Method, system and equipment for locating and sizing hydrogen fuel cell all-in-one machine based on thermoelectric property and medium

Abstract

The invention relates to the field of distributed hydrogen fuel cell locating and sizing optimization, in particular to a thermoelectric property-based locating and sizing method, system and equipment for a hydrogen fuel cell all-in-one machine and a medium. The method comprises the following steps: constructing an upper layer optimization model and a lower layer optimization model based on multi-dimensional operation influence factors of the position and the capacity of the hydrogen fuel cell all-in-one machine on the medium and low voltage power distribution network; solving the upper-layer optimization model based on the operation data of the medium-voltage power distribution network to obtain a first solving result, and solving the lower-layer optimization model based on the first solving result and the operation data of the low-voltage power distribution network to obtain a second solving result, according to the first solving result and the second solving result, the hydrogen fuel cell all-in-one machine is subjected to constant volume and arrangement, the comprehensive utilization rate and the energy conversion efficiency of the hydrogen fuel cell all-in-one machine are remarkably improved, and intelligent and collaborative optimization operation of a distributed energy system in the electric heating integration direction is achieved.

Description

Technical Field

[0001] This invention relates to the field of distributed hydrogen fuel cell site selection and capacity optimization, specifically to a site selection and capacity optimization method, system, equipment, and medium for an integrated hydrogen fuel cell based on thermoelectric characteristics. Background Technology

[0002] Currently, medium- and low-voltage distribution networks face multiple challenges, such as increased access to renewable energy sources, decreased voltage stability, and increased line losses, necessitating more efficient energy allocation solutions to improve system operational quality. Traditional distribution network site selection and capacity configuration methods often prioritize the characteristics of the power grid itself, neglecting the impact of combined heat and power (CHP) systems on regional energy efficiency and failing to fully leverage the advantages of multi-energy complementarity. Hydrogen fuel cells, on the other hand, are clean, efficient, and flexible, capable of connecting to both the power grid and the heating network, making them an ideal platform for achieving synergistic optimization of heat and power.

[0003] However, current hydrogen fuel cell deployments generally suffer from shortcomings such as failing to simultaneously consider their impact on the power grid and heating network, having a single optimization objective in the model, and lacking dynamic adaptability in capacity configuration. Existing research is often limited to a single point in time and ignores the impact of user load fluctuations and uncertainties in distributed generation, resulting in optimization results that lack feasibility and adaptability. Therefore, how to maximize the comprehensive utilization efficiency of hydrogen fuel cells, promote the consumption of new energy sources, and enhance the safety and economy of power distribution network operation is an urgent problem to be solved. Summary of the Invention

[0004] To address the technical problems existing in the site selection and capacity configuration of current power distribution networks, this invention proposes a site selection and capacity determination method for an integrated hydrogen fuel cell unit based on thermoelectric characteristics, comprising: An upper-level optimization model is constructed based on the location and capacity of the integrated hydrogen fuel cell unit to influence the multi-dimensional operation of the medium-voltage power distribution network, and a lower-level optimization model is constructed based on the location and capacity of the integrated hydrogen fuel cell unit to influence the multi-dimensional operation of the low-voltage power distribution network. The upper-level optimization model is solved based on the operating data of the medium-voltage power distribution network to obtain a first solution result. The lower-level optimization model is solved based on the first solution result and the operating data of the low-voltage power distribution network to obtain a second solution result. The hydrogen fuel cell integrated unit is then sized and arranged according to the first and second solution results.

[0005] Optionally, the location and capacity of the integrated hydrogen fuel cell unit have multi-dimensional impacts on the operation of the medium-voltage power distribution network, including the voltage deviation rate of the medium-voltage power distribution network nodes, the network loss of the medium-voltage power distribution network, and the location of the heating network.

[0006] Optionally, the upper-level optimization model constructed based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the medium-voltage power distribution network is as follows: An upper-level optimization model is constructed with the objective functions of minimizing the voltage deviation rate of medium-voltage distribution network nodes, minimizing the network loss of medium-voltage distribution network, and minimizing the weighted sum of the locations of heating networks.

[0007] Optionally, the expression for the objective function is:

[0008] in, The objective function of the upper-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at medium-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a medium-voltage distribution network. To minimize the per-unit value of the heating network location, , , These are the weighting coefficients. .

[0009] Optionally, the formulas for minimizing the voltage deviation rate of medium-voltage distribution network nodes, the minimum network loss of medium-voltage distribution network, and the minimum location of heating network are as follows:

[0010] in, This represents the total number of nodes in a medium-voltage distribution network. and These refer to the starting and ending nodes of lines in a medium-voltage distribution network. This refers to the voltage at the starting node of a line in a medium-voltage distribution network. This refers to the voltage at the end node of a line in a medium-voltage distribution network. The cosine of the phase angle of the node voltage in a medium-voltage distribution network. For the line conductance between the first and last nodes of a medium-voltage distribution network, The sum of the distances from the node deploying the integrated hydrogen fuel cell unit to the nearest heating network node, For nodes Distance to the nearest hotspot node For the voltage deviation rate of medium-voltage distribution network nodes, For medium-voltage distribution network losses, This refers to the rated voltage of a medium-voltage distribution network node. This represents the maximum voltage at a node in a medium-voltage distribution network. This represents the minimum node voltage in a medium-voltage distribution network.

[0011] Optionally, the location and capacity of the integrated hydrogen fuel cell unit have multi-dimensional impacts on the operation of the low-voltage distribution network, including the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss.

[0012] Optionally, the lower-level optimization model constructed based on the location and capacity of the integrated hydrogen fuel cell unit and its multi-dimensional operational influencing factors on the low-voltage power distribution network is as follows: A lower-level optimization model is constructed with the objective functions of minimizing the node voltage deviation rate and the weighted sum of the minimum network losses in the low-voltage distribution network.

