conversion relationship within the system, establishes a multi-energy coupling mathematical model to describe the interconnection topological relationship and electric-hydrogen interaction characteristics, and realizes the energy mutual assistance of electricity and hydrogen between energy systems and nodes in each electric-hydrogen fusion area, so as to increase the overall income of the system and promote the utilization efficiency of renewable energy.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an operation method, device, storage medium and electronic equipment of an electric-hydrogen fusion energy system. Background Art

[0002] With the continuous advancement of the construction of clean and low-carbon energy systems and new power systems, the rational development and utilization of new energy and the improvement of energy utilization efficiency are of great significance for the efficient consumption of new energy and the improvement of power supply capacity. For scenarios with a high proportion of new energy access, electrochemical energy storage can smooth out fluctuations in new energy output, strengthen the flexible adjustment function on the power supply side, and achieve power balance in short time scales of minutes and hours. However, its flexible adjustment capacity in long time scales is limited, and it is difficult to support the efficient consumption and comprehensive utilization of high-proportion new energy. The excellent characteristics of long-term storage of hydrogen energy can achieve large-capacity and long-term storage and utilization. Taking into account the physical properties of electricity and hydrogen energy, the electric-hydrogen fusion energy system will become an important means to support the power supply capacity and operating economy of new energy sites.

[0003] The electric-hydrogen fusion energy system includes core equipment such as distributed clean energy, electric-hydrogen multi-energy storage, electric-hydrogen-carbon multi-energy conversion equipment, and electric-hydrogen multi-loads. During operation, it is necessary to maintain a source-load balance in both electric energy and hydrogen energy. From the perspective of electric energy, considering the random fluctuation characteristics of the system source and load and the balance requirements of the power system, the regulation capability and balancing process centered on electricity can achieve short-time scale balance of system energy / power at the minute and hour levels. From the perspective of hydrogen energy, considering the physical properties of hydrogen energy storage over a long time scale and the supply and demand matching characteristics, the balance properties of hydrogen energy do not need to ensure real-time balance. The regulation capability centered on hydrogen energy can achieve long-time scale regulation and storage, which can serve as a beneficial supplement to the short-time scale balance and regulation centered on electricity. However, since the power generation resources are evenly distributed among the power loads and are scattered in space, it is impossible to ensure the multi-time and space scale balance of the electric-hydrogen fusion energy system.

[0004] Due to the impact of multiple factors such as weather factors, location characteristics, electricity prices, hydrogen prices, natural and social randomness on the value attributes of electric and hydrogen energy, the multi-energy interactive sharing of electric and hydrogen fusion energy systems faces multiple uncertainties.

[0005] At present, the research on the optimization operation of multi-energy systems at home and abroad is mostly focused on the multi-energy conversion characteristics and coupling mechanisms of electricity-heat, electricity-gas, and electricity-heat-gas. The coupling matrix from energy input to load output port is mainly used to represent the conversion, storage, distribution and transmission relationship between various energy forms. However, due to the complex interaction between the uncertainties of multiple terminals of electricity and hydrogen in time and space, the modeling of the coupling interaction characteristics of the integrated energy system of electricity and hydrogen fusion faces great challenges. Based on the scattered locations of distributed power generation resources, it is more complex to optimize and dispatch them in a unified and centralized manner. Domestic and foreign scholars use cluster optimization to coordinate and control distributed energy in order to achieve safe and reliable grid connection of high-penetration renewable energy, but lack of research on regional autonomy and inter-regional collaborative optimization operation of the electricity-hydrogen fusion energy system. In addition, energy sharing and mutual assistance is an effective means to alleviate the mismatch between uncertain renewable energy generation and electricity, but existing research mainly focuses on the multi-energy mutual assistance framework of microgrids, charging stations, power sharing and mutual assistance between producers and consumers, and hybrid renewable energy hydrogen suppliers, and usually ignores the hydrogen transmission delay effect and different time scale characteristics of the coordinated sharing and mutual assistance of electricity and hydrogen. Summary of the invention

[0006] In response to the above problems, the present application provides a method, device, storage medium and electronic device for operating an electric-hydrogen fusion energy system, which solves the technical problem that the relevant technology lacks consideration of the processing of intra-regional autonomy and inter-regional coordinated optimization operation of the electric-hydrogen fusion energy system.

[0007] In a first aspect, the present application provides a method for operating an electric-hydrogen fusion energy system, the method comprising:

[0008] Establish a node network of electric-hydrogen fusion energy systems in the target area;

[0009] According to the node network of the electric-hydrogen fusion energy system in the target area, confirm the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate of the electric-hydrogen fusion energy system in the target area;

[0010] According to the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate, the balance area division of the electric-hydrogen fusion regional energy system is performed to obtain the balance area division result of the electric-hydrogen fusion regional energy system;

[0011] According to the results of the balance zone division of the electric-hydrogen fusion regional energy system, a typical energy supply architecture and electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system are established.

[0012] In some embodiments, the method further comprises:

[0013] Collecting energy sharing management data of the electric-hydrogen fusion energy system in the target area at a long-term and short-term scales;

[0014] Establishing a long-time and space-scale electricity-hydrogen energy sharing management model based on the energy sharing management data at the long-time and space-scale and the electricity-hydrogen coupling model;

[0015] Obtaining the expected sharing amount of hydrogen according to the long-time and space-time scale electric-hydrogen energy sharing management model;

[0016] According to the energy sharing management data at the short-time and space scale, a short-time and space scale electricity and hydrogen energy sharing correction model is established;

[0017] Constraints are relaxed based on the expected hydrogen sharing amount and the short-time and space-scale electric hydrogen energy sharing correction model to obtain the actual hydrogen sharing amount on a short-time and space scale.

[0018] In some embodiments, the method further comprises:

[0019] According to the electricity-hydrogen coupling model, the long-time and space-time scale electricity-hydrogen energy sharing management model and the expected hydrogen sharing amount, the distributed pricing strategy of ADMM is adopted to perform distributed iteration of electricity and hydrogen mutual assistance to obtain the optimal solution of the electricity-hydrogen energy sharing price.

[0020] In some embodiments, the determining of the modularity index of the electric-hydrogen fusion energy system in the target area based on the node electrical distance includes:

[0021] According to the modularity formula:

[0022]

[0023] In the formula, k = ∑ m ∑ n W mn Represents the sum of the weights of all edges in the network; r m =∑ n W mn represents the sum of the weights of all edges connected to node m; r n =∑ m W mn represents the sum of the weights of all edges connected to node n; W mn is the weight of the edge connecting node m and node n; if node m and node n are in the same cluster, then δ(m,n) = 1, otherwise δ(m,n) = 0;

[0024] The node electrical distance is obtained through the sensitivity relationship between the node voltage and the changes in the injected power of other nodes, specifically:

[0025] ΔU=SP ΔP+S Q ΔQ

[0026] d mn =(S P,mm -S P,mn )+(S Q,mm -S Q,mn )

[0027] Where ΔU, ΔP, and ΔQ are the voltage amplitude change, node injected active power change, and node injected reactive power change, respectively; d mn Indicates the comprehensive impact of the power change of node n on node m; S P is the voltage-active power sensitivity matrix, and the element in the mth row and nth column in the matrix represents the influence of the active power change injected into node n on the voltage change of node m; S Q is the voltage-reactive sensitivity matrix, where the element in the mth row and nth column in the matrix represents the influence of the reactive power change injected into node n on the voltage change of node m;

[0028] Assume that the power distribution network has N nodes and define the electrical distance between node m and node n as for:

[0029]

[0030]

[0031] In the formula, is the weight of the edge connecting node m and node n; is the maximum value of the electrical distance between node m and node n; the formula:

