Light-hydrogen-storage micro-grid dispatching method considering dynamic safety constraint of electrolytic cell

Abstract

The invention relates to a light-hydrogen-storage micro-grid dispatching method considering dynamic safety constraints of an electrolytic cell, and belongs to the technical field of micro-grid dispatching. A light-hydrogen-storage micro-grid scheduling method considering dynamic safety constraints of an electrolytic cell comprises the following steps: performing a dynamic operation experiment on an AEL electrolytic cell and a PEM electrolytic cell in a micro-grid to obtain hydrogen and oxygen impurity response characteristics and obtain a hydrogen and oxygen impurity proportion dynamic model of the electrolytic cells; and constructing a scheduling model according to the operating characteristics of the micro-grid. The safety problem caused by over-standard hydrogen and oxygen impurities due to over-low power lower limit of the electrolytic cell and the problem that the response capability of the electrolytic cell cannot be fully utilized when the power lower limit of the electrolytic cell is over-high are avoided; the power lower limit of the AEL electrolytic cell and the PEM electrolytic cell is prevented from being continuously debugged; the hydrogen and oxygen impurity proportion of the system can be limited according to different levels of safety requirements, and the control degree of the system safety is higher.

Description

Technical Field

[0001] The invention relates to a power grid dispatching method and belongs to the technical field of microgrid dispatching. Background Art

[0002] Electricity-generated hydrogen technology is one of the effective ways to promote carbon emission reduction in industries such as electricity, transportation, and chemicals. In order to avoid carbon emissions in the process of electricity-generated hydrogen, the electrolyzer that produces hydrogen needs to be directly coupled with renewable energy generators that are volatile, random, and intermittent. Unlike the traditional constant power operation mode, when the electrolyzer is directly coupled with the renewable energy generator through a microgrid, the microgrid needs to formulate an operation strategy for the microgrid based on the output of renewable energy to improve the utilization rate of renewable energy, reduce the impact of renewable energy volatility on the upper power grid and electrolyzer, and maximize economic benefits.

[0003] Since the electrolyzer diaphragm cannot completely isolate the gas produced by the anode and cathode, the gas produced by the electrolyzer contains impurities. When the gas impurity ratio reaches the explosion limit, the system will explode, especially the impurity ratio of the gas-liquid separator on the anode side. The gas impurity ratio increases as the electrolyzer power decreases. Therefore, in order to ensure the safety of the electrolyzer, it is necessary to limit the lower limit of the electrolyzer's operating power when scheduling the microgrid.

[0004] Prior art literature:

[0005] Kong Lingguo's team from Northeast Electric Power University focuses on the distribution and centralized interactive optimization scheduling of the park's electricity-hydrogen-heat low-carbon energy system. With the goal of minimizing operating costs, they solve the interactive energy meters between buildings and the optimal output of each centralized energy equipment in the park, thus achieving precise and optimal point-to-point energy interaction among multiple energy entities.

[0006] Yuan Tiejiang's team from Dalian University of Technology took into account real-time changes in electricity prices, the operating status of multiple electrolyzers, and the intermittent nature of new energy sources, and established a day-ahead output scheduling model to achieve safe and stable operation of the system, avoid large-scale purchases of electricity at peak electricity prices and repeated start and stop of alkaline electrolyzers, and reduce system operating costs.

[0007] Yang Ping's team at South China University of Technology determined the upper and lower limits of the electrolyzer's power through the annual grid sales rate and the levelized electricity price, and proposed a capacity optimization method for wind-solar-hydrogen-storage microgrids to reduce wind and solar power curtailment.

[0008] The level of existing technology and existing problems (defects):

[0009] 1. At present, in the microgrid dispatching containing electrolyzers, the power lower limit of the electrolyzer is usually a given constant value. When the given constant power lower limit is too large, the response capacity of the electrolyzer cannot be fully utilized, and the system benefit is low. When the given constant power lower limit is too small, the system safety cannot be guaranteed.

[0010] 2. A microgrid may contain both proton exchange membrane (PEM) and alkaline electrolysis (AEL) electrolyzers. They have different ratios of hydrogen and oxygen impurities at the same power, so the given constant power lower limit is also different. It is very difficult to select an appropriate constant power lower limit to ensure the safe operation of PEM and AEL electrolyzers while fully utilizing the response capability of the electrolyzers.