[0013] Optionally, the expression for the objective function is:

[0014] in, The objective function of the lower-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at low-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a low-voltage distribution network. and These are the weighting coefficients. =1.

[0015] Optionally, the calculation formulas for the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss are as follows:

[0016] in, For the voltage deviation rate of low-voltage distribution network nodes, For low-voltage distribution network losses, This represents the total number of nodes in a low-voltage distribution network. This refers to the voltage at the starting node of a line in a low-voltage distribution network. This refers to the voltage at the end node of a line in a low-voltage distribution network. The cosine of the phase angle of the node voltage in a low-voltage distribution network. For the line conductance between the first and last nodes of a low-voltage distribution network, This refers to the rated voltage of low-voltage distribution network nodes. This represents the maximum voltage at a low-voltage distribution network node. This represents the minimum voltage at a node in a low-voltage distribution network.

[0017] Optionally, the constraints of the lower-level optimization model include one or more of the following: hydrogen production constraints, hydrogen storage tank constraints, and hydrogen fuel cell stack constraints.

[0018] Optionally, the step of solving the upper-level optimization model based on the operating data of the medium-voltage distribution network to obtain the first solution result is as follows: Based on the operating data of the medium-voltage power distribution network, a genetic algorithm is used to obtain the first solution result, including the location and capacity of each hydrogen fuel cell integrated unit in the medium-voltage power distribution network, using the objective function of the upper-level optimization model as the optimization objective.

[0019] Optionally, the solution module solves the lower-level optimization model based on the first solution result and the operating data of the low-voltage distribution network to obtain a second solution result, and performs capacity determination and layout of the integrated hydrogen fuel cell unit according to the first and second solution results. The specific steps are as follows: Based on the operating data of the low-voltage distribution network after the addition of the hydrogen fuel cell integrated unit to the medium-voltage distribution network, the Newton-Raphson algorithm is used to solve the power flow equations and obtain a second solution result including the location and capacity of the hydrogen fuel cell integrated unit in the low-voltage distribution network.

[0020] A second aspect of the present invention provides a site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics, comprising: The model building module is used to build an upper-level optimization model based on the location and capacity of the integrated hydrogen fuel cell unit and the multi-dimensional operational influencing factors of the medium-voltage power distribution network, and to build a lower-level optimization model based on the location and capacity of the integrated hydrogen fuel cell unit and the multi-dimensional operational influencing factors of the low-voltage power distribution network. The solution module is used to solve the upper-level optimization model based on the operating data of the medium-voltage distribution network to obtain a first solution result, and to solve the lower-level optimization model based on the first solution result and the operating data of the low-voltage distribution network to obtain a second solution result. Based on the first solution result and the second solution result, the integrated hydrogen fuel cell machine is sized and arranged.

[0021] Optionally, the location and capacity of the integrated hydrogen fuel cell unit in the model building module have multi-dimensional impacts on the operation of the medium-voltage power distribution network, including the voltage deviation rate of the medium-voltage power distribution network nodes, the network loss of the medium-voltage power distribution network, and the location of the heating network.

[0022] Optionally, the model building module constructs an upper-level optimization model based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the medium-voltage power distribution network, specifically as follows: An upper-level optimization model is constructed with the objective functions of minimizing the voltage deviation rate of medium-voltage distribution network nodes, minimizing the network loss of medium-voltage distribution network, and minimizing the weighted sum of the locations of heating networks.

[0023] Optionally, the expression for the objective function in the model building module is:

[0024] in, The objective function of the upper-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at medium-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a medium-voltage distribution network. To minimize the per-unit value of the heating network location, , , These are the weighting coefficients. .

[0025] Optionally, the calculation formulas for minimizing the voltage deviation rate of medium-voltage distribution network nodes, the minimum network loss of medium-voltage distribution network, and the minimum location of heating network in the model construction module are as follows:

[0026] in, This represents the total number of nodes in a medium-voltage distribution network. and These refer to the starting and ending nodes of lines in a medium-voltage distribution network. This refers to the voltage at the starting node of a line in a medium-voltage distribution network. This refers to the voltage at the end node of a line in a medium-voltage distribution network. The cosine of the phase angle of the node voltage in a medium-voltage distribution network. For the line conductance between the first and last nodes of a medium-voltage distribution network, The sum of the distances from the node deploying the integrated hydrogen fuel cell unit to the nearest heating network node, For nodes Distance to the nearest hotspot node For the voltage deviation rate of medium-voltage distribution network nodes, For medium-voltage distribution network losses, This refers to the rated voltage of a medium-voltage distribution network node. This represents the maximum voltage at a node in a medium-voltage distribution network. This represents the minimum node voltage in a medium-voltage distribution network.

[0027] Optionally, the location and capacity of the integrated hydrogen fuel cell unit in the model building module have multi-dimensional impacts on the operation of the low-voltage distribution network, including the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss.

[0028] Optionally, the model building module constructs a lower-level optimization model based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the low-voltage power distribution network, specifically: A lower-level optimization model is constructed with the objective functions of minimizing the node voltage deviation rate and the weighted sum of the minimum network losses in the low-voltage distribution network.

[0029] Optionally, the expression for the objective function in the model building module is:

[0030] in, The objective function of the lower-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at low-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a low-voltage distribution network. and These are the weighting coefficients. =1.