[0032]

[0033] Substituting into the modularity formula:

[0034]

[0035] In the above equation, the modularity index ξ1 based on electrical distance can be obtained as follows:

[0036]

[0037] In some embodiments, the determining of the modularity index of the electric-hydrogen fusion energy system of the target area based on the hydrogen flow coefficient includes:

[0038] According to Kirchhoff's law and the node-branch connection matrix:

[0039]

[0040] In the formula, is the node-branch association matrix of the hydrogen energy network; h represents hydrogen, and b represents a branch; is the mass flow rate of hydrogen from node m to node n; is the hydrogen mass flow rate at node m;

[0041] The hydrogen mass flow and pressure square difference ΔΠ from node m to node n in the hydrogen energy network can be obtained: mn The following relations are satisfied:

[0042]

[0043]

[0044]

[0045] In the formula, Π mn is the square vector of air pressure in the hydrogen energy network; κ mn is the resistance coefficient of the branch connecting node m and node n;

[0046] By giving the initial estimated value of each node pressure, the hydrogen energy network flow equation is solved according to the Newton-Raphson method Node Jacobian matrix It can be expressed as:

[0047]

[0048] Solved

[0049] Defining the Hydrogen Flow Coefficient Substitute the calculation formula of modularity:

[0050]

[0051] In the equation, the modularity index ξ2 based on the hydrogen flow coefficient can be obtained as follows:

[0052]

[0053]

[0054] In some embodiments, the step of confirming the functional indicators of the target area's electric-hydrogen fusion energy system based on the electric energy self-consistency rate and the functional indicators based on the hydrogen energy self-consistency rate includes:

[0055] Functional index of electric energy self-consistency rate ξ3:

[0056]

[0057] Functional index of hydrogen energy self-consistency ξ4:

[0058]

[0059] In the formula, and are the output powers of photovoltaic, wind power and hydrogen gas turbine connected to node m respectively; and are the hydrogen production of the electrolyzer and the hydrogen storage of the hydrogen storage tank connected to node m respectively; and are the power consumption of the electric vehicle and the electric load connected to the node m respectively; and are the power consumption of the hydrogen vehicle and hydrogen load connected to node m respectively.

[0060] In some embodiments, the dividing of the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate includes:

[0061] According to the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency and the functional index based on hydrogen energy self-consistency, the local search complex network community partition FN algorithm is used to divide the balance zone of the electric-hydrogen fusion regional energy system.

[0062] In a second aspect, an electric-hydrogen fusion energy system operation device is provided, the device comprising:

[0063] The first establishment unit is used to establish a node network of the electric-hydrogen fusion energy system in the target area;

[0064] A confirmation unit, used to confirm, according to the node network of the electric-hydrogen fusion energy system in the target area, a modularity index based on node electrical distance, a modularity index based on hydrogen flow coefficient, a functional index based on electric energy self-consistency rate, and a functional index based on hydrogen energy self-consistency rate of the electric-hydrogen fusion energy system in the target area;

[0065] A division unit, used for dividing the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate, to obtain a result of dividing the balance area of ​​the electric-hydrogen fusion regional energy system;

[0066] The second establishing unit is used to establish a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system according to the balance zone division result of the electric-hydrogen fusion regional energy system.

[0067] In a third aspect, the computer program stored in the storage medium can be executed by one or more processors and can be used to implement the method for operating the electric-hydrogen fusion energy system as described in the first aspect above.

[0068] The fourth aspect includes a memory and a processor, wherein the memory stores a computer program, and the memory and the processor are communicatively connected to each other, and when the computer program is executed by the processor, the method for operating the electric-hydrogen fusion energy system as described in the first aspect above is executed.

[0069] The present application provides an electric-hydrogen fusion energy system operation method, device, storage medium and electronic device, including: establishing an electric-hydrogen fusion energy system node network of a target area; confirming the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency and the functional index based on hydrogen energy self-consistency of the electric-hydrogen fusion energy system of the target area according to the electric-hydrogen fusion energy system node network of the target area; dividing the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency and the functional index based on hydrogen energy self-consistency, and obtaining the balance area division result of the electric-hydrogen fusion regional energy system; establishing a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system according to the balance area division result of the electric-hydrogen fusion regional energy system. This application constructs a structural and functional division indicator system for the balance zone of the electric-hydrogen fusion energy system, and proposes a dynamic division method for the balance zone based on complex network theory. It also constructs a typical architecture of the electric-hydrogen fusion energy system based on the electric-hydrogen conversion relationship of each component in the system, and establishes a multi-energy coupling mathematical model to describe the interconnection topological relationship and electric-hydrogen interaction characteristics, thereby realizing energy mutual assistance of electricity and hydrogen between each electric-hydrogen fusion regional energy system and node, so as to increase the overall system income and promote the utilization efficiency of renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0071] Figure 1 A schematic diagram of a flow chart of an operation method of an electric-hydrogen fusion energy system provided in an embodiment of the present application;

[0072] Figure 2 A schematic diagram of a typical energy supply architecture of an electric-hydrogen fusion regional energy system provided in an embodiment of the present application;

[0073] Figure 3 A schematic diagram of the structure of an electric-hydrogen fusion energy system operating device provided in an embodiment of the present application;

[0074] Figure 4 A connection block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0075] The following will describe the implementation methods of the present application in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present application applies technical means to solve technical problems and achieve corresponding technical effects can be fully understood and implemented accordingly. The embodiments of the present application and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present application.

[0076] As can be seen from the background technology, the current research on the optimization operation of multi-energy systems at home and abroad is mostly focused on the multi-energy conversion characteristics and coupling mechanisms of electricity-heat, electricity-gas, and electricity-heat-gas. The coupling matrix from energy input to load output port is mainly used to represent the conversion, storage, distribution and transmission relationship between various energy forms. However, due to the complex interaction between the uncertainty of multiple terminals of electricity and hydrogen in time and space, the modeling of the coupling interaction characteristics of the integrated energy system of electricity and hydrogen fusion faces huge challenges. Based on the dispersed placement of distributed power generation resources, the complexity of unified and centralized optimization scheduling is relatively high. Domestic and foreign scholars use cluster optimization to coordinate and control distributed energy in order to achieve safe and reliable grid connection of high-penetration renewable energy, but lack of consideration of the research on regional autonomy and inter-regional collaborative optimization operation of the electric hydrogen fusion energy system. In addition, energy sharing and mutual assistance is an effective means to alleviate the mismatch between uncertain renewable energy generation and electricity, but existing research mainly focuses on the multi-energy mutual assistance framework of microgrids, charging stations, power sharing and mutual assistance between producers and consumers, and hybrid renewable energy hydrogen suppliers, and usually ignores the hydrogen transmission delay effect and different time scale characteristics of the collaborative sharing and mutual assistance of electricity and hydrogen.

[0077] In view of this, the present application provides an operation method, device, storage medium and electronic device for an electric-hydrogen fusion energy system, which solves the technical problem in the related art that the related art lacks consideration of the processing of the autonomous operation within the region and the coordinated optimization operation between regions of the electric-hydrogen fusion energy system.

[0078] Based on the electricity-hydrogen conversion relationship of each component in the system, a typical architecture of the electricity-hydrogen fusion energy system is constructed, and a multi-energy coupling mathematical model is established to describe the interconnection topology relationship and electricity-hydrogen interaction characteristics. A multilateral mutual assistance model considering long-term and spatial-temporal scale electricity-hydrogen sharing and short-term and spatial-temporal scale flexible electricity interaction is proposed to maximize the expected income of the electricity-hydrogen fusion regional energy system. In order to accelerate the convergence speed of complex multi-energy interaction and sharing problems, a solution method based on distributed electricity-hydrogen energy pricing strategy is proposed and the closed optimal price solution of the energy autonomy sub-problem is derived.

