Voltage regulation and control method for user-side electrical hydrogen production distributed access scene

Abstract

The invention provides a voltage regulation and control method for a user-side electrical hydrogen production distributed access scene, and belongs to the technical field of power voltage regulation. The method comprises the following steps: establishing an electrical hydrogen production equipment model according to an obtained user-side electrical hydrogen production related data set; establishing a voltage optimization regulation and control model of the power distribution network containing the user-side electric hydrogen production based on a generalized Benders decomposition method by taking the minimum power distribution network loss as a target; the method comprises the following steps: establishing a power distribution network robust state estimation method containing user-side electrical hydrogen production state information aiming at the problem of voltage jump of a power distribution network, and determining a robust operation strategy of a power grid side voltage regulation and control device based on a robust optimization method with Wasserstein measurement; according to the method, a coupling regulation and control method of power distribution network side voltage regulation and user side electrical hydrogen production equipment is determined, modeling is carried out on the control cost of the electrical hydrogen production equipment, and finally, the target of the minimum control cost of the electrical hydrogen production equipment is introduced on the basis of the minimum power distribution network loss, so that the final coupling regulation and control method is obtained. And voltage regulation and control for the user-side electrical hydrogen production distributed access scene are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power voltage regulation, and in particular to a voltage regulation method for a distributed access scenario of hydrogen production by electricity at a user side. Background Art

[0002] With the advancement of global energy transformation and the proposal of carbon reduction targets, hydrogen production from electricity has attracted much attention as a clean energy technology. Hydrogen production from electricity uses electricity to drive the electrolysis of water to generate hydrogen, aiming to use renewable energy or low-carbon energy to replace traditional fuels and reduce greenhouse gas emissions. In this context, more and more hydrogen production equipment has begun to be decentralized to the sites of power users, such as factories, enterprises and residential areas, so as to more directly use local power resources for hydrogen production. However, the decentralized access of hydrogen production equipment on the user side has brought new challenges to the power system, especially in terms of grid voltage management. Traditional power system design and voltage regulation strategies are often concentrated on large power plants and power grid backbones, and are not applicable to the access scenarios of small and decentralized hydrogen production equipment. The sudden start or stop of hydrogen production equipment on the user side and the fluctuation of its power demand may cause instability of grid voltage and even affect the overall operational stability of the grid.

[0003] The existing user-side hydrogen production voltage control method is mainly based on the energy input and output model. It is achieved by setting a voltage regulation controller at each node in the network, and adjusting power and voltage according to the characteristics of different voltage regulation equipment and the load needs of the regional network while ensuring the grid operation indicators. From the macro perspective of the grid, this control method is a centralized method with optimal control. However, from the micro perspective of the local network, the voltage regulation of the user-side hydrogen production device will also affect the voltage regulation control decision of the grid-side voltage regulation device. The existing voltage regulation method only models from the steady-state level, and does not perform voltage regulation analysis on the hydrogen production process. At the same time, the influence of various internal states and control variables of the hydrogen production device on the voltage, current and other factors of the distribution network is not clear, resulting in low coupling and poor interactivity between the voltage regulation of the user-side hydrogen production device and the voltage regulation method on the grid side.

[0004] Therefore, for the decentralized access scenario of hydrogen production on the user side, it is necessary to establish an external characteristic model of the internal variables of the hydrogen production device, and by analyzing the relationship between the voltage regulation of the hydrogen production device on the user side and the coupled voltage regulation of the voltage control device on the grid side, we can overcome the voltage instability and sudden changes at the end of the distribution network caused by large-scale access of hydrogen production on the user side, and propose a method for coordinated operation of the voltage regulation of the hydrogen production device on the user side and the voltage regulation of the voltage control device on the grid side to improve the voltage level of the distribution network. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a voltage control method for the decentralized access scenario of hydrogen production by electricity on the user side in view of the deficiencies of the above-mentioned prior art. The method uses hydrogen production by electricity as a voltage regulation means to solve the problem of voltage reduction at the end of the distribution network after large-scale access of hydrogen production by electricity.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a voltage control method for a distributed access scenario of hydrogen production by electricity at the user side, comprising the following steps:

[0007] Step 1: In view of the low voltage or overvoltage at the end of the distribution network caused by large-scale access of hydrogen production on the user side, obtain the relevant data set of hydrogen production on the user side; then obtain the power consumption characteristics of each hydrogen production load on the user side, the energy flow equation of the hydrogen production system and the external power characteristics of hydrogen production on the user side;

[0008] The obtained user-side hydrogen production related data set includes a user-side hydrogen production load data set, a hydrogen production system status data set, and a hydrogen production system energy flow data set;

[0009] Obtaining the power consumption characteristics of each user-side hydrogen production load according to the user-side hydrogen production load data set; the user-side hydrogen production load power consumption characteristics represent the relationship between the user-side hydrogen production load current and the distribution network voltage;

[0010] The energy flow equation of the hydrogen production system is obtained according to the state data set of the hydrogen production system; the energy flow equation of the hydrogen production system is used to describe the relationship between the control variables and state variables of the hydrogen production operation on the user side and the hydrogen production load current on the user side; the state variables include temperature, pressure, voltage and current density;

[0011] Obtaining the external characteristics of the user-side hydrogen production power according to the energy flow data set of the hydrogen production system; the external characteristics of the user-side hydrogen production power represent the relationship between the user-side hydrogen production power and the user-side hydrogen production load current;

[0012] Step 2: Calculate the Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production operation and the voltage of each node in the distribution network based on the user-side hydrogen production related data set obtained in step 1, obtain the correlation analysis results of the control variables and state variables of the hydrogen production equipment operation and the voltage of each node in the distribution network, and establish the hydrogen production equipment model based on the analysis results;

[0013] Modeling of the electric hydrogen production plant around an alkaline electrolyzer; the total voltage across the alkaline electrolyzer is U el By the reversible voltage U oc , Activation polarity voltage U act and ohmic polarity voltage U ohm The total voltage across the alkaline electrolytic cell is expressed as:

[0014] Uel =U oc +U act +U ohm (1)

[0015] Reversible voltage U oc The following formula represents:

[0016] U oc =v0-v1(T0+T el )+v2(T0+T el )ln(T0+T el )+v3(T0+T el ) 2 (2)

[0017] Among them, v0, v1, v2, v3 are the temperature empirical coefficients of the electric hydrogen production equipment, T0 is the absolute temperature inside the alkaline electrolyzer, T el is the operating temperature of the electrolyzer unit;

[0018] The ohmic polarity voltage U ohm It is expressed as:

[0019]

[0020] Among them, I el is the instantaneous current flowing through the electrolytic cell unit, A is the surface area of ​​the alkaline electrolytic cell, r1, r2, r3, and r4 are the resistance coefficients of the electrolytic cell unit respectively;