[0031] Optionally, the calculation formulas for the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss in the model construction module are as follows:

[0032] in, For the voltage deviation rate of low-voltage distribution network nodes, For low-voltage distribution network losses, This represents the total number of nodes in a low-voltage distribution network. This refers to the voltage at the starting node of a line in a low-voltage distribution network. This refers to the voltage at the end node of a line in a low-voltage distribution network. The cosine of the phase angle of the node voltage in a low-voltage distribution network. For the line conductance between the first and last nodes of a low-voltage distribution network, This refers to the rated voltage of low-voltage distribution network nodes. This represents the maximum voltage at a low-voltage distribution network node. This represents the minimum voltage at a node in a low-voltage distribution network.

[0033] Optionally, the constraints of the lower-level optimization model in the model building module include one or more of the following: hydrogen production constraints, hydrogen storage tank constraints, and hydrogen fuel cell stack constraints.

[0034] Optionally, the solution module solves the upper-level optimization model based on the operating data of the medium-voltage distribution network to obtain the first solution result, and the steps are as follows: Based on the operating data of the medium-voltage power distribution network, a genetic algorithm is used to obtain the first solution result, including the location and capacity of each hydrogen fuel cell integrated unit in the medium-voltage power distribution network, using the objective function of the upper-level optimization model as the optimization objective.

[0035] Optionally, the solution module solves the lower-level optimization model based on the first solution result and the operating data of the low-voltage distribution network to obtain a second solution result, and performs capacity determination and layout of the integrated hydrogen fuel cell unit according to the first and second solution results. The specific steps are as follows: Based on the operating data of the low-voltage distribution network after the addition of the hydrogen fuel cell integrated unit to the medium-voltage distribution network, the Newton-Raphson algorithm is used to solve the power flow equations and obtain a second solution result including the location and capacity of the hydrogen fuel cell integrated unit in the low-voltage distribution network.

[0036] In another aspect, the present invention also provides a computing device, comprising: at least one processor and a memory; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, a method for site selection and capacity determination of an integrated hydrogen fuel cell machine based on thermoelectric characteristics, as described above, is implemented.

[0037] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the above-described method for the location and capacity determination of an integrated hydrogen fuel cell machine based on thermoelectric characteristics.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a method, system, device, and medium for the site selection and capacity determination of an integrated hydrogen fuel cell based on thermoelectric characteristics. The method includes constructing an upper-level optimization model based on the location and capacity of the integrated hydrogen fuel cell and its multi-dimensional operational influencing factors on a medium-voltage power distribution network, and constructing a lower-level optimization model based on the location and capacity of the integrated hydrogen fuel cell and its multi-dimensional operational influencing factors on a low-voltage power distribution network. The upper-level optimization model is solved using operational data from the medium-voltage power distribution network to obtain a first solution result. The lower-level optimization model is then solved using the first solution result and operational data from the low-voltage power distribution network to obtain a second solution result. The integrated hydrogen fuel cell is then determined and arranged according to the first and second solution results. This invention, firstly, involves... This invention constructs an optimization model based on the location and capacity of the integrated hydrogen fuel cell unit and its multi-dimensional influence on grid operation at both the grid and low-voltage distribution network levels. This model effectively reduces overall grid losses and improves voltage distribution balance, achieving coupled optimization of the power and thermal systems. Employing a combined optimization strategy of genetic algorithm and Newton-Raphson power flow analysis, the model rapidly converges to the optimal solution under complex constraints, improving computational efficiency and feasibility. This invention significantly improves the comprehensive utilization rate and energy conversion efficiency of the integrated hydrogen fuel cell unit, promotes the consumption of renewable energy, improves the voltage quality and power supply reliability of the distribution network, and realizes intelligent and collaborative optimized operation of distributed energy systems in the direction of integrated electricity and heat. It has good engineering application value and promising prospects for widespread application. Attached Figure Description

[0039] Figure 1 This is a flowchart of the site selection and volume determination method for an integrated hydrogen fuel cell based on thermoelectric characteristics proposed in this invention. Figure 2 This is a schematic diagram of the location and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics proposed in this invention. Figure 3 This is a schematic diagram of the electronic device proposed in this invention. Detailed Implementation

[0040] Most existing technologies only optimize power systems, failing to consider the role of hydrogen fuel cells in heating systems. This results in low overall energy efficiency, poor grid stability, and insufficient system economy. This invention establishes a two-layer optimization model for the location and capacity of a distributed integrated hydrogen fuel cell unit. It incorporates voltage deviation, line loss, and distance weights between heating network nodes and medium-voltage distribution networks into the upper-layer optimization objective. A lower-layer optimization model is constructed by combining 24-hour load fluctuations in the low-voltage distribution network with the internal module constraints of the integrated hydrogen fuel cell unit. This achieves globally optimal configuration of the power distribution system based on the coordinated electrothermal characteristics. Finally, by employing a solution mechanism combining genetic algorithms and Newton-Raphson power flow calculations, the access nodes and capacity configuration of the integrated hydrogen fuel cell unit in low-voltage distribution areas can be accurately determined. This effectively solves problems such as a single objective, insufficient dynamic adaptability, and imperfect model constraints in fuel cell deployment.

[0041] Specifically, this invention first introduces a comprehensive objective of voltage deviation, line network loss, and heating network location at the medium-voltage distribution network level, which can effectively reduce the overall network loss of the system and improve the voltage distribution balance, thereby achieving the coupling optimization of the power and heating systems.

[0042] Secondly, at the low-voltage distribution network level, the established lower-level optimization model, which combines 24-hour load variation characteristics and physical constraints of the integrated hydrogen fuel cell module, is time-adaptive and can dynamically adjust capacity configuration in response to load fluctuations, ensuring the stability and economy of the system under different operating conditions throughout the day.

[0043] Furthermore, this invention employs an optimization strategy that combines genetic algorithms with Newton-Raphson power flow analysis, which can quickly converge to the optimal solution under complex constraints, thereby improving computational efficiency and feasibility.