[0079] Embodiment 1

[0080] Figure 1 A schematic diagram of a flow chart of an operation method of an electric-hydrogen fusion energy system provided in an embodiment of the present application, such as Figure 1 As shown, the method includes:

[0081] S101. Establish a node network of the electric-hydrogen fusion energy system in the target area;

[0082] S102, according to the node network of the electric-hydrogen fusion energy system in the target area, confirming the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate of the electric-hydrogen fusion energy system in the target area;

[0083] S103, dividing the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate, and obtaining the balance area division result of the electric-hydrogen fusion regional energy system;

[0084] S104. According to the balance zone division results of the electric-hydrogen fusion regional energy system, a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system are established.

[0085] It should be noted that this application constructs a structural and functional division index system for the balance zone of the electric-hydrogen fusion energy system, and proposes a dynamic division method for the balance zone based on complex network theory. Based on the electric-hydrogen conversion relationship of each component in the system, a typical architecture of the electric-hydrogen fusion energy system is constructed, and a multi-energy coupling mathematical model is established to describe the interconnection topology relationship and electric-hydrogen interaction characteristics.

[0086] Specifically, considering the influence of the complexity of electric-hydrogen coupling and the characteristics of different time and space scales on the optimized operation of the electric-hydrogen fusion energy system, based on the electric-hydrogen synergistic conversion process within the electric-hydrogen fusion energy system, a structural division index of the balance area of ​​the electric-hydrogen fusion energy system is constructed to describe the density of connectivity between nodes, and a functional division index system is constructed to describe the degree of matching between the supply and demand of electric-hydrogen in the balance area. In combination with the theory of complex networks, a dynamic division method of the balance area of ​​the electric-hydrogen fusion energy system is proposed to achieve the energy mutual assistance of electricity and hydrogen between various electric-hydrogen fusion energy systems. Structurally, in order to ensure that the electrical and hydrogen flows of nodes within the balance area of ​​the electric-hydrogen fusion energy system are closely connected, and the electrical and hydrogen flows of nodes between balance areas are loosely connected, the modularity index based on the node electrical distance and the hydrogen flow coefficient is used to characterize the connection strength between the distribution network nodes; functionally, in order to ensure the balance of electricity and hydrogen energy under the access of high-penetration renewable distributed power sources, the degree of matching between the supply and demand of electric-hydrogen needs to be ensured when dividing the balance area, and its evaluation index is expressed by the self-consistency rate of electricity and the self-consistency rate of hydrogen energy.

[0087] In some embodiments, the determining of the modularity index of the electric-hydrogen fusion energy system in the target area based on the node electrical distance includes:

[0088] According to the modularity formula:

[0089]

[0090] In the formula, k = ∑ m ∑ n W mn Represents the sum of the weights of all edges in the network; r m =∑ n W mn represents the sum of the weights of all edges connected to node m; r n =∑ m W mn represents the sum of the weights of all edges connected to node n; W mn is the weight of the edge connecting node m and node n; if node m and node n are in the same cluster, then δ(m,n) = 1, otherwise δ(m,n) = 0;

[0091] It should be noted that in order to measure the cluster division structure strength of complex networks, Girvan and Newman proposed the concept and formula of modularity ξ.

[0092] The node electrical distance is obtained through the sensitivity relationship between the node voltage and the changes in the injected power of other nodes, specifically:

[0093] ΔU=S P ΔP+S Q ΔQ (2)

[0094] d mn=(S P,mm -S P,mn )+(S Q,mm -S Q,mn ) (3)

[0095] Where ΔU, ΔP, and ΔQ are the voltage amplitude change, node injected active power change, and node injected reactive power change, respectively; d mn Indicates the comprehensive impact of the power change of node n on node m; S P is the voltage-active power sensitivity matrix, and the element in the mth row and nth column in the matrix represents the influence of the active power change injected into node n on the voltage change of node m; S Q is the voltage-reactive sensitivity matrix, where the element in the mth row and nth column in the matrix represents the influence of the reactive power change injected into node n on the voltage change of node m;

[0096] It should be noted that the electrical distance is used to measure the tightness of the electrical coupling between two nodes in the network, and is obtained through the sensitivity relationship between the node voltage and the changes in the power injected into the other nodes.

[0097] Assume that the power distribution network has N nodes and define the electrical distance between node m and node n as for:

[0098]

[0099]

[0100] In the formula, is the weight of the edge connecting node m and node n; is the maximum value of the electrical distance between node m and node n; Substituting formula (5) into the modularity formula (1), the modularity structural index ξ1 based on electrical distance can be obtained as follows:

[0101]

[0102] It should be noted that in an actual power distribution network, the relationship between two nodes is not only related to the nodes themselves, but also to other surrounding nodes. Therefore, it can be assumed that the power distribution network has N nodes for calculation.

[0103] In some embodiments, the determining of the modularity index of the electric-hydrogen fusion energy system of the target area based on the hydrogen flow coefficient includes:

[0104] According to Kirchhoff's law and the node-branch connection matrix:

[0105]

[0106] In the formula, is the node-branch association matrix of the hydrogen energy network; h represents hydrogen, and b represents a branch; is the mass flow rate of hydrogen from node m to node n; is the hydrogen mass flow rate at node m;

[0107] It should be noted that according to Kirchhoff's law and the node-branch association matrix, the algebraic sum of the injected flow at any node in the hydrogen energy network is zero.

[0108] The hydrogen mass flow and pressure square difference ΔΠ from node m to node n in the hydrogen energy network can be obtained: mn The following relations are satisfied:

[0109]

[0110]

[0111]

[0112] In the formula, Π mn is the square vector of air pressure in the hydrogen energy network; κ mn is the resistance coefficient of the branch connecting node m and node n;

[0113] By giving the initial estimated value of each node pressure, the hydrogen energy network flow equation (7) is solved according to the Newton-Raphson method, and the node Jacobian matrix It can be expressed as:

[0114]

[0115] Solved

[0116] Defining the Hydrogen Flow Coefficient Substituting into the calculation formula (1) of modularity, the modularity index ξ2 based on the hydrogen flow coefficient can be obtained as follows:

[0117]

[0118]

[0119] It should be noted that the modularity index based on the hydrogen flow coefficient can reflect the consistency of the node hydrogen flow change when the node pressure fluctuates.

[0120] In some embodiments, the step of confirming the functional indicators of the target area's electric-hydrogen fusion energy system based on the electric energy self-consistency rate and the functional indicators based on the hydrogen energy self-consistency rate includes:

[0121] Functional index of electric energy self-consistency rate ξ3:

[0122]

[0123] Functional index of hydrogen energy self-consistency ξ4:

[0124]

[0125] In the formula, and are the output powers of photovoltaic, wind power and hydrogen gas turbine connected to node m respectively; and are the hydrogen production of the electrolyzer and the hydrogen storage of the hydrogen storage tank connected to node m respectively; and are the power consumption of the electric vehicle and the electric load connected to the node m respectively; and are the power consumption of the hydrogen vehicle and hydrogen load connected to node m respectively.

[0126] It should be noted that in order to give full play to the autonomous capacity of the balancing area and reduce the cross-regional flow of energy, the degree of matching between the supply and demand of electricity and hydrogen on both the source and load sides needs to reach a certain target value. Therefore, two functional indicators, the self-consistency rate of electricity in the balancing area ξ3 and the self-consistency rate of hydrogen, ξ4, are introduced to measure the supply and demand of electricity and hydrogen in the balancing area. Specifically, the self-consistency rate of electricity in the electric-hydrogen fusion energy system refers to its renewable energy supply capacity to meet the charging of electric vehicles and the refueling of hydrogen vehicles without relying on power supply from the power grid; the self-consistency rate of hydrogen can be defined as the ratio of the sum of the hydrogen production and hydrogen energy sharing of the electric-hydrogen fusion energy system to the hydrogen energy demand.