[0011] Therefore, it is urgent to propose a solar-hydrogen-storage microgrid scheduling method that considers the dynamic safety constraints of the electrolyzer to solve the above technical problems. Summary of the invention

[0012] In order to solve the above technical problems, a light-hydrogen-storage microgrid scheduling method considering the dynamic safety constraints of the electrolyzer is provided. A brief overview of the present invention is given below to provide a basic understanding of certain aspects of the present invention. It should be understood that this overview is not an exhaustive overview of the present invention. It is not intended to determine the key or important parts of the present invention, nor is it intended to limit the scope of the present invention.

[0013] The technical solution of the present invention:

[0014] A method for scheduling a photovoltaic-hydrogen-storage microgrid considering dynamic safety constraints of an electrolyzer, comprising the following steps:

[0015] Step 1: Conduct dynamic operation experiments on the AEL electrolyzer and PEM electrolyzer in the microgrid to obtain the hydrogen and oxygen impurity response characteristics and obtain a dynamic model of the hydrogen and oxygen impurity ratio of the electrolyzer;

[0016] Step 2: Construct a dispatch model based on the operating characteristics of the microgrid.

[0017] Preferably: step one comprises the following steps:

[0018] Step 1.1: Based on the voltage-current curve, the power-current curve of the electrolytic cell is obtained; the gas impurity model and the power-current curve are combined, and the electrolysis current is eliminated to obtain the relationship between the gas impurity ratio and the power of the electrolytic cell;

[0019] Step 1.2: According to the step size of the scheduling problem, the dynamic security constraint model suitable for microgrid scheduling is obtained.

[0020] Preferably: in step 1.1, the dynamic model of hydrogen-oxygen impurity ratio of the AEL electrolyzer can be expressed as:

[0021]

[0022] Among them, HTO AEL(t) and are the proportion and molar number of impurities in the gas-liquid separator on the anode side of the AEL electrolyzer at time t; p AEL , and T AEL are the pressure, volume and temperature of the gas in the gas-liquid separator on the anode side of the AEL electrolyzer; R is the ideal gas constant. The number of moles of gas impurities in the gas-liquid separator on the anode side is related to the gas impurities in the half-cell on the anode side of the electrolyzer:

[0023]

[0024] in, and are the molar flow rates of impurities caused by concentration diffusion, pressure difference permeation and alkali solution circulation in the anode half-cell of the AEL electrolyzer; is the molar flow rate of gas impurities flowing out of the gas-liquid separator on the anode side of the AEL electrolyzer, which is related to the electrolysis current of the AEL electrolyzer:

[0025]

[0026] Among them, I AEL is the electrolysis current of the AEL electrolytic cell; F is the Faraday constant;

[0027] Based on (1)-(3), the relationship between the impurity ratio in the gas-liquid separator on the anode side of the AEL electrolyzer and the electrolysis current can be obtained; the power of the AEL electrolyzer is the product of the electrolysis current and the voltage:

[0028] P AEL (t) = U AEL (t)I AEL (t) (4)

[0029] Among them, P AEL and U AEL Respectively represent the power and voltage of the AEL electrolyzer; the relationship between voltage and current is determined by the polarization curve:

[0030]

[0031] in, is the reversible voltage of the AEL electrolyzer; r 1,AEL 、r 2,AEL 、s AEL ,t 1,AEL ,t 2,AEL and t 3,AELis an empirical coefficient, which can be obtained based on the dynamic operation experiment of the AEL electrolyzer; based on the voltage-current curve, the power-current curve of the AEL electrolyzer can be obtained; by combining the gas impurity model (1)-(3) and the power-current curve (4)-(5), eliminating the electrolysis current, the relationship between the gas impurity ratio and power of the AEL electrolyzer can be obtained:

[0032]

[0033] Among them, a AEL and b AEL is the constant of the AEL electrolyzer gas impurity response, which can be obtained from equations (1)-(5) and the dynamic operation experiment of the AEL electrolyzer;

[0034] The difference between the gas impurity response of the PEM electrolyzer and the AEL electrolyzer is that the gas impurities in the anode side half-cell of the PEM electrolyzer are composed of only two parts: gas impurities caused by pressure difference penetration and concentration difference diffusion, namely:

[0035]