[0021] According to the Tafel equation, the activation polarity voltage U act is a nonlinear function of the activation current and is expressed as:

[0022]

[0023] Among them, I el is the instantaneous current flowing through the electrolytic cell unit, s1, s2, s3, t1, t2, t3 are Tafel empirical coefficients, A el is the electrode area;

[0024] Power P of a single electrolyzer unit el It is expressed as:

[0025] P el =U el I el (5)

[0026] Therefore, the voltage U tol and the power P of the electrolyzer stack tol It is described by formula (9) and formula (10):

[0027] Utol =NU el (6)

[0028] P tol =NP el (7)

[0029] Wherein, N is the number of electrolytic cell units constituting the electrolytic cell stack;

[0030] Theoretical partial pressure of electrolyte U th It is expressed as:

[0031]

[0032] Among them, U th (25°C, 1atm) is the thermoneutral voltage of the electrolyzer unit at 25°C and 1 standard atmosphere, ΔS is the change in internal entropy in the hydrogen production reaction, and z is the number of electrons required to transfer to produce 1 mole of hydrogen;

[0033] The efficiency of an alkaline electrolyzer refers to the voltage efficiency of the alkaline electrolyzer, which is defined as the theoretical partial pressure of the electrolyte U th The actual partial pressure of the electrolyte U el The ratio of v The calculation formula is as follows:

[0034]

[0035] According to Faraday's law, the Faraday efficiency η F The specific formula is:

[0036]

[0037] Among them, f1 and f2 are parameters related to Faraday efficiency, and the unit is mA 2 / cm 4 ;

[0038] The hydrogen production efficiency of alkaline electrolyzer is η el It is expressed as:

[0039] η el =η F η v (11)

[0040] For an electric hydrogen production device containing n alkaline electrolyzers, the molar flow rate of hydrogen production is It is expressed as:

[0041]

[0042] in, is the power of the i-th electrolytic cell;

[0043] Hydrogen production volume flow The specific formula is:

[0044]

[0045] in, is the molar flow rate of hydrogen;

[0046] Determined according to the following formula:

[0047]

[0048] Matrices of control variables and state variables of electric hydrogen production equipment E2H It is expressed as:

[0049]

[0050] According to the power consumption characteristics of the user-side hydrogen production load, the energy flow equation of the hydrogen production system and the external power characteristics of the hydrogen production on the user side obtained in step 1, the Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production operation and the voltage of each node in the distribution network is calculated jointly, and the correlation analysis results of the control variables and state variables of the hydrogen production equipment operation and the voltage of each node in the distribution network are preliminarily obtained. The calculation formula is as follows:

[0051]

[0052] Among them, ρ is the node The Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production equipment in the distribution network with each node and the voltage of each node in the distribution network, For node i node The original values ​​of each control variable and each state variable of the hydrogen production equipment. is the average value of each control variable and each state variable of the electric hydrogen production equipment, For node i node Voltage, is the average voltage of each node in the distribution network;

[0053] The voltage of each node in the distribution network is analyzed by using the grey correlation analysis method. The main sequence, each distributed hydrogen production control variable and state variable As a subsequence, after normalization, the grey correlation degree ζ(i node ), forming an associated sequence, the calculation formula is as follows:

[0054]

[0055] Among them, i nodeis the number of nodes in the power distribution network, k is the ordinal number of the control variables and state variables of the hydrogen production equipment, x0(i node ) is the distribution network node i node Voltage at x k (i node ) is the distribution network node i node The control variables and state variables of the kth electric hydrogen production equipment;

[0056] Based on this, the correlation coefficient matrix Matrices of the voltages of each node in the distribution network and the control variables and state variables of each distributed hydrogen production are established. Gra It is expressed as:

[0057] Matric Gra =[ζ k (i node )] (18)

[0058] So we can get the description of the influence of the state variables and control variables of hydrogen production at the user side on the voltage change ΔU at the end of the distribution network. Net The equivalent mathematical model is shown in the following formula:

[0059]

[0060] Step 3: Using the existing grid-side voltage regulation equipment, according to the variation law of the terminal voltage after large-scale access of distributed hydrogen production and the voltage regulation characteristics of the grid-side voltage regulation equipment, with the minimum distribution network loss as the goal, based on the generalized Benders decomposition method, establish a voltage optimization regulation model for the user-side hydrogen production distribution network, and obtain regulation strategies for various grid-side voltage regulation equipment;

[0061] The distribution network loss Loss(I jf ,R net ) is calculated using the root mean square method, as shown in the following formula:

[0062]

[0063] Among them, R net is the resistance value of the distribution network, I jf is the root mean square current of the distribution network, as shown in the following formula:

[0064]

[0065] Among them, P t , Q t are the three-phase active power and three-phase reactive power of the distribution network, U t is the simultaneous line voltage of the distribution network;

[0066] The process of establishing the voltage optimization control model of the distribution network containing user-side hydrogen production based on the generalized Benders decomposition method is as follows: the minimum distribution network loss is defined as the main problem, and the grid-side voltage regulation equipment constraints and hydrogen production equipment constraints are used as solutions. The problem is described as follows:

[0067]

[0068] Among them, g device (I jf ,t) is the set of grid-side voltage regulation equipment constraints, g E2H (I jf ,t) is the set of constraints for the hydrogen production equipment; the set of constraints for the hydrogen production equipment g E2H (I jf ,t) is:

[0069]

[0070] Among them, α i (t) is the start-up action of the electric hydrogen production equipment, β i (t) is the shutdown action of the electric hydrogen production equipment, μ i (t) is the start and stop state of the electric hydrogen production equipment, T is the total adjustment time, α max With β max are the maximum number of startups and shutdowns of the hydrogen production equipment in one day, P i (t) is the power of the electric hydrogen production equipment, P max and P min are the maximum power and minimum power of the electric hydrogen production equipment, ΔP control I is the maximum adjustment power allowed by the hydrogen production equipment per unit time. min is the minimum operating current of the electric hydrogen production equipment, I max The maximum operating current of the electric hydrogen production equipment;

[0071] The constraints of the on-load tap-changing transformer installation are:

[0072]

[0073] Among them, Tap(t) is the tap number of the on-load tap-changing transformer, min and Tap max The tap position of the on-load tap-changing transformer is the minimum position and the tap position of the on-load tap-changing transformer is the maximum position, ΔTap allow The maximum number of gears that the on-load voltage-changing transformer can adjust within a unit time;

[0074] The static VAR compensation device constraints are:

[0075]

[0076] in, is the number of static VAR compensation devices put into the power grid, λ max is the maximum number of static VAR compensation devices that can be put into operation, Δλ control The maximum change in the number of static VAR compensation devices put into use per unit time;

[0077] Step 4: In view of the voltage mutation problem of the distribution network caused by the failure of the hydrogen production equipment and the extreme load mutation, a robust state estimation method of the distribution network containing the user-side hydrogen production state information is established, and the robust operation strategy of the grid-side voltage control device is determined based on the robust optimization method with Wasserstein metric;