[0127] In some embodiments, the dividing of the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate includes:

[0128] According to the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency and the functional index based on hydrogen energy self-consistency, the local search complex network community partition FN algorithm is used to divide the balance zone of the electric-hydrogen fusion regional energy system.

[0129] It should be noted that, based on the two modularity indices and two functional indices in the previous part, the balance zone division index γ of the electric-hydrogen fusion energy system proposed in the present invention can be expressed as:

[0130] γ=a1ξ1+a2ξ2+a3ξ3+a4ξ4 (17)

[0131] In the formula, a1, a2, a3 and a4 are weight coefficients corresponding to each indicator. Based on the balance zone division index of the electric-hydrogen fusion energy system, the present invention adopts the complex network community partition algorithm (FN algorithm) of local search to divide the balance zone. The specific steps are as follows:

[0132] Initially, each node is regarded as a separate balance zone, and the balance zone partition index function γ is calculated according to formula (17).

[0133] For node m, randomly select node n from the remaining nodes to merge to form a new balance zone i(m,n), and calculate the balance zone partition index function γ' at this time; then calculate the change of the balance zone partition index function Δγ=γ'-γ in each combination; when Δγ reaches the maximum positive value, the corresponding two nodes i(m,n) at this time are divided into the same balance zone.

[0134] The newly formed balance area is regarded as a new node, and step (2) is repeated to implement the division process and form a new balance area division result.

[0135] When the nodes in the network can no longer be merged and the balance zone division index function γ reaches its maximum value, the balance zone division process is stopped and the optimal electric-hydrogen fusion regional energy system division result is obtained.

[0136] Furthermore, after obtaining the division results, a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system are established.

[0137] Specifically, Figure 2 As shown, it is a schematic diagram of a typical energy supply architecture of the electric-hydrogen fusion regional energy system disclosed in the embodiment of the present application; the energy supply architecture is driven by wind energy and solar energy, and is converted into electrical energy through photovoltaics and wind turbines. Renewable energy generation can be adjusted to charge electric vehicles, and can also provide power for electrolytic hydrogen production in electrolyzer stacks to achieve green hydrogen production. The hydrogen produced can provide kinetic energy for hydrogen-powered fuel vehicles, or be used for regenerative electricity of hydrogen gas turbines and fuel cells when power generation is insufficient to meet the uncertainty of user loads. The electrochemical energy storage on the distributed new energy side provides short-term storage flexibility for the electric-hydrogen fusion regional energy system, and due to its fast response characteristics, it can also alleviate the large fluctuations in the power of electrolytic hydrogen production caused by random wind power and photovoltaic unstable output, thereby reducing the life degradation cost of the electrolyzer; the hydrogen storage tank can store hydrogen for a long time, as a beneficial supplement to the flexible adjustment of electric energy storage on a short time scale. However, considering the complexity of electricity-hydrogen coupling and the impact of characteristics of different time and space scales on the optimal operation of the electricity-hydrogen fusion energy system, based on the internal electricity-hydrogen synergistic conversion process, energy mutual assistance of electricity and hydrogen is carried out between each electricity-hydrogen fusion regional energy system to increase the overall system income and promote the utilization efficiency of renewable energy.

[0138] The electric-hydrogen coupling model is established to describe the interactive conversion relationship between wind-solar energy input and hydrogen-electric energy output in the electric-hydrogen fusion regional energy system. and the steady-state variable vector Ω i,t The energy coupling vector reflects the energy conversion efficiency, distribution path and interconnection topology of the multi-energy flow cycle coupling in the hydrogen station. Here, each element of the matrix represents the steady-state conversion efficiency of the energy conversion equipment and the connection status between them; the steady-state variable vector includes the photovoltaic output power of the electric-hydrogen fusion regional energy system i Wind power output Electrolyzer stack hydrogen production mass flow Hydrogen storage tank hydrogen mass flow and hydrogen desorption mass flow rate Electrochemical energy storage charging power and discharge power Electrolytic power of electrolyzer Hydrogen storage tank compression power Hydrogen gas turbine output power and electric vehicle charging needs and hydrogen refueling demand for hydrogen-powered vehicles It is used to describe the production, storage, conversion and consumption of electricity and hydrogen in the electric-hydrogen fusion regional energy system, as shown below:

[0139]

[0140]

[0141]

[0142] In the formula, and is the reduction penalty factor corresponding to photovoltaic and wind power in the electric-hydrogen fusion regional energy system i; and It is a binary parameter, indicating whether photovoltaic and wind power are deployed in the electric-hydrogen fusion regional energy system; The hydrogen-to-electricity conversion efficiency of hydrogen gas turbines; and They are the charge and discharge efficiency of electrochemical energy storage; and They are the efficiency of hydrogen storage tank charging and discharging; is the calorific value of hydrogen; i and j represent different electric-hydrogen fusion regional energy systems; t represents the time; H is the set of the number of electric-hydrogen fusion regional energy systems, and the summation mark (H / i) represents other electric-hydrogen fusion regional energy systems j (different from i) in the set.

[0143] Based on the hydrogen-electricity conversion relationship of the electric-hydrogen fusion regional energy system, the total amount of electricity shared by the electric-hydrogen fusion regional energy system i Share total volume with hydrogen It can be expressed as:

[0144]

[0145]

[0146] Among them, (19a) represents the amount of electricity shared between the electric-hydrogen fusion regional energy system i and other systems, and (19b) represents the amount of hydrogen energy shared between the electric-hydrogen fusion regional energy system i and other systems.

[0147] In some embodiments, the method further comprises:

[0148] Collecting energy sharing management data of the electric-hydrogen fusion energy system in the target area at a long-term and short-term scales;

[0149] Establishing a long-time and space-scale electricity-hydrogen energy sharing management model based on the energy sharing management data at the long-time and space-scale and the electricity-hydrogen coupling model;

[0150] Obtaining the expected sharing amount of hydrogen according to the long-time and space-time scale electric-hydrogen energy sharing management model;

[0151] According to the energy sharing management data at the short-time and space scale, a short-time and space scale electricity and hydrogen energy sharing correction model is established;

[0152] Constraints are relaxed based on the expected hydrogen sharing amount and the short-time and space-scale electric hydrogen energy sharing correction model to obtain the actual hydrogen sharing amount on a short-time and space scale.

[0153] It should be noted that, based on the balance zone division, the typical energy supply architecture of the electric-hydrogen fusion regional energy system and the electric-hydrogen coupling model, the embodiment of the present application further proposes a multilateral mutual assistance model that takes into account the long-term and spatial scale electric-hydrogen sharing and the short-term and spatial scale flexible electric energy interaction, so as to maximize the expected income of the electric-hydrogen fusion regional energy system.