[0044] This invention can achieve coordinated optimization of the power grid and heating network while ensuring system stability, improve the capacity for renewable energy absorption, and enhance the safety, economy, and overall energy utilization efficiency of the distribution network.

[0045] Example 1: A method for site selection and volume determination of an integrated hydrogen fuel cell based on thermoelectric properties, such as... Figure 1 As shown, it includes the following steps S1 and S2.

[0046] S1. An upper-level optimization model is constructed based on the location and capacity of the integrated hydrogen fuel cell unit to influence the multi-dimensional operation of the medium-voltage power distribution network, and a lower-level optimization model is constructed based on the location and capacity of the integrated hydrogen fuel cell unit to influence the multi-dimensional operation of the low-voltage power distribution network.

[0047] Obtain basic configuration parameters of the distribution network, such as node voltage, connection method between nodes, line impedance, and location of heating network nodes.

[0048] In a further preferred embodiment, the location and capacity of the integrated hydrogen fuel cell unit affect the multidimensional operation of the medium-voltage power distribution network, including the voltage deviation rate of the medium-voltage power distribution network nodes, the network loss of the medium-voltage power distribution network, and the location of the heating network.

[0049] In a further preferred embodiment, the construction of an upper-level optimization model based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the medium-voltage power distribution network is specifically as follows: An upper-level optimization model is constructed with the objective functions of minimizing the voltage deviation rate of medium-voltage distribution network nodes, minimizing the network loss of medium-voltage distribution network, and minimizing the weighted sum of the locations of heating networks.

[0050] In a further preferred embodiment, the expression for the objective function is:

[0051] in, The objective function of the upper-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at medium-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a medium-voltage distribution network. To minimize the per-unit value of the heating network location, a standard value is set based on the actual situation, with the value decreasing the closer to the heating network node. , , These are weighting coefficients, and the weighting ratios can be flexibly adjusted according to different application scenarios. .

[0052] In a further preferred embodiment, the calculation formulas for minimizing the voltage deviation rate of medium-voltage distribution network nodes, the minimum network loss of medium-voltage distribution network, and the minimum location of heating network are as follows:

[0053] in, This represents the total number of nodes in a medium-voltage distribution network. and These refer to the starting and ending nodes of lines in a medium-voltage distribution network. This refers to the voltage at the starting node of a line in a medium-voltage distribution network. This refers to the voltage at the end node of a line in a medium-voltage distribution network. The cosine of the phase angle of the node voltage in a medium-voltage distribution network. For the line conductance between the first and last nodes of a medium-voltage distribution network, The sum of the distances from the node deploying the integrated hydrogen fuel cell unit to the nearest heating network node, For nodes Distance to the nearest hotspot node For the voltage deviation rate of medium-voltage distribution network nodes, For medium-voltage distribution network losses, This refers to the rated voltage of a medium-voltage distribution network node. This represents the maximum voltage at a node in a medium-voltage distribution network. This represents the minimum node voltage in a medium-voltage distribution network.

[0054] Since the solution results of the upper-level optimization model for medium-voltage distribution networks are generally the nodes that need to be connected to the hydrogen fuel cell integrated unit and the corresponding configuration capacity, and the location of new energy power generation, due to the uncertainty of its power generation, basically corresponds to the location of the node with a large voltage deviation rate, it needs to be focused on. The hourly power generation location and hourly power generation of the node, and the hourly load data of users, the location and capacity of the hydrogen fuel cell integrated unit have a multi-dimensional impact on the operation of the low-voltage distribution network, including the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss.

[0055] In a further preferred embodiment, the lower-level optimization model is constructed based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the low-voltage power distribution network, specifically as follows: A lower-level optimization model is constructed with the objective functions of minimizing the node voltage deviation rate and the weighted sum of the minimum network losses in the low-voltage distribution network.

[0056] In a further preferred embodiment, the expression for the objective function is:

[0057] in, The objective function of the lower-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at low-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a low-voltage distribution network. The standard value is set according to the actual situation, and the value is smaller the closer it is to the heating network node. and These are weighting coefficients, and the weighting ratios can be flexibly adjusted according to different application scenarios. =1.

[0058] In a further preferred embodiment, the calculation formulas for the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss are as follows:

[0059] in, For the voltage deviation rate of low-voltage distribution network nodes, For low-voltage distribution network losses, This represents the total number of nodes in a low-voltage distribution network. This refers to the voltage at the starting node of a line in a low-voltage distribution network. This refers to the voltage at the end node of a line in a low-voltage distribution network. The cosine of the phase angle of the node voltage in a low-voltage distribution network. For the line conductance between the first and last nodes of a low-voltage distribution network, This refers to the rated voltage of low-voltage distribution network nodes. This represents the maximum voltage at a low-voltage distribution network node. This represents the minimum voltage at a node in a low-voltage distribution network.

[0060] Since the upper-level optimization model based on medium-voltage distribution networks does not involve continuous power flow calculations, the constraints on the operating power of the integrated hydrogen fuel cell unit are relatively small, only existing in the limits of maximum and minimum power. However, in the site selection of low-voltage distribution networks, due to the design involving 24 continuous power flow calculations, the physical models and constraints within each module of the integrated hydrogen fuel cell unit need to be considered. An integrated hydrogen fuel cell unit generally includes an electro-hydrogen production module, a hydrogen storage tank module, and a hydrogen fuel cell stack module. Electro-hydrogen production is responsible for converting electrical energy into hydrogen energy, the hydrogen storage tank is responsible for storing hydrogen energy, and the hydrogen fuel cell is responsible for converting hydrogen energy into electrical and thermal energy. The final optimization determines the capacity configuration of each module. Since the integrated hydrogen fuel cell unit is only included in the fixed-capacity lower-level optimization model under a single node of a low-voltage distribution network, and the electrolysis of hydrogen, the hydrogen storage tank, and the hydrogen fuel cell stack all have corresponding constraints, it can also be understood as a fixed-capacity lower-level optimization model under a single node of a low-voltage distribution network. Its constraints mainly include the following: Constraints of Electrogenation:

[0061]

[0062] in, for Power consumption of the time-phase electrolytic cell The hydrogen production efficiency of the electrolyzer. for Hydrogen production power of the time-lapse electrolyzer, This is the maximum operating power of the electrolytic cell.