[0036] in, It represents the number of moles of impurities in the gas-liquid separator on the anode side of the PEM electrolyzer; They represent the molar flow rates of impurities caused by concentration diffusion and pressure difference penetration in the anode half-cell of the PEM electrolyzer respectively; is the molar flow rate of gas impurities flowing out of the gas-liquid separator on the anode side of the PEM electrolyzer;

[0037] Modeling the PEM electrolyzer provides the relationship between its gas impurity ratio and power:

[0038]

[0039] Among them, HTO PEM is the gas impurity ratio of the PEM electrolyzer; P PEM is the power of the PEM electrolyzer; a PEM and b PEM The constant representing the gas impurity response of the PEM electrolyzer can be obtained from the dynamic operation experiment of the PEM electrolyzer.

[0040] Preferably: In step 1.2, the dynamic gas impurity models (6) and (8) of the AEL electrolyzer and the PEM electrolyzer are discretized to obtain a dynamic safety constraint model suitable for microgrid scheduling:

[0041]

[0042] Among them, Δt is the step size of the day-ahead scheduling; t endIndicates the number of time steps or dimensions of each variable for day-ahead scheduling, which is related to the scheduling step size:

[0043]

[0044] Preferably: Step 2 comprises the following steps:

[0045] Step 2.1: Microgrid operation characteristic model;

[0046] Step 2.2: Considering the operating characteristics of the microgrid, the optimal dispatching strategy is obtained by finding the maximum value of the objective function.

[0047] Preferably: In step 2.1, the source and load power of the microgrid should be balanced:

[0048] P fuel (t)+P PV (t) = P AEL (t)+P PEM (t)+P load (t)+P sto (t)+P grid (t) (12)

[0049] Among them, P fuel and P PV Represent the output power of fuel cell and photovoltaic respectively; P AEL and P PEM Respectively represent the power consumed by AEL electrolyzer and PEM electrolyzer for hydrogen production; P load Represents the power of the electrical load in the microgrid; P sto Indicates the power of electrochemical energy storage. A positive value indicates charging, while a negative value indicates discharging. grid Represents the amount of electricity exchanged between the microgrid and the power system. A positive power indicates that the microgrid sells electricity to the upper-level power grid, and a negative power indicates that the microgrid purchases electricity from the upper-level power grid. PV and P load is the known day-ahead forecast value, and P grid , P sto , P AEL , P PEM and P fuel is the optimization variable that needs to be solved by the scheduling model;

[0050] There is a direct coupling between the power and the flow of hydrogen in the microgrid; the electrolyzer is the only source of hydrogen in the microgrid, and the relationship between its hydrogen production and power can be expressed by a quadratic function:

[0051]

[0052] in, and are the molar flow rates of hydrogen produced by the AEL electrolyzer and the PEM electrolyzer, respectively; h AEL,1 、h AEL,2 、h AEL,3 、h PEM,1 、h PEM,2 and h PEM,3 is the hydrogen production coefficient of the electrolyzer;

[0053] The fuel cell consumes hydrogen to generate electricity and supplies power to the microgrid when power is insufficient. The power supply and hydrogen consumption can be expressed as:

[0054]

[0055] in, is the molar flow rate of hydrogen consumed by the fuel cell; η cell is the hydrogen-to-electricity conversion coefficient of the fuel cell;

[0056] There is a balance between the hydrogen produced by the electrolyzer in the microgrid, the hydrogen consumed by the fuel cell, and the hydrogen stored in the hydrogen tank:

[0057]

[0058] in, is the molar flow rate of hydrogen flowing into the hydrogen storage tank; since the amount of hydrogen in the hydrogen storage tank is always not less than 0, then:

[0059]

[0060] in, Indicates the amount of hydrogen stored in the hydrogen storage tank at the initial moment;

[0061] At the same time, the hydrogen produced by the microgrid needs to meet the given day-ahead hydrogen production demand:

[0062]

[0063] in, is the day-ahead hydrogen production demand of the microgrid, which is a known value.

