Energy Management Method and Device for Wind-Solar-Hydrogen System Optimizing Electrolyzer Voltage and Power

Abstract

The present invention belongs to the field of electric power, and discloses an energy management method and device for a wind-solar-hydrogen system that optimizes the voltage and power of an electrolytic cell. The energy management of the present invention is for the energy management of a wind-solar-hydrogen system. The energy management method is to adjust the active power output of the power grid, coordinate the reactive power of photovoltaic, wind turbines, and the power grid, optimize the voltage and power fluctuations at the electrolytic cell connection point while optimizing the line loss, and further improve the hydrogen production efficiency of the electrolytic cell. The method of the present invention can improve the hydrogen production efficiency by optimizing the voltage and power at the electrolytic cell module connection point, reduce the line loss through reactive power coordinated output, adjust the power grid output, increase the output for the purpose of improving the hydrogen production efficiency, and thus produce more hydrogen.

Description

Technical Field

[0001] This application relates to the field of power technologies, and in particular to an energy management method for a wind-solar-hydrogen system that optimizes the voltage and power of an electrolyzer. Background Art

[0002] At the current stage, the production of hydrogen energy focuses on the development of hydrogen production by wind power and solar power generation. Using renewable energy to produce hydrogen can reduce environmental pollution and is sustainable. With the continuous development of new energy technologies, the cost of hydrogen production has been decreasing year by year. Currently, the cost of new energy hydrogen production is still higher than that of traditional hydrogen production methods, and continuous optimization and research are still needed.

[0003] Improving the hydrogen production efficiency in a wind-solar-hydrogen system is an effective method to reduce the cost of new energy hydrogen production. It can produce more hydrogen under the same power generation conditions, which is beneficial to improving the economic benefits of the system. The main factors affecting the hydrogen production efficiency of the electrolyzer include the access point voltage and power fluctuations. Voltage and power fluctuations will cause changes in the actual hydrogen production power of the electrolyzer, thereby affecting the electrolysis current. The sudden change in the electrolyzer current will cause the electrolyzer to deviate from the steady state and reduce the hydrogen production efficiency. Optimizing the access point voltage and power fluctuations of the electrolyzer can effectively improve the hydrogen production efficiency.

[0004] The existing energy management of the wind-solar-hydrogen system focuses on improving the solution algorithm and optimization objectives, ignoring the operating characteristics of the electrolyzer itself. For research on hydrogen production systems, it often focuses on increasing the hydrogen production power to increase the hydrogen production output. However, both the electrolyzer voltage and power fluctuations will cause sudden changes in the electrolysis current, which will cause the electrolyzer to deviate from the steady-state condition and reduce the hydrogen production efficiency. The reduction in hydrogen production efficiency will lead to a decline in the economic benefits of the system, which is not conducive to the popularization of the new energy hydrogen production system. Summary of the Invention

[0005] The purpose of the embodiments of this application is to provide an energy management method for a wind-solar-hydrogen system that optimizes the voltage and power of an electrolyzer, so as to reduce the voltage and power fluctuations at the access point of the electrolyzer module in the wind-solar-hydrogen system and improve the hydrogen production efficiency.

[0006] According to the first aspect of the embodiments of this application, an energy management method for a wind-solar-hydrogen system that optimizes the voltage and power of an electrolyzer is provided, including:

[0007] Step 1: Obtain the photovoltaic active power and wind power active power of the wind-solar-hydrogen system;

[0008] Step 2: Construct an electrolyzer model and a hydrogen production efficiency model based on the operating characteristics of the electrolyzer;

[0009] Step 3: Determine the constraint conditions according to the actual operation of the photovoltaic, wind power, and electrolyzer;

[0010] Step 4: Determine the objective function of the wind-solar-hydrogen system according to the optimization requirements of the wind-solar-hydrogen system;

[0011] Step 5: Obtain the parameters of the wind-solar-hydrogen system;

[0012] Step 6: Initialize the population according to the strength Pareto evolutionary algorithm in combination with the constraint conditions;

[0013] Step 7: Calculate the reactive power using the electrolyzer model, and determine the active power, reactive power, and node voltage of each node through power flow calculation in combination with the population, photovoltaic active power, wind power active power, and wind-solar-hydrogen system parameters;

[0014] Step 8: Calculate the target index of the wind-solar-hydrogen system according to the objective function in combination with the active power, reactive power, node voltage of each node of the wind-solar-hydrogen system, and the hydrogen production efficiency model;

[0015] Step 9: The population compares with each other according to the target index, forms an optimal solution set using the screening principle in the strength Pareto evolutionary algorithm, and regenerates the population using the crossover and mutation models in the strength Pareto evolutionary algorithm;

[0016] Step 10: Determine whether the iteration of the strength Pareto evolutionary algorithm reaches the upper limit. If it reaches, execute Step 11; if not, execute Step 7;

[0017] Step 11: Assign weights to each target index, calculate the target fitness of the optimal solution set by multiplying the objective function by the weights, select the minimum value of the target fitness to form an optimal population, and obtain the optimal energy management scheme.