[0078] The worst-case scenario of the failure and load mutation extreme conditions of the hydrogen production equipment is characterized by the distributed robust method, and then the Wasserstein divergence is used as the fuzzy set M of the uncertainty measurement of the distributed robust method. ε , thereby establishing an "uncertainty model" to verify the regulation performance of the electric hydrogen production equipment under extreme conditions of faults and load mutations; the fuzzy set M ε The specific formula is:

[0079]

[0080] in, is the probability distribution of the actual working power of the electric hydrogen production equipment, is the empirical distribution of the operating power of the electric hydrogen production equipment, M(ξ) is all the definitions in the Wasserstein divergence d w The probability distribution space under , ε is the fuzzy set radius;

[0081] According to the "uncertainty model", the original "voltage optimization control model of the distribution network including user-side hydrogen production" is improved, and the specific formula of the new "optimization control model" is obtained as follows:

[0082]

[0083] Among them, E P It means that the Wasserstein divergence d is defined w Moments of uncertainty measures under ;

[0084] Step 5: Based on step 4, take the hydrogen production equipment as the control object, determine the coupling control method between the voltage regulation on the distribution network side and the hydrogen production equipment on the user side, then model the control cost of the hydrogen production equipment, and finally introduce the goal of "minimizing the control cost of hydrogen production equipment" on the basis of minimum distribution network loss to obtain the final coupling control method, so as to realize voltage control for the distributed access scenario of hydrogen production on the user side;

[0085] The internal state variables and control variables of the hydrogen production equipment are mapped to the external characteristics of the hydrogen production equipment, and the state equation of the grid-side voltage regulation system of the hydrogen production equipment is combined. The voltage regulation coupling equation of the load-side hydrogen production device and the grid-side voltage regulation device is obtained by combining eigenvalue analysis and relative gain matrix theory.

[0086] According to the coupling equation of voltage regulation of load-side electric hydrogen production device and voltage regulation of grid-side voltage regulation device, on the basis of the minimum target of distribution network line loss, the minimum target of "minimum control cost of electric hydrogen production equipment" is introduced, and a dual-target voltage optimization control model is established. The power flow model is linearized based on the second-order cone optimization method, and a multi-objective optimization problem solving algorithm based on mixed integer NSGA-III is proposed, and the distribution network voltage optimization control method under the coupling of the two voltage regulation modes is obtained.

[0087] The control cost of hydrogen production equipment includes two aspects: one is the cost of controlling the hydrogen production amount according to the hydrogen demand on the user side; the other is the additional control cost caused by the voltage drop on the user side, which leads to a reduction in hydrogen production or the power adjustment of the hydrogen production equipment to meet the voltage regulation demand on the grid side when the voltage drop occurs at the end of the distribution network on the grid side;

[0088] The load control cost of hydrogen production is a function of the equipment's operating current, operating voltage, and power. The matrix constructed above is E2H The control variables and state variables of the hydrogen production equipment have been mapped to the distribution network parameters. Here, the load control cost is approximated as a function of the distribution network parameters, which is expressed as: cost(I jf ,R net ), and then the user's hydrogen production is used as a multi-objective solution constraint. The solution model of the multi-objective optimization model is expressed as:

[0089]

[0090] Among them, V subscribers The hydrogen production demand determined by the user side, is the amount of hydrogen produced by the electric hydrogen production equipment in the T period;

[0091] Finally, taking the different numerical ranges of voltage drop at the end of the distribution network as the basis for the execution strategy, a voltage control method for the distributed access scenario of hydrogen production by electricity on the user side is obtained.

[0092] The beneficial effects of adopting the above technical scheme are as follows: the present invention provides a voltage control method for the user-side electric hydrogen production distributed access scenario. Compared with the prior art, the method of the present invention combines the advantages of the voltage regulation of the user-side electric hydrogen production device and the voltage control device on the grid side, establishes an interactive influence relationship model and a coupled collaborative control model between the voltage regulation of the user-side electric hydrogen production equipment and the voltage optimization control model of the distribution network containing the user-side electric hydrogen production, and realizes the effective interaction of the user-side and grid-side voltage control methods in the user-side electric hydrogen production access scenario; at the same time, considering the electric hydrogen production load control cost, distribution network loss and the operation robustness of the distribution network under dangerous voltage conditions, a multi-objective voltage optimization control method of the distribution network under the coupling of two voltage regulation methods is proposed; the method of the present invention conducts voltage regulation analysis on the electric hydrogen production process, realizes the voltage regulation of the user-side electric hydrogen production device and the coupled voltage regulation of the grid-side voltage control device, and overcomes the voltage instability and mutation conditions at the end of the distribution network caused by large-scale electric hydrogen production on the user side. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] Figure 1 A flow chart of obtaining a user-side hydrogen production related data set provided by an embodiment of the present invention;

[0094] Figure 2 A structural diagram of an electrolyzer unit of an electric hydrogen production device provided in an embodiment of the present invention;

[0095] Figure 3 A schematic diagram of the oxidation-reduction reaction occurring at the cathode and anode of an alkaline electrolytic cell provided in an embodiment of the invention;

[0096] Figure 4 A schematic diagram of a simplified topological structure of a power grid including user-side hydrogen production provided by an embodiment of the present invention;

[0097] Figure 5 A flow chart of a method for obtaining a final coupling control provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0098] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0099] In this embodiment, a voltage control method for a distributed access scenario of hydrogen production by electricity at the user side is provided. Figure 1 As shown, the following steps are included:

[0100] Step 1: Obtain user-side hydrogen production related data sets for low voltage or overvoltage at the end of the distribution network caused by large-scale access of user-side hydrogen production;

[0101] The obtained user-side hydrogen production related data set includes a user-side hydrogen production load data set, a hydrogen production system status data set, and a hydrogen production system energy flow data set;

[0102] Obtaining the power consumption characteristics of each user-side hydrogen production load according to the user-side hydrogen production load data set; the user-side hydrogen production load power consumption characteristics represent the relationship between the user-side hydrogen production load current and the distribution network voltage;

[0103] The energy flow equation of the hydrogen production system is obtained according to the state data set of the hydrogen production system; the energy flow equation of the hydrogen production system is used to describe the relationship between the control variables and state variables of the hydrogen production operation on the user side and the hydrogen production load current on the user side; the state variables include temperature, pressure, voltage and current density;

[0104] Obtaining the external characteristics of the user-side hydrogen production power according to the energy flow data set of the hydrogen production system; the external characteristics of the user-side hydrogen production power represent the relationship between the user-side hydrogen production power and the user-side hydrogen production load current;