[0063] Hydrogen storage tank constraints:

[0064] 0

[0065] in, for Hydrogen storage capacity of the time-limited hydrogen storage tank. for Hydrogen storage capacity of the time-limited hydrogen storage tank. The hydrogen filling efficiency of the hydrogen storage tank. The hydrogen release efficiency of the hydrogen storage tank. Hydrogen loss rate, This is the maximum capacity of the hydrogen storage tank. for The power consumption of hydrogen by a hydrogen fuel cell during a given period. This refers to the time for charging and discharging hydrogen. Constraints of hydrogen fuel cell stacks:

[0066]

[0067]

[0068]

[0069] in, for The power generation capacity of hydrogen fuel cells at all times For the power generation efficiency of hydrogen fuel cells, for The heat production capacity of hydrogen fuel cells at all times For the heat generation efficiency of hydrogen fuel cells, This represents the minimum operating power of the hydrogen fuel cell. This represents the maximum operating power of the hydrogen fuel cell. This represents the maximum value of the operating power variation. This represents the minimum value of the operating power variation. for The power consumed by a hydrogen fuel cell at any given time.

[0070] S2, Based on the operating data of the medium-voltage distribution network, the upper-level optimization model is solved to obtain the first solution result. Based on the first solution result and the operating data of the low-voltage distribution network, the lower-level optimization model is solved to obtain the second solution result. The hydrogen fuel cell integrated machine is sized and arranged according to the first solution result and the second solution result.

[0071] In a further optimized scheme, a genetic algorithm is used to obtain the location and capacity of each hydrogen fuel cell integrated unit in the medium-voltage distribution network based on the operation data of the medium-voltage distribution network and the objective function of the upper-level optimization model. Based on the operating data of the low-voltage distribution network after the addition of the hydrogen fuel cell integrated unit to the medium-voltage distribution network, the Newton-Raphson algorithm is used to solve the power flow equations and obtain the location and capacity of the hydrogen fuel cell integrated unit in the low-voltage distribution network.

[0072] First, a genetic algorithm is used to optimize the objective function of the upper-level optimization model, which determines multiple candidate nodes for the installation of the integrated hydrogen fuel cell unit and their corresponding configuration capacities, such as nodes A, B, and C and their corresponding deployment capacities. Then, integrated hydrogen fuel cell units with corresponding configuration capacities are connected to the multiple candidate nodes. Since each candidate node includes multiple sub-nodes, connecting the integrated hydrogen fuel cell unit with the corresponding configuration capacity to the candidate node can also be understood as sequentially connecting the integrated hydrogen fuel cell unit with the corresponding configuration capacity to the sub-nodes.

[0073] After connecting a hydrogen fuel cell integrated unit with the corresponding configured capacity to a candidate node, the connected hydrogen fuel cell integrated unit can be equivalent to an active / reactive power injection into the bus, causing the power flow of reactive and active power in the original distribution network, thereby changing the node voltage state in the low-voltage distribution network. Therefore, the Newton-Raphson algorithm is used to solve the power flow equations to determine the node voltage of each node after adding the hydrogen fuel cell integrated unit. Assume the active and reactive power inputs of the low-voltage distribution network are as follows: and At the corresponding node Incorporate the injected power into the power flow equations , ,in, For nodes The injected active power equation, This refers to the net active power injected at the node via the integrated hydrogen fuel cell unit. For nodes The injected reactive power equation, This refers to the net reactive power injected at the node via the integrated hydrogen fuel cell unit. Voltage amplitude, The phase angle is then calculated using the power flow equations.

[0074] Since the line parameters and network architecture are fixed, after calculating the node voltage of each node in the low-voltage distribution network, a genetic algorithm can be used to optimize the objective function of the lower-level optimization model, and finally determine the access node and capacity configuration of the hydrogen fuel cell integrated unit in the low-voltage distribution network area.

[0075] The core function of using 24-hour load data in the above steps is to capture the temporal fluctuations of the load, allowing the installation location of the integrated hydrogen fuel cell unit to not only adapt to the operating conditions at a specific point in time, but also to continuously optimize network losses and voltage deviations under all load scenarios throughout the day, ultimately achieving "global optimization" rather than "local optimization." This is a concrete manifestation of the "temporal adaptability" principle in distribution network optimization—the operation of the power system is dynamic, and the optimization scheme must cover the complete cycle to ensure its effectiveness.

[0076] In summary, the method proposed in this application can establish an electro-thermal synergistic optimization model based on both the power characteristics of the distribution network and the thermoelectric characteristics of the integrated hydrogen fuel cell unit, thereby achieving joint decision-making on site selection and capacity determination. By simultaneously considering the matching relationship between voltage stability, line loss, and regional heat load, it not only effectively improves the comprehensive utilization efficiency of the integrated hydrogen fuel cell unit, but also enhances the stability and economy of the power grid operation, and solves the problem of new energy power generation absorption.