[0018] According to the second aspect of the embodiments of the present application, a wind-solar-hydrogen system energy management device for optimizing the electrolyzer voltage and power is provided, including:

[0019] The first acquisition module is used to acquire the photovoltaic active power and wind power active power of the wind-solar-hydrogen system;

[0020] The model construction module is used to construct an electrolyzer model and a hydrogen production efficiency model according to the operating characteristics of the electrolyzer;

[0021] The constraint condition determination module is used to determine the constraint conditions according to the actual operation of the photovoltaic, wind power, and electrolyzer;

[0022] The objective function determination module is used to determine the objective function of the wind-solar-hydrogen system according to the optimization requirements of the wind-solar-hydrogen system;

[0023] The second acquisition module is used to acquire the parameters of the wind-solar-hydrogen system;

[0024] The population initialization module is used to initialize the population according to the strength Pareto evolutionary algorithm in combination with the constraint conditions;

[0025] The first calculation module is used to calculate the reactive power by using the electrolyzer model, and determine the active power, reactive power, and node voltage of each node through power flow calculation in combination with the population, photovoltaic active power, wind power active power, and wind-solar-hydrogen system parameters.

[0026] The second calculation module is used to calculate the target indicators of the wind-solar-hydrogen system according to the objective function in combination with the active power, reactive power, node voltage of each node in the wind-solar-hydrogen system, and the hydrogen production efficiency model.

[0027] The population regeneration module is used to compare the populations according to the target indicators, form an optimal solution set by using the screening principle in the strength Pareto evolutionary algorithm, and regenerate the population by using the crossover and mutation models in the strength Pareto evolutionary algorithm.

[0028] The iteration module is used to determine whether the iteration of the strength Pareto evolutionary algorithm reaches the upper limit. If it reaches, the solution obtaining module is executed; if not, the first calculation module is executed.

[0029] The solution obtaining module is used to assign weights to each target indicator, calculate the target fitness of the optimal solution set by multiplying the objective function by the weights, select the minimum value of the target fitness to form an optimal population, and obtain the optimal energy management solution.

[0030] The technical solution provided by the embodiments of the present application may include the following beneficial effects:

[0031] As can be seen from the above embodiments, the present application adopts an energy management method for optimizing the access point voltage and power of the electrolyzer module, coordinates the active power and reactive power output of the photovoltaic module, wind turbine module, energy storage module, and hydrogen production module in the wind-solar-hydrogen system, considers the influence of voltage and power fluctuations on hydrogen production by the electrolyzer, reduces the voltage and power fluctuations at the electrolyzer access point, overcomes the problem of reduced hydrogen production efficiency of the electrolyzer caused by voltage and power fluctuations, takes into account the line loss of the wind-solar-hydrogen system, reduces the loss as much as possible while improving the hydrogen production efficiency, also takes into account the goal of increasing the hydrogen production output, increases the hydrogen production power as much as possible, and thus achieves the effects of increasing the system revenue and reducing the hydrogen production cost.

[0032] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0034] Figure 1 is a structural diagram of a wind-solar-hydrogen system shown according to an exemplary embodiment.

[0035] Figure 2 It is a flowchart of an energy management method for a wind-solar-hydrogen system that optimizes the electrolyzer voltage and power according to an exemplary embodiment.

[0036] Figure 3 It is the active power of photovoltaic and wind power according to an exemplary embodiment.

[0037] Figure 4 It is the reactive power output of the photovoltaic according to an exemplary embodiment.

[0038] Figure 5 It is the reactive power output of the wind power according to an exemplary embodiment.

[0039] Figure 6 It is the reactive power output of the power grid according to an exemplary embodiment.

[0040] Figure 7 It is the active power output of the power grid according to an exemplary embodiment.

[0041] Figure 8 It is the active power demand of the electrolyzer according to an exemplary embodiment.

[0042] Figure 9 It is the reactive power demand of the electrolyzer according to an exemplary embodiment.

[0043] Figure 10 It is the node voltage according to an exemplary embodiment.

[0044] Figure 11 It is the active and reactive power losses of line 12 according to an exemplary embodiment.

[0045] Figure 12 It is the active and reactive power losses of line 23 according to an exemplary embodiment.

[0046] Figure 13 It is the active and reactive power losses of line 24 according to an exemplary embodiment.

[0047] Figure 14 It is the active and reactive power losses of line 25 according to an exemplary embodiment.

[0048] Figure 15 It is the total active and reactive power losses of the line according to an exemplary embodiment.

[0049] Figure 16 It is the hydrogen production efficiency of the electrolyzer according to an exemplary embodiment.

[0050] Figure 17 It is a block diagram of an energy management device for a wind-solar-hydrogen system that optimizes the electrolyzer voltage and power according to an exemplary embodiment. Detailed implementation manners

[0051] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of apparatuses and methods consistent with some aspects of the present application as detailed in the appended claims.