[0105] Step 2: Calculate the Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production operation and the voltage of each node in the distribution network based on the user-side hydrogen production related data set obtained in step 1, obtain the correlation analysis results of the control variables and state variables of the hydrogen production equipment operation and the voltage of each node in the distribution network, and establish the hydrogen production equipment model based on the analysis results;

[0106] The electric hydrogen production equipment includes alkaline water electrolysis (AWE) electric hydrogen production equipment, proton exchange membranes (PEM) electric hydrogen production equipment and solid oxide water electrolysis (SOE) electric hydrogen production equipment; although their hydrogen production principles are different, their core mainly includes two parts: an electrolyzer stack and a control device; the electrolyzer stack is a load composed of several electrolyzer units connected in series; the electrolyzer unit is the smallest unit in the electric hydrogen production equipment where the electric hydrogen production reaction occurs, such as Figure 2 As shown;

[0107] In this embodiment, the modeling of the electric hydrogen production equipment will also be carried out around the electrolyzer unit, taking the alkaline electrolyzer as an example;

[0108] Alkaline water electrolysis technology is the earliest developed technology, the most mature technology in practical application, and the lowest construction cost. Based on the principle of alkaline water electrolysis, electric hydrogen production equipment suitable for large-scale engineering applications can be produced;

[0109] The working principle of the electrolytic cell unit is shown in the figure. By applying a DC voltage to the positive and negative electrodes of the alkaline electrolytic cell unit, a local electric field is formed, so that the positive and negative ions in the electrolyte move in a directional manner under the drive of the local electric field, causing the cathode and anode of the alkaline electrolytic cell to undergo redox reactions, such as Figure 3 As shown;

[0110] In this embodiment, the chemical reaction equation for the redox reaction between the cathode and the anode of the alkaline electrolytic cell is:

[0111]

[0112] Modeling of the electric hydrogen production plant around an alkaline electrolyzer; the total voltage across the alkaline electrolyzer is U el Mainly composed of reversible voltage U oc , Activation polarity voltage U act and ohmic polarity voltage U ohm The total voltage across the alkaline electrolytic cell is expressed as:

[0113] U el =U oc +U act +U ohm (1)

[0114] In this embodiment, the reversible voltage U oc Also known as the open circuit voltage of the alkaline electrolytic cell, it is the minimum theoretical voltage; the activation polarity voltage U act Corresponding to the activation phenomenon of the cathode and anode in the alkaline electrolytic cell, it is the voltage generated when the electrochemical reaction occurs in the alkaline electrolytic cell; Ohmic polarity voltage U ohm Also called the Ohmic overpotential, it is the voltage generated by the internal resistance of the alkaline electrolytic cell;

[0115] The reversible voltage U oc It is determined by the Gibbs free energy during the electrolysis process, and the specific formula is:

[0116]

[0117] Where ΔG is the Gibbs free energy, z is the number of electrons required to produce 1 mole of hydrogen, and ΔS is the change in internal entropy during the hydrogen production reaction (ΔS(25°C, 1atm) = ΔS 0 ≈0.16 kj mol -1 ·K -1 ), F is the Faraday constant, ΔH is the enthalpy change during the hydrogen production reaction, T el is the operating temperature of the electrolyzer unit;

[0118] In this embodiment, the z value in the process of electric hydrogen production is 2;

[0119] In the Nerst equation, the reversible voltage U oc It is expressed as:

[0120]

[0121] Where U0 is the standard reversible voltage, R is the universal gas constant (R = 8.314 J·mol -1 ·K -1 ), and are the pressures of hydrogen and oxygen, respectively. is the water activity between the anode and the electrolyte of the alkaline electrolyzer;

[0122] Combining the analysis of formula (2) and formula (3), it can be seen that in the process of electric hydrogen production, temperature is the main factor affecting the voltage of the electrolyzer unit. At the rated operating temperature of the electric hydrogen production equipment (45℃ to 70℃), the change in pressure has a significant effect on the reversible voltage U oc The influence of is almost negligible; therefore, the reversible voltage U oc It is usually expressed by the following formula:

[0123] U oc =v0-v1(T0+T el )+v2(T0+T el )ln(T0+T el )+v3(T0+T el ) 2 (4)

[0124] Among them, v0, v1, v2, and v3 are the temperature empirical coefficients of the electric hydrogen production equipment, and T0 is the absolute temperature inside the alkaline electrolyzer;

[0125] The ohmic polarity voltage U ohm It is mainly caused by the resistance of electrodes, bipolar plates, diaphragms and electrolytes to the flow of charge, which can be expressed as:

[0126]

[0127] Among them, I el is the instantaneous current flowing through the electrolytic cell unit, A is the surface area of ​​the alkaline electrolytic cell, r1, r2, r3, and r4 are the resistance coefficients of the electrolytic cell unit respectively;

[0128] In this embodiment, r2 is the effect of temperature on the resistance of the electrode, bipolar plate and electron flow, and r3 and r4 are the effects of temperature on the components such as electrolyte and diaphragm that hinder ion flow;

[0129] Activation polarity voltage U actThe existence of is due to the energy required for charge transfer between the electrolyte and the electrode to overcome; in the activation phenomenon, when the redox reaction rate changes, the electrolyte interface undergoes load transfer, making it behave as a dielectric medium, which leads to overcharge on the electrode surface; to compensate for this overcharge, ions of opposite polarity need to accumulate in the electrolyte; these two layers of opposite charges are called the double layer effect and are one of the main reasons for the dynamic response of the electrolyzer;

[0130] The activation polarity voltage U act It is expressed as:

[0131]

[0132] Among them, δ is the transfer coefficient, j is the current density, and j0 is the electrode exchange current density;

[0133] According to the Tafel equation, the activation polarity voltage U act is a nonlinear function of the activation current and is expressed as:

[0134]

[0135] Among them, s1, s2, s3, t1, t2, t3 are Tafel empirical coefficients, A el is the electrode area;

[0136] Power P of a single electrolyzer unit el It is expressed as:

[0137] P el =U el I el (8)

[0138] Therefore, the voltage U tol and the power P of the electrolyzer stack tol It is described by formula (9) and formula (10):

[0139] U tol =NU el (9)

[0140] P tol =NP el (10)

[0141] Wherein, N is the number of electrolytic cell units constituting the electrolytic cell stack;

[0142] Theoretical partial pressure of electrolyte U th It is expressed as:

[0143]

[0144] Among them, U th(25°C, 1atm) is the thermal neutral voltage of the electrolyzer unit at 25°C and 1 standard atmosphere;

[0145] The efficiency of an alkaline electrolyzer usually refers to the voltage efficiency of the alkaline electrolyzer, which is defined as the theoretical partial pressure of the electrolyte U th The actual partial pressure of the electrolyte U el The ratio of v , due to the theoretical partial pressure of electrolyte U th It is difficult to determine. Usually we use the thermal neutral voltage for calculation. The calculation formula is as follows:

[0146]

[0147] In this embodiment, U th is the thermal neutral voltage, U th (25℃, 1atm) takes the value as 1.481V;

[0148] According to Faraday's law, the Faraday efficiency η F The specific formula is:

[0149]

[0150] Among them, f1 and f2 are parameters related to Faraday efficiency, and the unit is mA 2 / cm 4 ;

[0151] The hydrogen production efficiency of alkaline electrolyzer is η el It is expressed as:

[0152] η el =η F η v (14)

[0153] For an electric hydrogen production device containing n alkaline electrolyzers, the molar flow rate of hydrogen production is It is expressed as:

[0154]

[0155] in, is the power of the i-th electrolytic cell;

[0156] In practical applications, the volume flow rate of hydrogen is often used to quantitatively measure the hydrogen demand on the user side. (Unit: Nm 3 ·h -1 )The specific formula is:

[0157]

[0158] in, is the molar flow rate of hydrogen;

[0159] Determined according to the following formula:

[0160]

[0161] According to the above modeling analysis, the control variables of the electric hydrogen production equipment are mainly the electrolyzer unit current I el , electrolytic cell unit voltage U el , electrolyzer unit power The number of electrolyzer units N in the electrolyzer stack; the state variables of the electric hydrogen production equipment mainly include the hydrogen volume flow rate The working temperature of the electrolyzer unit is T el , Hydrogen gas pressure in electrolyzer Electrolyzer hydrogen production efficiency η el ;

[0162] Matrices of control variables and state variables of electric hydrogen production equipment E2H It is expressed as:

[0163]

[0164] According to the power consumption characteristics of the user-side hydrogen production load, the energy flow equation of the hydrogen production system and the external characteristics of the hydrogen production power on the user side obtained in step 1, the Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production operation and the voltage of each node in the distribution network is calculated jointly, and the correlation analysis results of the control variables and state variables of the hydrogen production equipment operation and the voltage of each node in the distribution network are preliminarily obtained. The calculation formula is as follows:

[0165]

[0166] Among them, ρ is the node The Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production equipment in the distribution network with each node and the voltage of each node in the distribution network, For node i node The original values ​​of each control variable and each state variable of the hydrogen production equipment. is the average value of each control variable and each state variable of the electric hydrogen production equipment, For node i node Voltage, is the average voltage of each node in the distribution network;

[0167] The Grey Relation Analysis (GRA) method is used to analyze the voltage of each node in the distribution network. The main sequence, each distributed hydrogen production control variable and state variable As a subsequence, after normalization, the grey correlation degree ζ(i node ), forming an associated sequence, the calculation formula is as follows:

[0168]

[0169] Among them, i node is the number of nodes in the power distribution network, k is the ordinal number of the control variables and state variables of the hydrogen production equipment, x0(i node ) is the distribution network node i node Voltage at x k (i node ) is the distribution network node i node The control variables and state variables of the kth electric hydrogen production equipment;

[0170] Based on this, the correlation coefficient matrix Matrices of the voltages of each node in the distribution network and the control variables and state variables of each distributed hydrogen production are established. Gra It is expressed as:

[0171] Matric Gra =[ζ k (i node )] (twenty one)

[0172] So we can get the description of the influence of the state variables and control variables of hydrogen production at the user side on the voltage change ΔU at the end of the distribution network. Net The equivalent mathematical model is shown in the following formula:

[0173]

[0174] Step 3: Using the existing on-load tap-changing transformer, static var compensator (SVC), static var generator (SVG) and automatic voltage regulation (AVR) grid-side voltage regulation equipment, according to the variation law of the terminal voltage after large-scale access of distributed hydrogen production and the voltage regulation characteristics of the grid-side voltage regulation equipment, with the minimum distribution network loss as the goal, based on the generalized Benders decomposition method, establish a voltage optimization regulation model for the user-side hydrogen production distribution network, and obtain regulation strategies for various grid-side voltage regulation equipment;

[0175] In this embodiment, the electric energy in the power grid is transmitted to the user through the AC bus, and the electric hydrogen production equipment obtains electric energy from the AC bus through the power electronic conversion structure, such as Figure 4 As shown;

[0176] The distribution network loss Loss(I jf ,R net ) is calculated using the root mean square method, as shown in the following formula:

[0177]

[0178] Among them, R net is the resistance value of the distribution network, I jf is the root mean square current of the distribution network, as shown in the following formula:

[0179]

[0180] Among them, P t , Q t are the three-phase active power and three-phase reactive power of the distribution network, U t is the simultaneous line voltage of the distribution network;

[0181] The process of establishing the voltage optimization control model of the distribution network containing user-side hydrogen production based on the generalized Benders decomposition method is as follows: the minimum distribution network loss is defined as the main problem, and the grid-side voltage regulation equipment constraints and hydrogen production equipment constraints are used as solutions. The problem is described as follows:

[0182]

[0183] Among them, g device (I jf ,t) is the set of grid-side voltage regulation equipment constraints, g E2H (I jf ,t) is the set of constraints for the electric hydrogen production equipment;

[0184] The above constraints on the hydrogen production equipment are E2H (I jf ,t) is:

[0185]

[0186] Among them, α i (t) is the start-up action of the electric hydrogen production equipment, β i (t) is the shutdown action of the electric hydrogen production equipment, μ i (t) is the start and stop state of the electric hydrogen production equipment, T is the total adjustment time, α max With β max are the maximum number of startups and shutdowns of the hydrogen production equipment in one day, P i (t) is the power of the electric hydrogen production equipment, P max and P min are the maximum power and minimum power of the electric hydrogen production equipment, ΔP control I is the maximum adjustment power allowed by the hydrogen production equipment per unit time.min The minimum operating current of the hydrogen production equipment, I max The maximum operating current of the electric hydrogen production equipment;

[0187] The constraints of the on-load tap-changing transformer installation are:

[0188]

[0189] Among them, Tap(t) is the tap number of the on-load tap-changing transformer, min and Tap max The tap position of the on-load tap-changing transformer is the minimum position and the tap position of the on-load tap-changing transformer is the maximum position, ΔTap allow The maximum number of gears that the on-load voltage-changing transformer can adjust within a unit time;

[0190] The static VAR compensation device constraints are:

[0191]

[0192] in, is the number of static VAR compensation devices put into the power grid, λ max is the maximum number of static VAR compensation devices that can be put into operation, Δλ control The maximum change in the number of static VAR compensation devices put into use per unit time;

[0193] Step 4: In view of the voltage mutation problem of the distribution network caused by the failure of the hydrogen production equipment and the extreme load mutation, a robust state estimation method of the distribution network containing the user-side hydrogen production state information is established, and the robust operation strategy of the grid-side voltage control device is determined based on the robust optimization method with Wasserstein metric;