[0077] Example 2: Based on the same inventive concept, this invention also provides a site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics, such as... Figure 2 As shown, it includes: The model building module is used to build an upper-level optimization model based on the location and capacity of the integrated hydrogen fuel cell unit and the multi-dimensional operational influencing factors of the medium-voltage power distribution network, and to build a lower-level optimization model based on the location and capacity of the integrated hydrogen fuel cell unit and the multi-dimensional operational influencing factors of the low-voltage power distribution network. The solution module is used to solve the upper-level optimization model based on the operating data of the medium-voltage distribution network to obtain a first solution result, and to solve the lower-level optimization model based on the first solution result and the operating data of the low-voltage distribution network to obtain a second solution result. Based on the first solution result and the second solution result, the integrated hydrogen fuel cell machine is sized and arranged.

[0078] In a further preferred embodiment, the location and capacity of the integrated hydrogen fuel cell unit in the model building module affect the multidimensional operation of the medium-voltage power distribution network, including the voltage deviation rate of the medium-voltage power distribution network nodes, the network loss of the medium-voltage power distribution network, and the location of the heating network.

[0079] In a further preferred embodiment, the model building module constructs an upper-level optimization model based on the multi-dimensional operational influencing factors of the hydrogen fuel cell integrated unit on the medium-voltage power distribution network, specifically as follows: An upper-level optimization model is constructed with the objective functions of minimizing the voltage deviation rate of medium-voltage distribution network nodes, minimizing the network loss of medium-voltage distribution network, and minimizing the weighted sum of the locations of heating networks.

[0080] In a further preferred embodiment, the expression for the objective function in the model building module is:

[0081] in, The objective function of the upper-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at medium-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a medium-voltage distribution network. To minimize the per-unit value of the heating network location, , , These are the weighting coefficients. .

[0082] In a further preferred embodiment, the calculation formulas for minimizing the sum of voltage deviation rates at medium-voltage distribution network nodes, the minimum network loss of the medium-voltage distribution network, and the minimum location of the heating network in the model building module are as follows:

[0083] in, This represents the total number of nodes in a medium-voltage distribution network. and These refer to the starting and ending nodes of lines in a medium-voltage distribution network. This refers to the voltage at the starting node of a line in a medium-voltage distribution network. This refers to the voltage at the end node of a line in a medium-voltage distribution network. The cosine of the phase angle of the node voltage in a medium-voltage distribution network. For the line conductance between the first and last nodes of a medium-voltage distribution network, The sum of the distances from the node deploying the integrated hydrogen fuel cell unit to the nearest heating network node, For nodes Distance to the nearest hotspot node For the voltage deviation rate of medium-voltage distribution network nodes, For medium-voltage distribution network losses, This refers to the rated voltage of a medium-voltage distribution network node. This represents the maximum voltage at a node in a medium-voltage distribution network. This represents the minimum node voltage in a medium-voltage distribution network.

[0084] In a further preferred embodiment, the location and capacity of the integrated hydrogen fuel cell unit in the model building module affect the multidimensional operation of the low-voltage distribution network, including the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss.

[0085] In a further preferred embodiment, the model building module constructs a lower-level optimization model based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the low-voltage power distribution network, specifically as follows: A lower-level optimization model is constructed with the objective functions of minimizing the node voltage deviation rate and the weighted sum of the minimum network losses in the low-voltage distribution network.

[0086] In a further preferred embodiment, the expression for the objective function in the model building module is:

[0087] in, The objective function of the lower-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at low-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a low-voltage distribution network. and These are the weighting coefficients. =1.

[0088] In a further preferred embodiment, the calculation formulas for the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss in the model construction module are as follows:

[0089] in, For the voltage deviation rate of low-voltage distribution network nodes, For low-voltage distribution network losses, This represents the total number of nodes in a low-voltage distribution network. This refers to the voltage at the starting node of a line in a low-voltage distribution network. This refers to the voltage at the end node of a line in a low-voltage distribution network. The cosine of the phase angle of the node voltage in a low-voltage distribution network. For the line conductance between the first and last nodes of a low-voltage distribution network, This refers to the rated voltage of low-voltage distribution network nodes. This represents the maximum voltage at a low-voltage distribution network node. This represents the minimum voltage at a node in a low-voltage distribution network.

[0090] In a further preferred embodiment, the constraints of the lower-level optimization model in the model building module include one or more of the following: hydrogen production constraints, hydrogen storage tank constraints, and hydrogen fuel cell stack constraints.

[0091] In a further preferred embodiment, the solution module solves the upper-level optimization model based on the operating data of the medium-voltage distribution network to obtain a first solution result. The steps are as follows: Based on the operating data of the medium-voltage power distribution network, a genetic algorithm is used to obtain the first solution result, including the location and capacity of each hydrogen fuel cell integrated unit in the medium-voltage power distribution network, using the objective function of the upper-level optimization model as the optimization objective.

[0092] In a further preferred embodiment, the solving module solves the lower-level optimization model based on the first solution result and the operating data of the low-voltage distribution network to obtain a second solution result. The integrated hydrogen fuel cell unit is then sized and arranged according to the first and second solution results. The specific steps are as follows: Based on the operating data of the low-voltage distribution network after the addition of the hydrogen fuel cell integrated unit to the medium-voltage distribution network, the Newton-Raphson algorithm is used to solve the power flow equations and obtain a second solution result including the location and capacity of the hydrogen fuel cell integrated unit in the low-voltage distribution network.

[0093] Example 3 like Figure 3 As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0094] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to realize the corresponding method flow or corresponding function, so as to realize the steps of the addressing and calibrating method of a hydrogen fuel cell integrated machine based on thermoelectric characteristics in the above embodiment.

[0095] Example 4 Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the addressing and sizing method for an integrated hydrogen fuel cell machine based on thermoelectric characteristics in the above embodiments.