[0052] The terms used in the present application are for the purpose of describing particular embodiments only and are not intended to limit the present application. The singular forms "a", "the", and "said" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0053] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0054] As Figure 1 shown, the energy management object of the present invention is a wind-solar-hydrogen system, and the wind-solar-hydrogen system mainly consists of a photovoltaic power generation module, a wind power generation module, and an electrolyzer module, and adopts a grid-connected operation mode; the active power output of the photovoltaic power generation module and the wind power generation module is selected according to the actual situation, and the reactive power output participates in the adjustment of the system voltage, line loss, and reactive power balance; the electrolyzer module includes a transformer, an inverter, and a DC electrolysis module, and the actual hydrogen production power is affected by the access point voltage and power; the energy management method is to coordinate the reactive power of the photovoltaic, wind turbine, and power grid by adjusting the active power output of the power grid, optimize the line loss while optimizing the voltage and power fluctuations at the electrolyzer access point, and thus improve the hydrogen production efficiency of the electrolyzer.

[0055] Figure 2 is a flowchart of a method for managing the energy of a wind-solar-hydrogen system that optimizes the voltage and power of an electrolyzer, as Figure 2 shown. The method is applied to a terminal and may include the following steps:

[0056] Step S1: Obtain the photovoltaic active power and wind power active power of the wind-solar-hydrogen system;

[0057] Specifically, the active power of photovoltaic and the active power of wind power are the electrical energy inputs of the wind-solar-hydrogen system, which are the preconditions for the system to perform energy management. They are affected by factors such as light, temperature, wind speed, and wind direction in the area where the wind-solar-hydrogen system is located. Energy management can control the power generation and consumption of photovoltaic and wind power modules. Maximizing the power generation and consumption rate is also one of the goals of the wind-solar-hydrogen system. Increasing the consumption rate can increase the hydrogen production power and the grid connection power, thereby increasing the system's revenue.

[0058] Step S2: Construct an electrolyzer model and a hydrogen production efficiency model based on the operating characteristics of the electrolyzer;

[0059] The active power of the alkaline electrolyzer is affected by the voltage at the connection point, the reactive power demand, etc. Voltage fluctuations will cause fluctuations in the active power. The specific electrolyzer model is as follows:

[0060]

[0061] In the formula, is the reactive power of the electrolyzer, with the unit of Mvar; is the th minute of system operation; is the voltage at the connection point of the electrolyzer, with the unit of kV; is the equivalent reactance of the electrolyzer, with the unit of Ω; is the active power of the electrolyzer allocated by the system, with the unit of MW.

[0062] The hydrogen production efficiency of the electrolyzer is affected by the fluctuations in hydrogen production power. The hydrogen production power is affected by voltage fluctuations and energy management allocation. The greater the fluctuations, the lower the efficiency. The rate of decrease in hydrogen production efficiency is slow at first and then fast. After a short-term decrease in hydrogen production efficiency, it will gradually recover, and the recovery rate is fast at first and then slow. Taking the characteristic point surface fitting, the influence of power fluctuations on the electrolyzer efficiency is instantaneous. For the comparison problem of hydrogen production efficiency and hydrogen production output on a unit time scale, the method of integrating to solve the average value of hydrogen production efficiency is adopted. The specific hydrogen production efficiency model is as follows:

[0063]

[0064] In the formula, is the voltage fluctuation , t s is the proportion of the hydrogen production efficiency recovered at time is the voltage fluctuation , t s is the actual hydrogen production efficiency recovered at time is the actual maximum hydrogen production efficiency of the electrolyzer, with the unit of %; , are intermediate variables; is the proportion of the electrolyzer power fluctuation, with the unit of %; is the Active power per minute, unit: MW; is the -1 minute active power, unit: MW; is the rated power of the electrolyzer, unit: MW; is the average hydrogen production efficiency at time t, unit: %.

[0065] The hydrogen production efficiency model conforms to the law of hydrogen production efficiency reduction caused by voltage and power fluctuations. This model can quantify the problem of hydrogen production efficiency reduction and facilitate system energy management.

[0066] Step S3: Determine the constraint conditions according to the actual operation of photovoltaic, wind power and electrolyzer;

[0067] Specifically, the constraint conditions include photovoltaic constraint conditions, wind power constraint conditions, and electrolyzer constraint conditions.

[0068] The reactive power output of the photovoltaic module is limited by the converter capacity and active power output. That is, the photovoltaic constraint condition is:

[0069]

[0070] In the formula, is the upper limit of the photovoltaic reactive power output at time t, unit: Mvar; is the apparent power of the photovoltaic converter, unit: MVA; is the photovoltaic active power output at time t, unit: MW.

[0071] The reactive power output of the fan module is limited by the power factor and active power output. That is, the wind power constraint condition is:

[0072]

[0073] In the formula, is the upper limit of the fan reactive power output at time t, unit: Mvar; is the fan active power output at time t, unit: MW; is the lower limit of the fan power factor.