[0194] The failure of the hydrogen production equipment is different from equipment failure. Equipment failure refers to the complete collapse of the hydrogen production equipment, which is the complete interruption of the required functions of the hydrogen production equipment under specific operating conditions. The failure of the hydrogen production equipment mentioned here refers to the malfunction of the hydrogen production equipment, which can be regarded as a brief interruption of the required functions of the hydrogen production equipment or a reduction in system performance under specific operating conditions, which may be caused by sensor equipment failure, actuator equipment failure, etc. The mathematical model expression of the fault condition of the hydrogen production equipment is regarded as a deviation of the control variables or state variables of one or more hydrogen production equipment, such as: sensor equipment failure causes the hydrogen production equipment to deviate from the working temperature measurement of the electrolyzer unit. At this time, the working temperature T of the electrolyzer unit el It can be expressed as T el ±ΔT el The failure of the electric hydrogen production current regulator causes a deviation in the input DC power supply of the electric hydrogen production equipment. At this time, the working current of the electrolyzer unit can be expressed as Iel ±ΔI el From the perspective of the power grid, the working condition of the hydrogen production equipment is abstractly integrated by the working power of the equipment. When the load mutation occurs in extreme working conditions, the power of the hydrogen production equipment is expressed as P tol ±ΔP tol ;

[0195] The worst-case scenario of the failure and load mutation extreme conditions of the hydrogen production equipment is characterized by the distributed robust method, and then the Wasserstein divergence is used as the fuzzy set M of the uncertainty measurement of the distributed robust method. ε , thereby establishing an "uncertainty model" to verify the regulation performance of the electric hydrogen production equipment under extreme conditions of faults and load mutations; the fuzzy set M ε The specific formula is:

[0196]

[0197] in, is the probability distribution of the actual working power of the electric hydrogen production equipment, is the empirical distribution of the operating power of the electric hydrogen production equipment, M(ξ) is all the definitions in the Wasserstein divergence d w The probability distribution space under , ε is the fuzzy set radius;

[0198] According to the "uncertainty model", the original "voltage optimization control model of the distribution network including user-side hydrogen production" is improved, and the specific formula of the new "optimization control model" is obtained as follows:

[0199]

[0200] Among them, E P It means that the Wasserstein divergence d is defined w Moments of uncertainty measures under ;

[0201] Step 5: Based on step 4, the electric hydrogen production equipment is taken as the control object, and the coupling control method of the voltage regulation on the distribution network side and the electric hydrogen production equipment on the user side is determined. Then the control cost of the electric hydrogen production equipment is modeled. Finally, the goal of "minimizing the control cost of the electric hydrogen production equipment" is introduced on the basis of the minimum distribution network loss to obtain the final coupling control method, such as Figure 5 As shown, voltage regulation is realized for the distributed access scenario of hydrogen production by electricity at the user side;

[0202] The internal state variables and control variables of the hydrogen production equipment are mapped to the external characteristics of the hydrogen production equipment, and the state equation of the grid-side voltage regulation system of the hydrogen production equipment is combined. The voltage regulation coupling equation of the load-side hydrogen production device and the grid-side voltage regulation device is obtained by combining eigenvalue analysis and relative gain matrix theory.

[0203] According to the coupling equation of voltage regulation of load-side electric hydrogen production device and voltage regulation of grid-side voltage regulation device, on the basis of the minimum target of distribution network line loss, the minimum target of "minimum control cost of electric hydrogen production equipment" is introduced, and a dual-target voltage optimization control model is established. The power flow model is linearized based on the second-order cone optimization method, and a multi-objective optimization problem solving algorithm based on mixed integer NSGA-III is proposed, and the distribution network voltage optimization control method under the coupling of the two voltage regulation modes is obtained.

[0204] The control cost of hydrogen production equipment includes two aspects: one is the cost of controlling the hydrogen production amount according to the hydrogen demand on the user side; the other is the additional control cost caused by the voltage drop on the user side, which leads to a reduction in hydrogen production or the power adjustment of the hydrogen production equipment to meet the voltage regulation demand on the grid side when the voltage drop occurs at the end of the distribution network on the grid side;

[0205] In this embodiment, taking an alkaline electrolytic cell as an example, the following assumptions are made:

[0206] S1: Set the capacity of the user-side hydrogen production equipment to V device Standard side, user hydrogen demand is V subscribers The standard is that the hydrogen production equipment consists of N electrolyzer units with a rated power of P N kilowatt;

[0207] S2: The hydrogen production capacity of the electric hydrogen production equipment can always meet the needs of users. The electric hydrogen production equipment always works in the adjustable area. When the user's hydrogen demand changes, all electrolyzer units jointly undertake the adjustment task;

[0208] S3: The electric hydrogen production equipment has sufficient adjustment capability to ensure that each electrolyzer unit maintains constant temperature and pressure during operation;

[0209] S4: Raw water consumption per standard cubic meter of hydrogen ct material Tons, cooling water ct cooldown Tons, water fee water Yuan / ton;

[0210] S5: The industrial electricity price is fee electric Yuan / kWh;

[0211] S6: The cost of each adjustment of the electric hydrogen production equipment is fee control Yuan

[0212] S7: Every time the hydrogen production adjustment reaches 5% of the equipment capacity, it is regarded as one adjustment;

[0213] S8: When the hydrogen production equipment performs power regulation to meet the voltage regulation demand on the grid side, every 2% of the rated power is regarded as one regulation;

[0214] S9: Labor cost and maintenance cost are ct maintain Yuan.

[0215] S10: Faradaic efficiency and voltage efficiency are calculated using the following empirical formula:

[0216]

[0217] Therefore, the hydrogen flow rate of the electric hydrogen production equipment It is expressed as:

[0218]

[0219] Hydrogen production capacity of electric hydrogen production equipment in time period T It is expressed as:

[0220]

[0221] satisfy:

[0222]

[0223] Among them, V subscribers The hydrogen production demand determined for the user side;

[0224] The water consumption cost ct water It is expressed as:

[0225]

[0226] Electricity consumption cost electric It is expressed as:

[0227]

[0228] Adjustment costct control.sub1 It is expressed as:

[0229]

[0230] In summary, the cost ct1 of controlling hydrogen production on the user side is:

[0231] ct1=ct water +ct electric +ct control.sub +ct maintain (39)

[0232] For the voltage drop at the end of the distribution network, the cost of power regulation ct control.sub2 for:

[0233]

[0234] The load control cost of hydrogen production by electricity is expressed as:

[0235] cost=ct control.sub2 +ct1 (41)

[0236] From the above analysis, it can be seen that the load control cost of hydrogen production is a function of the equipment working current, working voltage, and power. E2H The control variables and state variables of the hydrogen production equipment have been mapped to the distribution network parameters. Here, the load control cost is approximated as a function of the distribution network parameters, which is expressed as: cost(I jf ,R net ), and then the user's hydrogen production is used as a multi-objective solution constraint. The solution model of the multi-objective optimization model is expressed as:

[0237]

[0238] Among them, V subscribers The hydrogen production demand determined by the user side, is the amount of hydrogen produced by the electric hydrogen production equipment in the T period;

[0239] Finally, taking the different numerical ranges of voltage drop at the end of the distribution network as the basis for the execution strategy, a voltage control method for the distributed access scenario of hydrogen production by electricity on the user side is obtained.