[0096] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0098] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0100] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for site selection and volume determination of an integrated hydrogen fuel cell based on thermoelectric characteristics, characterized in that, include: An upper-level optimization model is constructed based on the location and capacity of the integrated hydrogen fuel cell unit to influence the multi-dimensional operation of the medium-voltage power distribution network, and a lower-level optimization model is constructed based on the location and capacity of the integrated hydrogen fuel cell unit to influence the multi-dimensional operation of the low-voltage power distribution network. The upper-level optimization model is solved based on the operating data of the medium-voltage power distribution network to obtain a first solution result. The lower-level optimization model is solved based on the first solution result and the operating data of the low-voltage power distribution network to obtain a second solution result. The hydrogen fuel cell integrated unit is then sized and arranged according to the first and second solution results.

2. The site selection and volume determination method for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 1, characterized in that, The location and capacity of the integrated hydrogen fuel cell unit have multi-dimensional impacts on the operation of the medium-voltage power distribution network, including the voltage deviation rate of the medium-voltage power distribution network nodes, the network loss of the medium-voltage power distribution network, and the location of the heating network.

3. The site selection and volume determination method for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 2, characterized in that, The upper-level optimization model, based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the medium-voltage power distribution network, is constructed as follows: An upper-level optimization model is constructed with the objective functions of minimizing the voltage deviation rate of medium-voltage distribution network nodes, minimizing the network loss of medium-voltage distribution network, and minimizing the weighted sum of the locations of heating networks.

4. The site selection and volume determination method for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 3, characterized in that, The expression for the objective function is: in, The objective function of the upper-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at medium-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a medium-voltage distribution network. To minimize the per-unit value of the heating network location, , , These are the weighting coefficients. .

5. The site selection and volume determination method for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 4, characterized in that, The formulas for minimizing the voltage deviation rate at medium-voltage distribution network nodes, the minimum network loss in medium-voltage distribution network, and the minimum location of the heating network are as follows: in, This represents the total number of nodes in a medium-voltage distribution network. and These refer to the starting and ending nodes of lines in a medium-voltage distribution network. This refers to the voltage at the starting node of a line in a medium-voltage distribution network. This refers to the voltage at the end node of a line in a medium-voltage distribution network. The cosine of the phase angle of the node voltage in a medium-voltage distribution network. For the line conductance between the first and last nodes of a medium-voltage distribution network, The sum of the distances from the node deploying the integrated hydrogen fuel cell unit to the nearest heating network node, For nodes Distance to the nearest hotspot node For the voltage deviation rate of medium-voltage distribution network nodes, For medium-voltage distribution network losses, This refers to the rated voltage of a medium-voltage distribution network node. This represents the maximum voltage at a node in a medium-voltage distribution network. This represents the minimum node voltage in a medium-voltage distribution network.

6. The method for site selection and volume determination of an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 1, characterized in that, The location and capacity of the integrated hydrogen fuel cell unit have multi-dimensional impacts on the operation of the low-voltage distribution network, including the voltage deviation rate of the low-voltage distribution network nodes and the network loss of the low-voltage distribution network.

7. The site selection and volume determination method for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 6, characterized in that, The lower-level optimization model, based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the low-voltage power distribution network, is constructed as follows: A lower-level optimization model is constructed with the objective functions of minimizing the node voltage deviation rate and the weighted sum of the minimum network losses in the low-voltage distribution network.

8. The site selection and volume determination method for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 7, characterized in that, The expression for the objective function is: in, The objective function of the lower-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at low-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a low-voltage distribution network. and These are the weighting coefficients. =1.

9. The site selection and volume determination method for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 8, characterized in that, The formulas for calculating the voltage deviation rate of the low-voltage distribution network nodes and the network loss of the low-voltage distribution network are as follows: in, For the voltage deviation rate of low-voltage distribution network nodes, For low-voltage distribution network losses, This represents the total number of nodes in a low-voltage distribution network. This refers to the voltage at the starting node of a line in a low-voltage distribution network. This refers to the voltage at the end node of a line in a low-voltage distribution network. The cosine of the phase angle of the node voltage in a low-voltage distribution network. For the line conductance between the first and last nodes of a low-voltage distribution network, This refers to the rated voltage of low-voltage distribution network nodes. This represents the maximum voltage at a low-voltage distribution network node. This represents the minimum voltage at a node in a low-voltage distribution network.

10. The method for site selection and volume determination of an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 1, characterized in that, The constraints of the lower-level optimization model include one or more of the following: hydrogen production constraints, hydrogen storage tank constraints, and hydrogen fuel cell stack constraints.

11. The method for site selection and volume determination of an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 1, characterized in that, The steps for solving the upper-level optimization model based on the operating data of the medium-voltage distribution network to obtain the first solution result are as follows: Based on the operating data of the medium-voltage power distribution network, a genetic algorithm is used to obtain the first solution result, including the location and capacity of each hydrogen fuel cell integrated unit in the medium-voltage power distribution network, using the objective function of the upper-level optimization model as the optimization objective.

12. The method for site selection and volume determination of an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 1 or 11, characterized in that, The second solution result is obtained by solving the lower-level optimization model based on the first solution result and the operating data of the low-voltage distribution network. The hydrogen fuel cell integrated unit is then sized and arranged according to the first and second solution results. The specific steps are as follows: Based on the operating data of the low-voltage distribution network after the addition of the hydrogen fuel cell integrated unit to the medium-voltage distribution network, the Newton-Raphson algorithm is used to solve the power flow equations and obtain a second solution result including the location and capacity of the hydrogen fuel cell integrated unit in the low-voltage distribution network.