[0074] Both the active and reactive powers in the hydrogen production system need to reach balance. That is, the electrolyzer constraint condition is:

[0075]

[0076] In the formula, is the line reactive power at time t, unit: MW, Mvar; is the photovoltaic reactive power output at time t, unit: Mvar; is the fan reactive power output at time t, unit: Mvar; is the grid active power output at time t, unit: MW; is the reactive power output of the power grid at time t, with the unit of Mvar.

[0077] Step S4: Determine the objective function of the wind-solar-hydrogen system according to the optimization requirements of the wind-solar-hydrogen system;

[0078] Specifically, the objective function includes the voltage fluctuation at the electrolyzer connection point, the power fluctuation of the electrolyzer, the line loss, the power support of the power grid, and the hydrogen production amount.

[0079] The voltage fluctuation at the electrolyzer connection point reduces the electrolytic hydrogen production efficiency. The objective function with the minimum voltage fluctuation at the electrolyzer connection point is:

[0080] ;

[0081] In the formula, is the electrolyzer voltage fluctuation value; T is the system calculation period.

[0082] The power fluctuation of the electrolyzer reduces the electrolytic hydrogen production efficiency. The objective function with the minimum power fluctuation of the electrolyzer is:

[0083] ;

[0084] Reducing the line loss can improve the hydrogen production power of the system, and then improve the economic benefit of the system. It is also one of the important indicators. The objective function with the minimum line loss is:

[0085] ;

[0086] In the formula, is the total active power loss of the line, with the unit of MW; is the active power loss of line 23, with the unit of MW; is the active power loss of line 24, with the unit of MW; is the active power loss of line 25, with the unit of MW;

[0087] The active power support of the power grid for hydrogen production will increase the hydrogen production cost. Making full use of solar and wind energy for hydrogen production is beneficial to improving the economic benefit of the system. The system aims to minimize the active power of the power grid. In the wind-solar-hydrogen system, both the photovoltaic and wind power modules have reactive power regulation capabilities, and it is expected that the reactive power is balanced locally. The objective function with the minimum power support of the power grid is:

[0088] ;

[0089] In the formula, is the total active power output of the power grid, with the unit of MW; is the total reactive power output of the power grid, with the unit of Mvar;

[0090] The main income of the wind-solar-hydrogen system comes from selling hydrogen. Increasing the hydrogen production is beneficial to improving the system economy. The objective function aiming at the maximum hydrogen production is as follows:

[0091] ;

[0092] In the formula, is the total hydrogen production of the system, with the unit of Nm 3 ; is the maximum hydrogen production of the system at a unit time, with the unit of Nm 3 .

[0093] The introduction of the hydrogen production efficiency correction in the hydrogen production objective function can make it closer to the actual hydrogen production of the electrolyzer. The system aims at the maximum hydrogen production as one of the goals, which can coordinate the output of each module to ensure a high hydrogen production level and improve the economic benefits of the system.

[0094] Step S5: Obtain the parameters of the wind-solar-hydrogen system;

[0095] Specifically, the parameters of the wind-solar-hydrogen system include the rated voltage of the system, line impedance, apparent power of the photovoltaic converter, fan power factor, and rated power of the electrolyzer.

[0096] The parameters of the wind-solar-hydrogen system represent the actual operating system data. Different parameters mean that the energy management needs to adapt to different systems. Among them, the rated voltage of the system determines the grid connection level of the system, and voltage levels such as 220 kV, 110 kV, and 35 kV are all available. The line impedance is determined according to the system line selection and operating environment, which is the main factor affecting the line loss. The apparent power of the photovoltaic converter is determined according to the equipment option, which is used to determine the maximum reactive power output of the photovoltaic module. The fan power factor is selected according to the fan model, which is used to determine the maximum reactive power output of the fan module. The rated power of the electrolyzer is determined according to the electrolyzer model, which is the maximum hydrogen production power of the hydrogen production module.

[0097] Step S6: Initialize the population according to the strength Pareto evolutionary algorithm in combination with the constraint conditions;

[0098] Specifically, the population includes photovoltaic reactive power output, fan reactive power output, electrolyzer active power, and electrolyzer connection point voltage variables. The wind-solar-hydrogen system takes the photovoltaic reactive power output, fan reactive power output, electrolyzer active power, and electrolyzer connection point voltage as unknown solutions, which are randomly generated through the strength Pareto evolutionary algorithm and combined to form a population, and the system power flow can be calculated.