[0240] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A voltage control method for a distributed access scenario of hydrogen production from electricity at the user side, characterized by: The following steps are involved: Step 1: Obtain user-side hydrogen production related data sets for low voltage or overvoltage at the end of the distribution network caused by large-scale access of user-side hydrogen production; Then, the power consumption characteristics of each user-side hydrogen production load, the energy flow equation of the hydrogen production system and the external power characteristics of the hydrogen production on the user side are obtained; Step 2: Calculate the Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production operation and the voltage of each node in the distribution network based on the user-side hydrogen production related data set obtained in step 1, obtain the correlation analysis results of the control variables and state variables of the hydrogen production equipment operation and the voltage of each node in the distribution network, and establish the hydrogen production equipment model based on the analysis results; Step 3: Using the existing grid-side voltage regulation equipment, according to the variation law of the terminal voltage after large-scale access of distributed hydrogen production and the voltage regulation characteristics of the grid-side voltage regulation equipment, with the minimum distribution network loss as the goal, based on the generalized Benders decomposition method, establish a voltage optimization regulation model for the user-side hydrogen production distribution network, and obtain regulation strategies for various grid-side voltage regulation equipment; Step 4: In view of the voltage mutation problem of the distribution network caused by the failure of the hydrogen production equipment and the extreme load mutation, a robust state estimation method of the distribution network containing the user-side hydrogen production state information is established, and the robust operation strategy of the grid-side voltage control device is determined based on the robust optimization method with Wasserstein metric; Step 5: Based on step 4, take the hydrogen production equipment as the control object, determine the coupling control method between the voltage regulation on the distribution network side and the hydrogen production equipment on the user side, then model the control cost of the hydrogen production equipment, and finally introduce the goal of "minimizing the control cost of hydrogen production equipment" on the basis of minimum distribution network loss to obtain the final coupling control method, so as to realize voltage control for the distributed access scenario of hydrogen production on the user side.

2. According to claim 1, a voltage control method for a distributed access scenario of hydrogen production from electricity at the user side is characterized by: The obtained user-side hydrogen production related data set includes a user-side hydrogen production load data set, a hydrogen production system status data set and a hydrogen production system energy flow data set.

3. A voltage control method for user-side hydrogen production distributed access scenario according to claim 2, characterized in that: The specific method of step 1 is: Obtaining the power consumption characteristics of each user-side hydrogen production load according to the user-side hydrogen production load data set; the user-side hydrogen production load power consumption characteristics represent the relationship between the user-side hydrogen production load current and the distribution network voltage; The energy flow equation of the hydrogen production system is obtained according to the state data set of the hydrogen production system; the energy flow equation of the hydrogen production system is used to describe the relationship between the control variables and state variables of the hydrogen production operation on the user side and the hydrogen production load current on the user side; The state variables include temperature, pressure, voltage and current density; The external characteristics of the hydrogen production power on the user side are obtained according to the energy flow data set of the hydrogen production system; the external characteristics of the hydrogen production power on the user side represent the relationship between the hydrogen production power on the user side and the hydrogen production load current on the user side.

4. A voltage control method for user-side hydrogen production distributed access scenario according to claim 3, characterized in that: The specific method of step 2 is: Modeling of the electric hydrogen production plant around an alkaline electrolyzer; the total voltage across the alkaline electrolyzer is U el By the reversible voltage U oc , Activation polarity voltage U act and ohmic polarity voltage U ohm The total voltage across the alkaline electrolytic cell is expressed as: IN el =U oc +U act +U ohm (1) Reversible voltage U oc The following formula expresses it: U oc =v0-v1(T0+T el )+v2(T0+T el )ln(T0+T el )+v3(T0+T el ) 2 (2) Among them, v0, v1, v2, v3 are the temperature empirical coefficients of the electric hydrogen production equipment, T0 is the absolute temperature inside the alkaline electrolyzer, T el is the operating temperature of the electrolyzer unit; The ohmic polarity voltage U ohm It is expressed as: Among them, I el is the instantaneous current flowing through the electrolytic cell unit, A is the surface area of ​​the alkaline electrolytic cell, r1, r2, r3, and r4 are the resistance coefficients of the electrolytic cell unit respectively; According to the Tafel equation, the activation polarity voltage U act is a nonlinear function of the activation current and is expressed as: Among them, I el is the instantaneous current flowing through the electrolytic cell unit, s1, s2, s3, t1, t2, t3 are Tafel empirical coefficients, A el is the electrode area; Power P of a single electrolyzer unit el It is expressed as: P el =U el AND el (5) Therefore, the voltage U tol and the power P of the electrolyzer stack tol It is described by formula (9) and formula (10): YOU tol =NOW el (6) P tol =NP el (7) Wherein, N is the number of electrolytic cell units constituting the electrolytic cell stack; Theoretical partial pressure of electrolyte U th It is expressed as: Among them, U th (25°C, 1atm) is the thermoneutral voltage of the electrolyzer unit at 25°C and 1 standard atmosphere, ΔS is the change in internal entropy in the hydrogen production reaction, and z is the number of electrons required to transfer to produce 1 mole of hydrogen; The efficiency of an alkaline electrolyzer refers to the voltage efficiency of the alkaline electrolyzer, which is defined as the theoretical partial pressure of the electrolyte U th The actual partial pressure of the electrolyte U el The ratio of v The calculation formula is as follows: According to Faraday's law, the Faraday efficiency η F The specific formula is: Among them, f1 and f2 are parameters related to Faraday efficiency, and the unit is mA 2 / cm 4 ; The hydrogen production efficiency of alkaline electrolyzer is η el It is expressed as: or el =the F or v (11) For an electric hydrogen production device containing n alkaline electrolyzers, the molar flow rate of hydrogen production is It is expressed as: in, is the power of the i-th electrolytic cell; Hydrogen production volume flow The specific formula is: in, is the molar flow rate of hydrogen; Determined according to the following formula: Matrices of control variables and state variables of electric hydrogen production equipment E2H It is expressed as: According to the power consumption characteristics of the user-side hydrogen production load, the energy flow equation of the hydrogen production system and the external power characteristics of the hydrogen production on the user side obtained in step 1, the Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production operation and the voltage of each node in the distribution network is calculated jointly, and the correlation analysis results of the control variables and state variables of the hydrogen production equipment operation and the voltage of each node in the distribution network are preliminarily obtained. The calculation formula is as follows: Among them, ρ is the node The Spearman rank correlation coefficient between the control variables and state variables of the hydrogen production equipment in the distribution network with each node and the voltage of each node in the distribution network, For node i node is the original value of each control variable and each state variable of the electric hydrogen production equipment, x is the average value of each control variable and each state variable of the electric hydrogen production equipment, For node i node The voltage at the node, y is the average voltage of each node in the distribution network; The voltage of each node in the distribution network is analyzed by using the grey correlation analysis method. The main sequence, each distributed hydrogen production control variable and state variable As a subsequence, after normalization, the grey correlation degree ζ(i node ), forming an associated sequence, the calculation formula is as follows: Among them, i node is the number of nodes in the power distribution network, k is the ordinal number of the control variables and state variables of the hydrogen production equipment, x0(i node ) is the distribution network node i node Voltage at x k (i node ) is the distribution network node i node The control variables and state variables of the kth electric hydrogen production equipment; Based on this, the correlation coefficient matrix Matrices of the voltages of each node in the distribution network and the control variables and state variables of each distributed hydrogen production are established. Gra It is expressed as: Matric Gra =[ζ k (i node )] (18) So we can get the description of the influence of the state variables and control variables of hydrogen production at the user side on the voltage change ΔU at the end of the distribution network. Net The equivalent mathematical model is shown in the following formula:

5. A voltage control method for user-side hydrogen production distributed access scenario according to claim 4, characterized in that: The distribution network loss Loss(I jf ,R net ) is calculated using the root mean square method, as shown in the following formula: Among them, R net is the resistance value of the distribution network, I jf is the root mean square current of the distribution network, as shown in the following formula: Among them, P t , Q t are the three-phase active power and three-phase reactive power of the distribution network, U t is the simultaneous line voltage of the distribution network.

6. A voltage control method for user-side hydrogen production distributed access scenario according to claim 5, characterized in that: The process of establishing the voltage optimization control model of the distribution network containing user-side hydrogen production based on the generalized Benders decomposition method in step 3 is as follows: the minimum distribution network loss is defined as the main problem, and the grid-side voltage regulation equipment constraints and hydrogen production equipment constraints are taken as the solution. The problem is described as follows: Among them, g device (I jf ,t) is the set of grid-side voltage regulation equipment constraints, g E2H (I jf ,t) is the set of constraints for the electric hydrogen production equipment; The above constraints on the hydrogen production equipment are E2H (I jf ,t) is: Among them, α i (t) is the start-up action of the electric hydrogen production equipment, β i (t) is the shutdown action of the electric hydrogen production equipment, μ i (t) is the start and stop state of the electric hydrogen production equipment, T is the total adjustment time, α max With β max are the maximum start-up times and maximum shutdown times of the hydrogen production equipment in one day, P i (t) is the power of the electric hydrogen production equipment, P max and P min are the maximum power and minimum power of the electric hydrogen production equipment, ΔP control I is the maximum adjustment power allowed by the hydrogen production equipment per unit time. min is the minimum operating current of the electric hydrogen production equipment, I max The maximum operating current of the electric hydrogen production equipment; The constraints of the on-load tap-changing transformer installation are: Among them, Tap(t) is the tap number of the on-load tap-changing transformer, min and Tap max The tap position of the on-load tap-changing transformer is the minimum position and the tap position of the on-load tap-changing transformer is the maximum position, ΔTap allow The maximum number of gears that the on-load voltage-changing transformer can adjust within a unit time; The static VAR compensation device constraints are: in, is the number of static VAR compensation devices put into the power grid, λ max is the maximum number of static VAR compensation devices that can be put into operation, Δλ control It is the maximum change in the number of static VAR compensation devices put into operation per unit time.

7. A voltage control method for user-side hydrogen production distributed access scenario according to claim 6, characterized in that: The specific method of step 4 is: The worst-case scenario of the failure and load mutation extreme conditions of the hydrogen production equipment is characterized by the distributed robust method, and then the Wasserstein divergence is used as the fuzzy set M of the uncertainty measurement of the distributed robust method. ε , thereby establishing an "uncertainty model" to verify the regulation performance of the electric hydrogen production equipment under extreme conditions of faults and load mutations; the fuzzy set M ε The specific formula is: in, is the probability distribution of the actual working power of the electric hydrogen production equipment, is the empirical distribution of the operating power of the electric hydrogen production equipment, M(ξ) is all the definitions in the Wasserstein divergence d w The probability distribution space under , ε is the fuzzy set radius; According to the "uncertainty model", the original "voltage optimization control model of the distribution network including user-side electric hydrogen production" is improved, and the specific formula of the new "optimization control model" is obtained as follows: Among them, E P It means that the Wasserstein divergence d is defined w Moments of uncertainty measures under .

8. A voltage control method for user-side hydrogen production distributed access scenario according to claim 7, characterized in that: The specific method of step 5 is: The internal state variables and control variables of the hydrogen production equipment are mapped to the external characteristics of the hydrogen production equipment, and the state equation of the grid-side voltage regulation system of the hydrogen production equipment is combined. The voltage regulation coupling equation of the load-side hydrogen production device and the grid-side voltage regulation device is obtained by combining eigenvalue analysis and relative gain matrix theory. According to the coupling equation of voltage regulation of load-side electric hydrogen production device and voltage regulation of grid-side voltage regulation device, on the basis of the minimum target of distribution network line loss, the minimum target of "minimum control cost of electric hydrogen production equipment" is introduced, and a dual-target voltage optimization control model is established. The power flow model is linearized based on the second-order cone optimization method, and a multi-objective optimization problem solving algorithm based on mixed integer NSGA-III is proposed, and the distribution network voltage optimization control method under the coupling of the two voltage regulation modes is obtained. The control cost of hydrogen production equipment includes two aspects: one is the cost of controlling the hydrogen production amount according to the hydrogen demand on the user side; the other is the additional control cost caused by the voltage drop on the user side, which leads to a reduction in hydrogen production or the power adjustment of the hydrogen production equipment to meet the voltage regulation demand on the grid side when the voltage drop occurs at the end of the distribution network on the grid side; The load control cost of hydrogen production is a function of the equipment's operating current, operating voltage, and power. The matrix constructed above is E2H The control variables and state variables of the hydrogen production equipment have been mapped to the distribution network parameters. Here, the load control cost is approximated as a function of the distribution network parameters, which is expressed as: cost(I jf ,R net ), and then the user's hydrogen production is used as a multi-objective solution constraint. The solution model of the multi-objective optimization model is expressed as: Among them, V subscribers The hydrogen production demand determined by the user side, is the amount of hydrogen produced by the electric hydrogen production equipment in the T period; Finally, taking the different numerical ranges of voltage drop at the end of the distribution network as the basis for the execution strategy, a voltage control method for the distributed access scenario of hydrogen production by electricity on the user side is obtained.

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