[0154] Specifically, in the long-term and spatial scale stage, the energy sharing problem of the electric-hydrogen fusion regional energy system can be expressed as a multi-time and spatial scale energy management model in view of the randomness of distributed new energy, the uncertainty of electric-hydrogen load demand, and the storage characteristics of electric-hydrogen energy at different time scales. In the energy transportation relationship, the shared hydrogen and electricity can be transported through hydrogen pipelines and local power lines in different time frames, respectively. However, due to the certain time delay of hydrogen transportation, the adjustment of power line sharing is more flexible and convenient than the adjustment of hydrogen energy shared by hydrogen pipelines. Therefore, the hydrogen sharing and electricity sharing between the electric-hydrogen fusion regional energy systems are first optimized over a long period of time with a weekly cycle and a daily interval. The long-term and spatial scale electric-hydrogen energy sharing aims to maximize the weekly revenue of the electric-hydrogen regional fusion energy system, considers the expected total cost associated with the uncertainty of distributed clean energy and electric-hydrogen load in the worst case, and determines the optimal sharing price and optimal sharing quantity of electric-hydrogen energy within the optimization period. Specifically, its objective function includes electricity and hydrogen sharing benefits, electric vehicle charging and hydrogen vehicle benefits, hydrogen transportation costs, electrolyzer stack operating costs due to electrolysis power fluctuations deviating from rated power, electrochemical energy storage life degradation costs, and operating costs caused by uncertainty in the worst-case probability distribution, as follows:

[0155]

[0156]

[0157]

[0158]

[0159] In the formula, x i,t and i,t They are the set of decision variables and the set of uncertain variables; and They represent the electricity-hydrogen transaction prices between the electricity-hydrogen fusion regional energy systems; and Represent the refueling costs of electric vehicles and hydrogen vehicles respectively; Δt long is the hydrogen sharing time interval, take Δt long = 1 day; c r and l r are the unit transportation cost and unit transportation distance of hydrogen respectively; c EC is the unit life degradation cost of the electrolyzer; is the number of electrolytic cells connected in series in the stack; fi is the objective function, min is to find the minimum value, sup represents the minimum upper bound, which is derived from the distribution rod, r is the transportation path, R ij is the set of paths connecting i and j, and the electrolysis power fluctuation deviates from the rated power PEC,ra , long-term and spatial-temporal scale electricity-hydrogen energy sharing optimization cycle T up .

[0160] Due to the frequent charge and discharge behavior of electrochemical energy storage, its aging is inevitable, so the battery linear life degradation model is used to quantify the life degradation cost; i,t The true probability distribution P i,t Usually ambiguous and can only be used with a series of historical data The empirical probability distribution obtained To approximate, E Pi,t is the probability of the worst case; and the unit costs of load shedding and renewable energy curtailment for electric and hydrogen vehicles, respectively; and They are the upstream and downstream reserve constraint capacities of hydrogen gas turbines and energy storage, respectively; and is the affine participation factor, take Energy storage power deviation The penalty coefficient is ; a piecewise linear generation cost function associated with uncertain variables is used to reduce the computational burden, where and are the cost coefficients of segment π in the segment set Π respectively; Represents the output active power of the hydrogen gas turbine.

[0161] Considering the worst-case scenario, the upper bound of the total operating cost can be approximately obtained by exchanging the maximum value and the sum. The first term on the right side of equation (21a) represents the expected penalty cost of load reduction and renewable energy in the worst case, and the last two terms represent the expected hydrogen gas turbine power generation cost and electrochemical energy storage adjustment cost in the worst case. By introducing the Lagrange multiplier Auxiliary variables n , conjugate parameter χ nπ By performing an equivalent linear programming reformulation, the operating cost caused by the uncertainty of the worst-case implementation in (21a) can be reformulated as (21b), where

[0162]

[0163]

[0164] The equipment operation constraints related to electricity, hydrogen production, storage, and conversion in the electric-hydrogen fusion regional energy system are as follows:

[0165]

[0166]

[0167]

[0168]

[0169]

[0170]

[0171]

[0172]

[0173]

[0174]

[0175]

[0176] In the formula, and are the energy and pressure states of the hydrogen storage tank, respectively, which must satisfy the upper and lower bounds allowed to ensure the safety of hydrogen storage; and Respectively represent the upper and lower limits of the energy and pressure state of the hydrogen storage tank; R, T i 、V i and are the ideal gas constant, standard storage temperature, volume and mass capacity, respectively. is the molar mass of hydrogen; the state of charge of the stored energy It should also be limited to its safe operating range At the same time, the input / output of various multi-energy conversion devices should not exceed the allowed upper limit (22j) represents the shared power between the electric-hydrogen fusion regional energy systems Should be lower than the line transmission capacity

[0177] In the short-term spatial and temporal scale stage, based on the continuously updated forecast of renewable energy and electric hydrogen load data, through rolling optimization, under the constraint of the optimal hydrogen sharing amount given by the long-term spatial and temporal scale electric hydrogen energy sharing energy management model, the power sharing amount is optimized again with a daily cycle and an hourly interval to maximize the daily revenue of the electric hydrogen regional fusion energy system, in order to cope with the instability of electric vehicle charging and hydrogen vehicle refueling demand, the uncertainty of distributed clean energy generation and the slow dynamic characteristics of shared hydrogen transportation. The specific objective function is as follows:

[0178]

[0179] In the formula, and They represent the short-term space-time sharing electricity price and electricity quantity between the electric-hydrogen fusion regional energy systems; Δt short and N T They represent the length and number of short time and space time intervals for rolling optimization respectively; and They represent the short-time and space charging and discharging power of electrochemical energy storage, respectively; is the short-term space-time electrolysis power of the electrolyzer; and similar, is the operating cost caused by the short-term and spatial uncertainty of distributed clean energy and electric hydrogen loads and transportation delays; only the optimal decision for the current time interval t0 will be realized, and the real-time fuzzy set Will be updated continuously as the scrolling progresses. h ,Ψ EC and BES They respectively represent the deviation coefficients of long-term and short-term space-time hydrogen trading volume, electrolysis power of electrolyzer, and energy storage charging and discharging power.

[0180] Based on the optimal hydrogen sharing amount optimized by the long-time and space-time electric hydrogen energy sharing energy management model, the deviation between the actual hydrogen sharing amount and the expected hydrogen sharing amount in the short-time and space-time scale is considered, and a certain proportional coefficient is used to relax the hydrogen sharing amount in the short-time and space-time scale, as follows:

[0181]

[0182] In the formula, is the actual amount of hydrogen shared over a short time and space scale; The expected amount of hydrogen shared by optimizing the long-term spatial and temporal scale; τ h is the relaxation ratio coefficient. The remaining constraints are the same as those in the day-ahead optimization model and will not be described here.

[0183] In some embodiments, the method further comprises:

[0184] According to the electricity-hydrogen coupling model, the long-time and space-time scale electricity-hydrogen energy sharing management model and the expected hydrogen sharing amount, the distributed pricing strategy of ADMM is adopted to perform distributed iteration of electricity and hydrogen mutual assistance to obtain the optimal solution of the electricity-hydrogen energy sharing price.

[0185] It should be noted that the embodiments of the present application, based on the division of balance zones, typical energy supply architecture of electric-hydrogen fusion regional energy systems, electric-hydrogen coupling models, and long-time and space-time scale electric-hydrogen sharing and short-time and space-time scale flexible electric energy interaction, further propose a solution method based on distributed electric-hydrogen energy pricing strategy in order to accelerate the convergence speed of complex multi-energy interaction and sharing problems, and derive the closed optimal price solution to the energy autonomy sub-problem.

[0186] Specifically, a distributed pricing strategy based on ADMM is used to decompose the complex electricity-hydrogen sharing problem into multiple local multi-energy management sub-problems to reduce the heavy computational burden and protect information privacy. Taking the long-term spatial and temporal scale stage as an example, the goal of the electricity-hydrogen energy mutual assistance is to maximize the weekly revenue of the electricity-hydrogen regional fusion energy system, as follows:

[0187]

[0188]

[0189]

[0190] In formula (26) and (27), the mutual balance constraints of electricity and hydrogen energy are expressed. The auxiliary variable of the mutual balance between hydrogen and electricity in the electric-hydrogen fusion energy system is introduced. and Re-express equation (26) and equation (27):

[0191]

[0192]

[0193]

[0194]

[0195]

[0196]

[0197] Establishing the augmented Lagrangian function Relax the consistency constraints as follows:

[0198]

[0199]

[0200] In the formula, The local augmented Lagrangian function for the electric-hydrogen fusion regional energy system; and represents the set of auxiliary variables and Lagrange multipliers corresponding to constraints (28a) and (28d); ρ e and ρ h represents the penalty factor, and They respectively represent the electricity-hydrogen transaction prices between electricity-hydrogen fusion regional energy systems.