[0099] Step S7: Calculate the reactive power using the electrolyzer model, and determine the active power, reactive power, and node voltage of each node through power flow calculation in combination with the population, photovoltaic active power, wind power active power, and wind-solar-hydrogen system parameters;

[0100] Specifically, the electrolyzer model can calculate the reactive power of the electrolyzer based on the existing voltage and active power. Combining the reactive power, active power, and voltage of the electrolyzer, the reactive power of the photovoltaic system, the reactive power of the fan, the active power of the energy storage, the reactive power of the energy storage, the active power of the photovoltaic system input to the system, the active power of the wind power, and the system line impedance parameters, the voltage and power of each node in the system can be calculated using the power flow formula as follows:

[0101] The node voltage is determined by the active and reactive power outputs of wind power, photovoltaic power, and the power grid. The change in the reactive power of the electrolyzer will also affect the voltage of each node in the system. The voltage formulas for nodes 1 and 2 are as follows:

[0102]

[0103] In the formula, is the voltage of node 2 at time t, in kV; is the voltage of node 1 at time t, in kV; is the longitudinal component of the voltage drop at node 1, in kV; is the transverse component of the voltage drop at node 1, in kV; is the active power at node 1, in MW; is the resistance of line 12, in Ω; is the reactive power at node 1, in Mvar; is the reactance of line 12, in Ω.

[0104] The voltage formula for node 3 is as follows:

[0105]

[0106] In the formula, is the voltage of node 3 at time t, in kV; is the longitudinal component of the voltage drop at node 2, in kV; is the transverse component of the voltage drop at node 2, in kV; is the active power transmitted from node 2 to node 3, in MW; is the resistance of line 23, in Ω; is the reactive power transmitted from node 2 to node 3, in Mvar; is the reactance of line 23, in Ω.

[0107] The voltage formula for node 4 is as follows:

[0108]

[0109] In the formula, is the voltage of node 4 at time t, in kV; The active power transmitted from node 2 to node 4, with the unit of MW; The resistance of line 24, with the unit of Ω; The reactive power transmitted from node 2 to node 4, with the unit of Mvar; The reactance of line 24, with the unit of Ω.

[0110] The voltage formula of node 5 is as follows:

[0111]

[0112] In the formula, The voltage of node 5 at time t, with the unit of kV; The active power transmitted from node 2 to node 5, with the unit of MW; The resistance of line 25, with the unit of Ω; The reactive power transmitted from node 2 to node 5, with the unit of Mvar; The reactance of line 25, with the unit of Ω.

[0113] The loss formula of line 12 is as follows:

[0114]

[0115] In the formula, The active power of line 12, with the unit of MW; The reactive power of line 12, with the unit of Mvar.

[0116] The loss formula of line 23 is as follows:

[0117]

[0118] In the formula, The active power of line 23, with the unit of MW; The reactive power of line 23, with the unit of Mvar.

[0119] The loss formula of line 24 is as follows:

[0120]

[0121] In the formula, The active power of line 24, with the unit of MW; The reactive power of line 24, with the unit of Mvar.

[0122] The loss formula of line 25 is as follows:

[0123]

[0124] In the formula, The active power of line 25, with the unit of MW; It is the reactive power of line 25, with the unit of Mvar.

[0125] Step S8: According to the objective function, combined with the active power, reactive power, node voltage and hydrogen production efficiency model of each node in the wind-solar-hydrogen system, calculate the target indicators of the wind-solar-hydrogen system;

[0126] Specifically, the target indicators include grid support, line loss, hydrogen production efficiency, and hydrogen production volume. The active power and reactive power of the power grid can be obtained according to the active power and reactive power calculation formulas of the power grid in step S4, which is the grid support amount. The degree of dependence of the wind-solar-hydrogen system on the power grid can be compared. The smaller the grid support amount, the smaller the degree of dependence of the system on the power grid. The system line loss can be obtained according to the line loss calculation formula in step S4. The rationality of the reactive power output scheme can be judged by comparing the line loss. The smaller the line loss, the more reasonable the reactive power output scheme. The system hydrogen production efficiency can be obtained according to the hydrogen production efficiency model in step S2. The hydrogen production with the same power can be compared. The higher the hydrogen production, the higher the hydrogen production efficiency. The system hydrogen production volume can be obtained according to the hydrogen production volume calculation formula in step S4. The rationality of the active power and reactive power distribution scheme can be judged by comparing the hydrogen production volume. The higher the hydrogen production volume, the more reasonable the scheme.

[0127] Step S9: The population compares with each other according to the target indicators, and forms an optimal solution set by using the screening principle in the strength Pareto evolutionary algorithm, and regenerates the population by using the crossover and mutation models in the strength Pareto evolutionary algorithm;

[0128] Specifically, the comparison of the target indicators means that a group of populations calculate the grid support, line loss, hydrogen production efficiency, and hydrogen production volume targets respectively according to the calculation formula, and delete the populations in which all 4 targets are smaller than another group. Through screening, a single-objective optimal and comprehensive-objective optimal solution set can be formed, and the unreasonable schemes of active power and reactive power distribution can be removed.