13. A site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics, characterized in that, include: The model building module is used to build an upper-level optimization model based on the location and capacity of the integrated hydrogen fuel cell unit and the multi-dimensional operational influencing factors of the medium-voltage power distribution network, and to build a lower-level optimization model based on the location and capacity of the integrated hydrogen fuel cell unit and the multi-dimensional operational influencing factors of the low-voltage power distribution network. The solution module is used to solve the upper-level optimization model based on the operating data of the medium-voltage distribution network to obtain a first solution result, and to solve the lower-level optimization model based on the first solution result and the operating data of the low-voltage distribution network to obtain a second solution result. Based on the first solution result and the second solution result, the integrated hydrogen fuel cell machine is sized and arranged.

14. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 13, characterized in that, The location and capacity of the integrated hydrogen fuel cell unit in the model building module have multi-dimensional impacts on the operation of the medium-voltage power distribution network, including the voltage deviation rate of the medium-voltage power distribution network nodes, the network loss of the medium-voltage power distribution network, and the location of the heating network.

15. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 14, characterized in that, The model building module constructs an upper-level optimization model based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the medium-voltage power distribution network. Specifically: An upper-level optimization model is constructed with the objective functions of minimizing the voltage deviation rate of medium-voltage distribution network nodes, minimizing the network loss of medium-voltage distribution network, and minimizing the weighted sum of the locations of heating networks.

16. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 15, characterized in that, The expression for the objective function in the model building module is: in, The objective function of the upper-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at medium-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a medium-voltage distribution network. To minimize the per-unit value of the heating network location, , , These are the weighting coefficients. .

17. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 16, characterized in that, The calculation formulas for minimizing the voltage deviation rate of medium-voltage distribution network nodes, the minimum network loss of medium-voltage distribution network, and the minimum location of heating network in the model building module are as follows: in, This represents the total number of nodes in a medium-voltage distribution network. and These refer to the starting and ending nodes of lines in a medium-voltage distribution network. This refers to the voltage at the starting node of a line in a medium-voltage distribution network. This refers to the voltage at the end node of a line in a medium-voltage distribution network. The cosine of the phase angle of the node voltage in a medium-voltage distribution network. For the line conductance between the first and last nodes of a medium-voltage distribution network, The sum of the distances from the node deploying the integrated hydrogen fuel cell unit to the nearest heating network node, For nodes Distance to the nearest hotspot node For the voltage deviation rate of medium-voltage distribution network nodes, For medium-voltage distribution network losses, This refers to the rated voltage of a medium-voltage distribution network node. This represents the maximum voltage at a node in a medium-voltage distribution network. This represents the minimum node voltage in a medium-voltage distribution network.

18. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 13, characterized in that, The location and capacity of the integrated hydrogen fuel cell unit in the model building module have multi-dimensional impacts on the operation of the low-voltage distribution network, including the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss.

19. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 18, characterized in that, The model building module constructs a lower-level optimization model based on the multi-dimensional operational influencing factors of the location and capacity of the integrated hydrogen fuel cell unit on the low-voltage power distribution network. Specifically: A lower-level optimization model is constructed with the objective functions of minimizing the node voltage deviation rate and the weighted sum of the minimum network losses in the low-voltage distribution network.

20. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 19, characterized in that, The expression for the objective function in the model building module is: in, The objective function of the lower-level optimization model is... To minimize the per-unit value of the sum of voltage deviation rates at low-voltage distribution network nodes, This is the per-unit value for the minimum network loss in a low-voltage distribution network. and These are the weighting coefficients. =1.

21. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 20, characterized in that, The calculation formulas for the low-voltage distribution network node voltage deviation rate and the low-voltage distribution network loss in the model construction module are as follows: in, For the voltage deviation rate of low-voltage distribution network nodes, For low-voltage distribution network losses, This represents the total number of nodes in a low-voltage distribution network. This refers to the voltage at the starting node of a line in a low-voltage distribution network. This refers to the voltage at the end node of a line in a low-voltage distribution network. The cosine of the phase angle of the node voltage in a low-voltage distribution network. For the line conductance between the first and last nodes of a low-voltage distribution network, This refers to the rated voltage of low-voltage distribution network nodes. This represents the maximum voltage at a low-voltage distribution network node. This represents the minimum voltage at a node in a low-voltage distribution network.

22. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 13, characterized in that, The constraints of the lower-level optimization model in the model building module include one or more of the following: hydrogen production constraints, hydrogen storage tank constraints, and hydrogen fuel cell stack constraints.

23. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 13, characterized in that, The solution module solves the upper-level optimization model based on the operating data of the medium-voltage distribution network to obtain the first solution result. The steps are as follows: Based on the operating data of the medium-voltage power distribution network, a genetic algorithm is used to obtain the first solution result, including the location and capacity of each hydrogen fuel cell integrated unit in the medium-voltage power distribution network, using the objective function of the upper-level optimization model as the optimization objective.

24. The site selection and volume control system for an integrated hydrogen fuel cell based on thermoelectric characteristics according to claim 13 or 23, characterized in that, The solution module solves the lower-level optimization model based on the first solution result and the operating data of the low-voltage distribution network to obtain a second solution result. Based on the first and second solution results, the integrated hydrogen fuel cell unit is sized and arranged. The specific steps are as follows: Based on the operating data of the low-voltage distribution network after the addition of the hydrogen fuel cell integrated unit to the medium-voltage distribution network, the Newton-Raphson algorithm is used to solve the power flow equations and obtain a second solution result including the location and capacity of the hydrogen fuel cell integrated unit in the low-voltage distribution network.

25. A computer device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, the site selection and gradation method for an integrated hydrogen fuel cell machine based on thermoelectric characteristics as described in any one of claims 1 to 12 is implemented.

26. A computer-readable storage medium, characterized in that, It contains an execution program, which, when executed, implements the site selection and capacity determination method for an integrated hydrogen fuel cell machine based on thermoelectric characteristics as described in any one of claims 1 to 12.

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