[0201] The distributed pricing strategy based on ADMM describes the distributed iterative process of mutual assistance between electricity and hydrogen, in which the key steps are summarized as follows:

[0202] First, the local decision variables and auxiliary variables are updated:

[0203] Using the and To solve the local subproblem (29b), we can obtain the local decision variables for the current iteration. According to x φ-1 , σ φ-1 and constraints (28c) and (28f), the auxiliary variables can be updated by solving (30b)

[0204]

[0205]

[0206] Due to the energy mutual auxiliary variable and Only with and coupling, so (30b) can be decomposed into:

[0207]

[0208]

[0209] In the formula, is the dual variable set, and the closed-form solution of the auxiliary variables is derived using the Karush-Kuhn-Tucker (KKT) condition as follows:

[0210]

[0211]

[0212] where L0 is the Lagrangian function of problem (31a). The closed-form solution of the auxiliary variables at iteration φ can be derived from the KKT condition, as shown in (33):

[0213]

[0214] Next is the update of the Lagrange multiplier:

[0215] The Lagrange multiplier, i.e. the shadow price of multi-energy sharing, is calculated as shown in formula (34a). The closed solution of energy sharing price can be obtained by combining formula (33) and formula (34a):

[0216]

[0217]

[0218] The iterative process stops until both the primal and dual residuals converge to within the allowed tolerance.

[0219] In summary, new energy has strong randomness and volatility characteristics, and its high proportion of access puts higher requirements on the flexible adjustment ability of the power system. In the scenario of high proportion of new energy access, most studies focus on the role of electrochemical energy storage in smoothing the fluctuation of new energy output and ensuring the consumption of new energy, but lack research on the long-term storage characteristics of hydrogen energy; due to the strong local characteristics of local distribution and use of hydrogen energy, the unified division of distributed clean energy, electric hydrogen multi-energy conversion equipment, and electric hydrogen multi-energy storage equipment, combined with different energy flow characteristics, is conducive to the local consumption of distributed clean energy, but the existing research on the autonomous balance of electric hydrogen zoning mostly uses a single indicator for cluster division, and lacks a comprehensive indicator that considers the degree of coupling between hydrogen flow and electrical connection. In addition, the traditional multi-energy system mutual optimization is based on the incentive strategy, auction mechanism, strategic supply behavior, etc. of contract theory to study various energy sharing modes such as electricity-heat, electricity-gas, electricity-heat-gas, and heat-cold-gas, but does not consider the long-term hydrogen energy mutual assistance scheme and the short-term electricity interaction scheme at the same time, resulting in poor economic results. Therefore, the present invention proposes structural indicators of hydrogen energy network based on hydrogen flow coefficient by analogy with the electrical distance characteristics of the power network, and simultaneously considers the functional indicators of the balance matching of supply and demand of electric-hydrogen energy, thereby realizing the balance zone division of the electric-hydrogen fusion energy system; based on the regulation characteristics of hydrogen long-term energy storage, transmission network and key equipment, a typical architecture and multi-energy coupling model of the electric-hydrogen fusion regional energy system are constructed; considering the storage characteristics of electric-hydrogen energy in different time and space, the sharing and mutual assistance of electric-hydrogen fusion is considered at a long time and space scale, and the electrical interaction at a short time and space scale is constrained according to the optimized hydrogen sharing amount, a multi-time and space scale optimization operation method of the electric-hydrogen fusion regional energy system with the goal of maximizing the total cycle revenue and a solution method based on the distributed electric-hydrogen energy pricing strategy are proposed, which accelerates the convergence speed of the multi-energy sharing problem.

[0220] In summary, an embodiment of the present application provides a method for operating an electric-hydrogen fusion energy system, the method comprising: establishing an electric-hydrogen fusion energy system node network of a target area; confirming, based on the electric-hydrogen fusion energy system node network of the target area, a modularity index based on a node electrical distance, a modularity index based on a hydrogen flow coefficient, a functional index based on an electric energy self-consistency rate, and a functional index based on an hydrogen energy self-consistency rate of the electric-hydrogen fusion energy system of the target area; dividing the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on a node electrical distance, the modularity index based on a hydrogen flow coefficient, the functional index based on an electric energy self-consistency rate, and the functional index based on an hydrogen energy self-consistency rate, and obtaining a balance area division result of the electric-hydrogen fusion regional energy system; establishing a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system according to the balance area division result of the electric-hydrogen fusion regional energy system. This application constructs a structural and functional division indicator system for the balance zone of the electric-hydrogen fusion energy system, and proposes a dynamic division method for the balance zone based on complex network theory. It also constructs a typical architecture of the electric-hydrogen fusion energy system based on the electric-hydrogen conversion relationship of each component in the system, and establishes a multi-energy coupling mathematical model to describe the interconnection topological relationship and electric-hydrogen interaction characteristics, thereby realizing energy mutual assistance of electricity and hydrogen between each electric-hydrogen fusion regional energy system and node, so as to increase the overall system income and promote the utilization efficiency of renewable energy.

[0221] Embodiment 2

[0222] Based on the operating method of the electric-hydrogen fusion energy system disclosed in the above embodiment of the present invention, Figure 3 Specifically disclosed is an electric-hydrogen fusion energy system operating device that applies the electric-hydrogen fusion energy system operating method.

[0223] like Figure 3 As shown, an embodiment of the present invention discloses an electric-hydrogen fusion energy system operation device, the device comprising:

[0224] The first establishing unit 301 is used to establish a node network of an electric-hydrogen fusion energy system in a target area;

[0225] A confirmation unit 302 is used to confirm, according to the node network of the electric-hydrogen fusion energy system in the target area, a modularity index based on node electrical distance, a modularity index based on hydrogen flow coefficient, a functional index based on electric energy self-consistency rate, and a functional index based on hydrogen energy self-consistency rate of the electric-hydrogen fusion energy system in the target area;

[0226] The division unit 303 is used to divide the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate, and obtain the balance area division result of the electric-hydrogen fusion regional energy system;

[0227] The second establishing unit 304 is used to establish a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system according to the balance zone division result of the electric-hydrogen fusion regional energy system.

[0228] In some embodiments, the apparatus further comprises:

[0229] A collection unit 305 is used to collect energy sharing management data of the electric-hydrogen fusion energy system in the target area at a long-term and short-term scales;

[0230] The third establishing unit 306 is used to establish a long-time and space-scale electricity-hydrogen energy sharing management model according to the energy sharing management data under the long-time and space-scale and the electricity-hydrogen coupling model;

[0231] A calculation unit 307 is used to obtain the expected sharing amount of hydrogen according to the long-time and space-time scale electricity-hydrogen energy sharing management model;

[0232] The fourth establishing unit 308 is used to establish a short-time and space scale electricity-hydrogen energy sharing correction model according to the energy sharing management data under the short-time and space scale;

[0233] The constraint unit 309 is used to relax the constraints according to the expected hydrogen sharing amount and the short-time and space-scale electric hydrogen energy sharing correction model to obtain the actual hydrogen sharing amount on the short-time and space scale.