[0129] Step S10: Judge whether the iteration of the strength Pareto evolutionary algorithm reaches the upper limit. If it reaches, execute step S11. If it does not reach, execute step S7;

[0130] Specifically, the iteration of the strength Pareto evolutionary algorithm is a process of continuously generating new populations by using the crossover and mutation rules of the strength Pareto evolutionary algorithm for the optimal solution set, comparing the grid support, line loss, hydrogen production efficiency, and hydrogen production volume targets of the new population and the original optimal population, and screening out the new optimal solution set.

[0131] Step S11: Assign weights to each target indicator, calculate the target fitness of the optimal solution set according to the objective function multiplied by the weights, select the minimum value of the target fitness to form the optimal population, and obtain the optimal energy management scheme.

[0132] Specifically, the weights assigned to the target indicators can be changed according to requirements, representing the importance of grid support, line loss, hydrogen production efficiency, and hydrogen production volume targets in the current wind-solar-hydrogen system respectively. The target fitness is formed by accumulating the product of the target and the weight. By comparing the magnitudes of the target fitness data, the population corresponding to the smallest value is selected to form the optimal solution. Different weights can select different solutions from the solution set to meet different energy management requirements.

[0133] As can be seen from the above embodiments, the present application adopts an energy management method for optimizing the access point voltage and power of the electrolyzer module, coordinates the active power and reactive power outputs of the photovoltaic module, wind turbine module, energy storage module, and hydrogen production module in the wind-solar-hydrogen system, takes into account the impact of voltage and power fluctuations on hydrogen production by electrolyzers, reduces the voltage and power fluctuations at the electrolyzer access point, so it overcomes the problem of reduced hydrogen production efficiency of electrolyzers caused by voltage and power fluctuations, takes into account the line loss of the wind-solar-hydrogen system, reduces the loss as much as possible while improving the hydrogen production efficiency, also takes into account the goal of increasing the hydrogen production output, increases the hydrogen production power as much as possible, and thus achieves the effects of increasing the system revenue and reducing the hydrogen production cost.

[0134] Embodiment:

[0135] The wind-solar system is as Figure 1 shown, and the system parameters are shown in Table 1.

[0136] Table 1 Wind-solar-hydrogen system parameters

[0137]

[0138] The energy management optimization method of the wind-solar-hydrogen system is adopted to verify the effectiveness of improving hydrogen production efficiency by optimizing the electrolyzer voltage and power fluctuations.

[0139] The actual active power outputs of the photovoltaic and wind turbines in the wind-solar-hydrogen system are selected as Figure 3 shown. The energy management method for optimizing voltage and power is introduced, and the reactive power of the photovoltaic, wind turbine, power grid, and electrolyzer and the active power of the power grid and electrolyzer are arranged as Figures 4 - 9 shown; the voltages at nodes 2-5 are as Figure 10 shown. After optimization, the hydrogen production power of the electrolyzer increases, the reactive power demand increases, and the difficulty of optimizing voltage fluctuations increases. On this basis, the voltage fluctuations after optimization are still slightly improved compared with those before optimization; the losses of lines 12, 23, 24, and 25 are as Figures 11 - 14 shown, and the total line loss is as Figure 15 shown. After optimization, the line loss increases, mainly because the hydrogen production power increases and the increased part is supplied by the power grid. At the same time, the line loss corresponding to the unit hydrogen production power before optimization is 1.37%, and after optimization it is 1.36%. It can be seen that the coordinated reactive power output has optimized the line loss; the efficiency optimization results are as Figure 16As shown, the hydrogen production efficiency is significantly improved, and more hydrogen is produced with the same hydrogen production power. The energy management strategy significantly optimizes the electrolytic cell voltage and power fluctuations while taking into account the line loss. Although the power output of the power grid is increased, the increase in hydrogen production is even greater, improving the economy of the system. The energy management method for the wind-solar-hydrogen system that optimizes the electrolytic cell voltage and power is effective.

[0140] Corresponding to the embodiment of the energy management method for the wind-solar-hydrogen system that optimizes the electrolytic cell voltage and power described above, the present application also provides an embodiment of an energy management device for the wind-solar-hydrogen system that optimizes the electrolytic cell voltage and power.

[0141] Figure 17 It is a block diagram of an energy management device for a wind-solar-hydrogen system that optimizes the electrolytic cell voltage and power shown according to an exemplary embodiment. Refer to Figure 17 , the device includes:

[0142] The first acquisition module 1 is used to acquire the photovoltaic active power and wind power active power of the wind-solar-hydrogen system;

[0143] The model construction module 2 is used to construct an electrolytic cell model and a hydrogen production efficiency model according to the operating characteristics of the electrolytic cell;

[0144] The constraint condition determination module 3 is used to determine the constraint conditions according to the actual operation of the photovoltaic, wind power, and electrolytic cell;

[0145] The objective function determination module 4 is used to determine the objective function of the wind-solar-hydrogen system according to the optimization requirements of the wind-solar-hydrogen system;

[0146] The second acquisition module 5 is used to acquire the parameters of the wind-solar-hydrogen system;

[0147] The population initialization module 6 is used to initialize the population according to the strength Pareto evolutionary algorithm in combination with the constraint conditions;