[0234] In some embodiments, the apparatus further comprises:

[0235] The solving unit 310 is used to perform distributed iteration of the mutual assistance of electricity and hydrogen using the distributed pricing strategy of ADMM according to the electricity-hydrogen coupling model, the long-time and space-time scale electricity-hydrogen energy sharing management model and the expected sharing amount of hydrogen, so as to obtain the optimal solution of the electricity-hydrogen energy sharing price.

[0236] For the specific working processes of the first establishing unit 301, the confirming unit 302, the dividing unit 303, the second establishing unit 304, the collecting unit 305, the third establishing unit 306, the calculating unit 307, the fourth establishing unit 308, the constraint unit 309 and the solving unit 310 in the electric-hydrogen fusion energy system operating device disclosed in the above embodiment of the present invention, please refer to the corresponding contents in the electric-hydrogen fusion energy system operating method disclosed in the above embodiment of the present invention, which will not be repeated here.

[0237] In summary, an embodiment of the present application provides an electric-hydrogen fusion energy system operation device, which includes: a first establishment unit, used to establish an electric-hydrogen fusion energy system node network of a target area; a confirmation unit, used to confirm the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency, and the functional index based on hydrogen energy self-consistency of the electric-hydrogen fusion energy system of the target area according to the electric-hydrogen fusion energy system node network of the target area; a division unit, used to divide the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency, and the functional index based on hydrogen energy self-consistency, and obtain the balance area division result of the electric-hydrogen fusion regional energy system; a second establishment unit, used to establish a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system according to the balance area division result of the electric-hydrogen fusion regional energy system. This application constructs a structural and functional division indicator system for the balance zone of the electric-hydrogen fusion energy system, and proposes a dynamic division method for the balance zone based on complex network theory. It also constructs a typical architecture of the electric-hydrogen fusion energy system based on the electric-hydrogen conversion relationship of each component in the system, and establishes a multi-energy coupling mathematical model to describe the interconnection topological relationship and electric-hydrogen interaction characteristics, thereby realizing energy mutual assistance of electricity and hydrogen between each electric-hydrogen fusion regional energy system and node, so as to increase the overall system income and promote the utilization efficiency of renewable energy.

[0238] Embodiment 3

[0239] This embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a disk, an optical disk, a server, an App application store, etc., on which a computer program is stored. When the computer program is executed by a processor, the method steps of the first embodiment can be implemented, and this embodiment will not be repeated here.

[0240] Embodiment 4

[0241] Figure 4 A connection block diagram of an electronic device 400 provided in an embodiment of the present application, such as Figure 4 As shown, the electronic device 400 may include: a processor 401 , a memory 402 , a multimedia component 403 , an input / output (I / O) interface 404 , and a communication component 405 .

[0242] The processor 401 is used to execute all or part of the steps in the method for operating the electric-hydrogen fusion energy system in Embodiment 1. The memory 402 is used to store various types of data, which may include instructions of any application or method in the electronic device, and data related to the application.

[0243] The processor 401 can be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and is used to execute the operation method of the electric-hydrogen fusion energy system in the above-mentioned embodiment 1.

[0244] The memory 402 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0245] The multimedia component 403 may include a screen and an audio component, the screen may be a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, and the microphone is used to receive external audio signals. The received audio signal may be further stored in a memory or sent via a communication component. The audio component also includes at least one speaker for outputting audio signals.

[0246] The I / O interface 404 provides an interface between the processor 401 and other interface modules, which may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons.

[0247] The communication component 405 is used for wired or wireless communication between the electronic device 400 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 405 can include: Wi-Fi module, Bluetooth module, NFC module.

[0248] In summary, the present application provides an electric-hydrogen fusion energy system operation method, device, storage medium and electronic device, the method comprising: establishing an electric-hydrogen fusion energy system node network of a target area; confirming the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency and the functional index based on hydrogen energy self-consistency of the electric-hydrogen fusion energy system of the target area according to the electric-hydrogen fusion energy system node network of the target area; dividing the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency and the functional index based on hydrogen energy self-consistency, and obtaining the balance area division result of the electric-hydrogen fusion regional energy system; establishing a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system according to the balance area division result of the electric-hydrogen fusion regional energy system. This application constructs a structural and functional division indicator system for the balance zone of the electric-hydrogen fusion energy system, and proposes a dynamic division method for the balance zone based on complex network theory. It also constructs a typical architecture of the electric-hydrogen fusion energy system based on the electric-hydrogen conversion relationship of each component in the system, and establishes a multi-energy coupling mathematical model to describe the interconnection topological relationship and electric-hydrogen interaction characteristics, thereby realizing energy mutual assistance of electricity and hydrogen between each electric-hydrogen fusion regional energy system and node, so as to increase the overall system income and promote the utilization efficiency of renewable energy.

[0249] In the several embodiments provided in the present application, it should be understood that the disclosed method can also be implemented in other ways. The method embodiments described above are merely illustrative.

[0250] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0251] Although the implementation methods disclosed in this application are as above, the above contents are only the implementation methods adopted for facilitating the understanding of this application, and are not intended to limit this application. Any technician in the technical field to which this application belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in this application, but the scope of patent protection of this application shall still be based on the scope defined in the attached claims.

Claims

1. A method for operating an electric-hydrogen fusion energy system, characterized in that: The method comprises: Establish a node network of electric-hydrogen fusion energy systems in the target area; According to the node network of the electric-hydrogen fusion energy system in the target area, confirm the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate of the electric-hydrogen fusion energy system in the target area; The method of confirming the modularity index of the electric-hydrogen fusion energy system in the target area based on the node electrical distance includes: According to the modularity formula: In the formula, ξ is the modularity index, k = ∑ m ∑ n W mn Represents the sum of the weights of all edges in the network; r m =∑ n W mn represents the sum of the weights of all edges connected to node m; r n =∑ m W mn represents the sum of the weights of all edges connected to node n; W mn is the weight of the edge connecting node m and node n; if node m and node n are in the same cluster, then δ(m,n) = 1, otherwise δ(m,n) = 0; The node electrical distance is obtained through the sensitivity relationship between the node voltage and the changes in the injected power of other nodes, specifically: ΔU= S P ΔP+ S Q ΔQ; d mn =(S P,mm - S P,mn )+(S Q,mm - S Q,mn ); Where ΔU, ΔP, and ΔQ are the voltage amplitude change, node injected active power change, and node injected reactive power change, respectively; d mn Indicates the comprehensive impact of the power change of node n on node m; S P is the voltage-active power sensitivity matrix, and the element in the mth row and nth column in the matrix represents the influence of the active power change injected into node n on the voltage change of node m; S Q is the voltage-reactive sensitivity matrix, where the element in the mth row and nth column in the matrix represents the influence of the reactive power change injected into node n on the voltage change of node m; Assume that the power distribution network has N nodes and define the electrical distance between node m and node n as for: In the formula, is the weight of the edge connecting node m and node n; is the maximum value of the electrical distance between node m and node n; the formula: Substituting into the modularity formula: In the above equation, the modularity index ξ1 based on electrical distance can be obtained as follows: The method for determining the modularity index of the electric-hydrogen fusion energy system in the target area based on the hydrogen flow coefficient includes: According to Kirchhoff's law and the node-branch connection matrix: In the formula, is the node-branch association matrix of the hydrogen energy network; h represents hydrogen, and b represents a branch; is the mass flow rate of hydrogen from node m to node n; is the hydrogen mass flow rate at node m; The hydrogen mass flow and pressure square difference ΔΠ from node m to node n in the hydrogen energy network can be obtained: mn The following relations are satisfied: In the formula, Π mn is the square vector of air pressure in the hydrogen energy network; κ mn is the resistance coefficient of the branch connecting node m and node n; By giving the initial estimated value of each node pressure, the hydrogen energy network flow equation is solved according to the Newton-Raphson method Node Jacobian matrix It can be expressed as: Solved Defining the Hydrogen Flow Coefficient Substitute the calculation formula of modularity: In the equation, the modularity index ξ2 based on the hydrogen flow coefficient can be obtained as follows: The functional indicators based on the self-consistency rate of electric energy and the functional indicators based on the self-consistency rate of hydrogen energy of the electric-hydrogen fusion energy system of the target area are confirmed, including: Functional index of electric energy self-consistency rate ξ3: Functional index of hydrogen energy self-consistency ξ4: In the formula, and are the output powers of photovoltaic, wind power and hydrogen gas turbine connected to node m respectively; and are the hydrogen production of the electrolyzer and the hydrogen storage of the hydrogen storage tank connected to node m respectively; and are the power consumption of the electric vehicle and the electric load connected to the node m respectively; and are the power consumption of hydrogen vehicles and hydrogen loads connected to node m respectively; According to the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate, the balance area division of the electric-hydrogen fusion regional energy system is performed to obtain the balance area division result of the electric-hydrogen fusion regional energy system, including: According to the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency rate and the functional index based on hydrogen energy self-consistency rate, the local search complex network community partition FN algorithm is used to divide the balance area of ​​the electric-hydrogen fusion regional energy system; According to the results of the balance zone division of the electric-hydrogen fusion regional energy system, a typical energy supply architecture and electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system are established.

2. The method according to claim 1, characterized in that Also includes: Collecting energy sharing management data of the electric-hydrogen fusion energy system in the target area at a long-term and short-term scales; Establishing a long-time and space-scale electricity-hydrogen energy sharing management model based on the energy sharing management data at the long-time and space-scale and the electricity-hydrogen coupling model; Obtaining the expected sharing amount of hydrogen according to the long-time and space-scale electric-hydrogen energy sharing management model; According to the energy sharing management data at the short-time and space scale, a short-time and space scale electricity and hydrogen energy sharing correction model is established; Constraints are relaxed based on the expected hydrogen sharing amount and the short-time and space-scale electric hydrogen energy sharing correction model to obtain the actual hydrogen sharing amount on a short-time and space scale.

3. The method according to claim 2, characterized in that Also includes: According to the electricity-hydrogen coupling model, the long-time and space-time scale electricity-hydrogen energy sharing management model and the expected hydrogen sharing amount, the distributed pricing strategy of ADMM is adopted to perform distributed iteration of electricity and hydrogen mutual assistance to obtain the optimal solution of the electricity-hydrogen energy sharing price.

4. An electric-hydrogen fusion energy system operating device, characterized in that: The device comprises: The first establishment unit is used to establish a node network of the electric-hydrogen fusion energy system in the target area; A confirmation unit, used to confirm, according to the node network of the electric-hydrogen fusion energy system in the target area, a modularity index based on node electrical distance, a modularity index based on hydrogen flow coefficient, a functional index based on electric energy self-consistency rate, and a functional index based on hydrogen energy self-consistency rate of the electric-hydrogen fusion energy system in the target area; The method of confirming the modularity index of the electric-hydrogen fusion energy system in the target area based on the node electrical distance includes: According to the modularity formula: In the formula, ξ is the modularity index, k = ∑ m ∑ n W mn Represents the sum of the weights of all edges in the network; r m =∑ n W mn represents the sum of the weights of all edges connected to node m; r n =∑ m W mn represents the sum of the weights of all edges connected to node n; W mn is the weight of the edge connecting node m and node n; if node m and node n are in the same cluster, then δ(m,n) = 1, otherwise δ(m,n) = 0; The node electrical distance is obtained through the sensitivity relationship between the node voltage and the changes in the injected power of other nodes, specifically: ΔU= S P ΔP+ S Q ΔQ; d mn =(S P,mm - S P,mn )+(S Q,mm - S Q,mn ); Where ΔU, ΔP, and ΔQ are the voltage amplitude change, node injected active power change, and node injected reactive power change, respectively; d mn Indicates the comprehensive impact of the power change of node n on node m; S P is the voltage-active power sensitivity matrix, and the element in the mth row and nth column in the matrix represents the influence of the active power change injected into node n on the voltage change of node m; S Q is the voltage-reactive sensitivity matrix, where the element in the mth row and nth column in the matrix represents the influence of the reactive power change injected into node n on the voltage change of node m; Assume that the power distribution network has N nodes and define the electrical distance between node m and node n as for: In the formula, is the weight of the edge connecting node m and node n; is the maximum value of the electrical distance between node m and node n; the formula: Substituting into the modularity formula: In the above equation, the modularity index ξ1 based on electrical distance can be obtained as follows: The method for determining the modularity index of the electric-hydrogen fusion energy system in the target area based on the hydrogen flow coefficient includes: According to Kirchhoff's law and the node-branch connection matrix: In the formula, is the node-branch association matrix of the hydrogen energy network; h represents hydrogen, and b represents a branch; is the mass flow rate of hydrogen from node m to node n; is the hydrogen mass flow rate at node m; The hydrogen mass flow and pressure square difference ΔΠ from node m to node n in the hydrogen energy network can be obtained: mn The following relations are satisfied: In the formula, Π mn is the square vector of air pressure in the hydrogen energy network; κ mn is the resistance coefficient of the branch connecting node m and node n; By giving the initial estimated value of each node pressure, the hydrogen energy network flow equation is solved according to the Newton-Raphson method Node Jacobian matrix It can be expressed as: Solved Defining the Hydrogen Flow Coefficient Substitute the calculation formula of modularity: In the equation, the modularity index ξ2 based on the hydrogen flow coefficient can be obtained as follows: The functional indicators based on the self-consistency rate of electric energy and the functional indicators based on the self-consistency rate of hydrogen energy of the electric-hydrogen fusion energy system of the target area are confirmed, including: Functional index of electric energy self-consistency rate ξ3: Functional index of hydrogen energy self-consistency ξ4: In the formula, and are the output powers of photovoltaic, wind power and hydrogen gas turbine connected to node m respectively; and are the hydrogen production of the electrolyzer and the hydrogen storage of the hydrogen storage tank connected to node m respectively; and are the power consumption of the electric vehicle and the electric load connected to the node m respectively; and are the power consumption of hydrogen vehicles and hydrogen loads connected to node m respectively; A division unit is used to divide the balance area of ​​the electric-hydrogen fusion regional energy system according to the modularity index based on the node electrical distance, the modularity index based on the hydrogen flow coefficient, the functional index based on the electric energy self-consistency rate, and the functional index based on the hydrogen energy self-consistency rate, and obtain the balance area division result of the electric-hydrogen fusion regional energy system, including: According to the modularity index based on node electrical distance, the modularity index based on hydrogen flow coefficient, the functional index based on electric energy self-consistency rate and the functional index based on hydrogen energy self-consistency rate, the local search complex network community partition FN algorithm is used to divide the balance area of ​​the electric-hydrogen fusion regional energy system; The second establishing unit is used to establish a typical energy supply architecture and an electric-hydrogen coupling model of the electric-hydrogen fusion regional energy system according to the balance zone division result of the electric-hydrogen fusion regional energy system.

5. A storage medium, characterized in that: The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the method for operating the electric-hydrogen fusion energy system as described in any one of claims 1 to 3.

6. An electronic device, characterized in that: It comprises a memory and a processor, wherein a computer program is stored in the memory, and the memory and the processor are communicatively connected with each other, and when the computer program is executed by the processor, the method for operating the electric-hydrogen fusion energy system as claimed in any one of claims 1 to 3 is executed.

Images