[0148] The first calculation module 7 is used to calculate the reactive power using the electrolytic cell model, and determine the active power, reactive power, and node voltage of each node through power flow calculation in combination with the population, photovoltaic active power, wind power active power, and parameters of the wind-solar-hydrogen system;

[0149] The second calculation module 8 is used to calculate the target index of the wind-solar-hydrogen system according to the objective function in combination with the active power, reactive power, node voltage of each node of the wind-solar-hydrogen system and the hydrogen production efficiency model;

[0150] The population regeneration module 9 is used to compare the populations according to the target index, form an optimal solution set using the screening principle in the strength Pareto evolutionary algorithm, and regenerate the population using the crossover and mutation models in the strength Pareto evolutionary algorithm;

[0151] Iterative module 10 is used to determine whether the iteration of the intensity Pareto evolutionary algorithm reaches the upper limit. If it reaches the limit, the solution obtaining module 11 is executed; if it does not reach the limit, the first calculation module 7 is executed.

[0152] Solution obtaining module 11 is used to assign weights to each target index, calculate the objective fitness of the optimal solution set by multiplying the objective function by the weights, select the minimum value of the objective fitness to form the optimal population, and obtain the optimal energy management solution.

[0153] Regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0154] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial descriptions of the method embodiments. The device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this application. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0155] Correspondingly, the present application also provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method for optimizing the energy management of the wind-solar-hydrogen system for electrolytic cell voltage and power as described above.

[0156] Correspondingly, the present application also provides a computer-readable storage medium, on which computer instructions are stored, and when the instructions are executed by a processor, the method for optimizing the energy management of the wind-solar-hydrogen system for electrolytic cell voltage and power as described above is implemented.

[0157] After considering the specification and practicing the content disclosed herein, those skilled in the art will easily think of other implementation schemes of the present application. The present application aims to cover any variations, uses, or adaptive changes of the present application, which follow the general principles of the present application and include the common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present application are pointed out by the claims.

[0158] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A wind-solar hydrogen system energy management method for optimizing the voltage and power of the electrolyzer, characterized in that: include: Step 1: Obtain the photovoltaic active power and wind power active power of the wind-solar-hydrogen system; Step 2: Construct an electrolyzer model and a hydrogen production efficiency model based on the electrolyzer operation characteristics; Step 3: Determine the constraints based on the actual operation of photovoltaic, wind power and electrolyzer; Step 4: Determine the objective function of the wind-solar-hydrogen system based on the optimization requirements of the wind-solar-hydrogen system; Step 5: Obtain wind-solar-hydrogen system parameters; Step 6: Initialize the population according to the intensity Pareto evolutionary algorithm in combination with the constraints; Step 7: Calculate reactive power using the electrolyzer model, combine population, photovoltaic active power, wind power active power, and wind-solar-hydrogen system parameters, and determine active power, reactive power, and node voltage of each node through power flow calculation; Step 8: According to the objective function, combined with the active power, reactive power, node voltage and hydrogen production efficiency model of each node of the wind-solar-hydrogen system, the target indicators of the wind-solar-hydrogen system are calculated; Step 9: The populations are compared with each other according to the target indicators, the selection principle in the intensity Pareto evolutionary algorithm is used to form the optimal solution set, and the crossover and mutation model in the intensity Pareto evolutionary algorithm is used to regenerate the population; Step 10: Determine whether the iteration of the intensity Pareto evolutionary algorithm reaches the upper limit, if so, execute step 11, if not, execute step 7; Step 11: assign weights to each target indicator, calculate the target fitness of the optimal solution set according to the target function multiplied by the weight, select the minimum value of the target fitness to form the optimal population, and obtain the optimal energy management plan; Wherein, the electrolytic cell model is as follows: ， In the formula, is the reactive power of the electrolyzer, in Mvar; Run the system minute; is the voltage at the access point of the electrolyzer, in kV; is the equivalent reactance of the electrolytic cell, in Ω; Allocate electrolyzer active power to the system in MW; The hydrogen production efficiency model is as follows: In the formula, For voltage fluctuation ,t s The ratio of hydrogen production efficiency restored at the moment, in %; For voltage fluctuation ,t s The actual hydrogen production efficiency restored at the moment, in %; is the actual maximum hydrogen production efficiency of the electrolyzer, in %; , is an intermediate variable; is the power fluctuation ratio of the electrolytic cell, in %; For electrolytic cell Minute active power, in MW; For electrolytic cell -1 minute active power, in MW; is the rated power of the electrolyzer, in MW; is the average hydrogen production efficiency at time t, in %; The objective function includes voltage fluctuation at the access point of the electrolyzer, power fluctuation of the electrolyzer, line loss, power support of the power grid, and hydrogen production; Among them, the objective function with the goal of minimizing the voltage fluctuation at the electrolyzer access point is: ； In the formula, is the voltage fluctuation value of the electrolytic cell; T is the system calculation period; The objective function to minimize the electrolytic cell power fluctuation is: ； The objective function with the minimum line loss as the goal is: ； In the formula, is the total active power loss of the line, in MW; is the active power loss of line 23, in MW; is the active power loss of line 24, in MW; is the active power loss of line 25, in MW; The objective function to minimize the grid power support is: ； In the formula, is the total active power output of the power grid, in MW; is the total reactive power output of the power grid, in Mvar; The objective function for maximizing hydrogen production is: ； In the formula, is the total hydrogen production of the system, in Nm 3 ; is the maximum hydrogen production of the system per unit time, in Nm 3 .

2. The method according to claim 1, characterized in that: The constraints include photovoltaic constraints, wind power constraints, and electrolyzer constraints.

3. The method according to claim 1, characterized in that The wind-solar-hydrogen system parameters include system rated voltage, line impedance, photovoltaic inverter apparent power, wind turbine power factor, and electrolyzer rated power.

4. The method according to claim 1, characterized in that: The population includes photovoltaic reactive power output, wind turbine reactive power output, electrolyzer active power, and electrolyzer access point voltage variables.

5. The method according to claim 1, characterized in that The target indicators include grid support, line loss, hydrogen production efficiency, and hydrogen production volume.

6. An energy management device for a wind-solar hydrogen system that optimizes the voltage and power of an electrolyzer, characterized in that: include: The first acquisition module is used to acquire the photovoltaic active power and wind power active power of the wind-solar-hydrogen system; A model building module is used to build an electrolyzer model and a hydrogen production efficiency model based on the electrolyzer operation characteristics; The constraint determination module is used to determine the constraint conditions according to the actual operation of photovoltaic, wind power and electrolyzer; An objective function determination module is used to determine the objective function of the wind-solar-hydrogen system according to the optimization requirements of the wind-solar-hydrogen system; The second acquisition module is used to obtain the wind-solar-hydrogen system parameters; A population initialization module, used to initialize the population according to the intensity Pareto evolutionary algorithm in combination with the constraint conditions; The first calculation module is used to calculate reactive power using the electrolyzer model, and determine the active power, reactive power, and node voltage of each node through power flow calculation in combination with population, photovoltaic active power, wind power active power, and wind-solar-hydrogen system parameters; The second calculation module is used to calculate the target index of the wind-solar hydrogen system according to the objective function and in combination with the active power, reactive power, node voltage and hydrogen production efficiency model of each node of the wind-solar hydrogen system; A population regeneration module is used to compare populations with each other according to the target indicators, form an optimal solution set using the selection principle in the intensity Pareto evolutionary algorithm, and regenerate the population using the crossover and mutation model in the intensity Pareto evolutionary algorithm; An iteration module is used to determine whether the iteration of the intensity Pareto evolutionary algorithm reaches an upper limit, and if so, execute the solution acquisition module; if not, execute the first calculation module; A scheme acquisition module is used to assign weights to each target indicator, calculate the target fitness of the optimal solution set according to the target function multiplied by the weight, select the minimum value of the target fitness to form the optimal population, and obtain the optimal energy management scheme; Wherein, the electrolytic cell model is as follows: ， In the formula, is the reactive power of the electrolyzer, in Mvar; Run the system minute; is the voltage at the access point of the electrolyzer, in kV; is the equivalent reactance of the electrolytic cell, in Ω; Allocate electrolyzer active power to the system in MW; The hydrogen production efficiency model is as follows: In the formula, For voltage fluctuation ,t s The ratio of hydrogen production efficiency restored at the moment, in %; For voltage fluctuation ,t s The actual hydrogen production efficiency restored at the moment, in %; is the actual maximum hydrogen production efficiency of the electrolyzer, in %; , is an intermediate variable; is the power fluctuation ratio of the electrolytic cell, in %; For electrolytic cell Minute active power, in MW; For electrolytic cell -1 minute active power, in MW; is the rated power of the electrolyzer, in MW; is the average hydrogen production efficiency at time t, in %; The objective function includes voltage fluctuation at the access point of the electrolyzer, power fluctuation of the electrolyzer, line loss, power support of the power grid, and hydrogen production; Among them, the objective function with the goal of minimizing the voltage fluctuation at the electrolyzer access point is: ； In the formula, is the voltage fluctuation value of the electrolytic cell; T is the system calculation period; The objective function to minimize the electrolytic cell power fluctuation is: ； The objective function with the minimum line loss as the goal is: ； In the formula, is the total active power loss of the line, in MW; is the active power loss of line 23, in MW; is the active power loss of line 24, in MW; is the active power loss of line 25, in MW; The objective function to minimize the grid power support is: ； In the formula, is the total active power output of the power grid, in MW; is the total reactive power output of the power grid, in Mvar; The objective function for maximizing hydrogen production is: ； In the formula, is the total hydrogen production of the system, in Nm 3 ; is the maximum hydrogen production of the system per unit time, in Nm 3 .

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