[0064] Preferably: in step 2.2, in actual dispatching, the operating characteristics of the microgrid are taken into consideration, and the optimal dispatching strategy is obtained by finding the maximum value of the objective function, with economy as the goal; the economic objective function can be expressed as:

[0065]

[0066] Among them, w power and w H2 The prices for electricity and hydrogen sales;

[0067] In summary, the microgrid dispatch model considering the dynamic safety constraints of the electrolyzer can be expressed as:

[0068]

[0069] Beneficial effects of the present invention:

[0070] 1. The present invention avoids the safety problem caused by excessive hydrogen and oxygen impurities due to the low lower limit of the electrolytic cell power in the traditional scheduling method, and the problem that the response capacity of the electrolytic cell cannot be fully utilized when the lower limit of the electrolytic cell power is set too high;

[0071] 2. The present invention avoids the need to continuously adjust the power lower limit of the AEL electrolyzer and the PEM electrolyzer. The proposed scheduling method can automatically allocate power to electrolyzers with different hydrogen and oxygen impurity response characteristics through dynamic safety constraints, ensuring the safety of all electrolyzers while making full use of the power response capacity of the electrolyzers;

[0072] 3. The present invention can limit the ratio of hydrogen and oxygen impurities in the system according to different levels of safety requirements. Compared with traditional scheduling methods, the degree of control over system safety is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 It is a flow chart of a light-hydrogen-storage microgrid scheduling method considering dynamic safety constraints of electrolyzers according to the present invention;

[0074] Figure 2 It is the electricity load diagram of the solar-hydrogen-storage microgrid;

[0075] Figure 3 It is the photovoltaic output diagram of the light-hydrogen-storage microgrid;

[0076] Figure 4 This is a comparison chart of the electrolyzer power allocation results of the proposed method and the traditional method;

[0077] Figure 5 It is a comparison chart of hydrogen and oxygen impurity ratios in the electrolyzer of the proposed method and the traditional method;

[0078] Figure 6 This is the result diagram of electrolytic cell power distribution when the upper limit of hydrogen and oxygen impurity ratio is 1.8%;

[0079] Figure 7 This is the response diagram of the hydrogen and oxygen impurity ratio of the electrolytic cell when the upper limit of the hydrogen and oxygen impurity ratio is 1.8%. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is described below by the specific embodiments shown in the accompanying drawings. However, it should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0081] Specific implementation method 1: Combination Figure 1 This embodiment is described. A light-hydrogen-storage microgrid scheduling method considering dynamic safety constraints of electrolyzers in this embodiment includes the following steps:

[0082] Step 1: Conduct dynamic operation experiments on the AEL electrolyzer and PEM electrolyzer in the microgrid to obtain the hydrogen and oxygen impurity response characteristics and obtain a dynamic model of the hydrogen and oxygen impurity ratio of the electrolyzer;

[0083] Step one includes the following steps:

[0084] Step 1.1: Based on the voltage-current curve, the power-current curve of the electrolyzer is obtained; the electrolyzer current-hydrogen-oxygen impurity ratio model and the electrolyzer current-power curve are combined, and the electrolysis current is eliminated to obtain the electrolyzer power-hydrogen-oxygen impurity ratio model;

[0085] In step 1.1, the dynamic model of hydrogen and oxygen impurity ratio of AEL electrolyzer can be expressed as:

[0086]

[0087] Among them, HTO AEL (t) and are the proportion and molar number of impurities in the gas-liquid separator on the anode side of the AEL electrolyzer at time t; p AEL , and T AEL are the pressure, volume and temperature of the gas in the gas-liquid separator on the anode side of the AEL electrolyzer; R is the ideal gas constant. The number of moles of gas impurities in the gas-liquid separator on the anode side is related to the gas impurities in the half-cell on the anode side of the electrolyzer:

[0088]

[0089] in, and are the molar flow rates of impurities caused by concentration diffusion, pressure difference permeation and alkali solution circulation in the anode half-cell of the AEL electrolyzer; is the molar flow rate of gas impurities flowing out of the gas-liquid separator on the anode side of the AEL electrolyzer, which is related to the electrolysis current of the AEL electrolyzer:

[0090]

[0091] Among them, I AEL is the electrolysis current of the AEL electrolytic cell; F is the Faraday constant;

[0092] Based on (1)-(3), the relationship between the impurity ratio in the gas-liquid separator on the anode side of the AEL electrolyzer and the electrolysis current can be obtained; the power of the AEL electrolyzer is the product of the electrolysis current and the voltage:

[0093] P AEL (t) = U AEL (t)I AEL (t) (4)

[0094] Among them, P AEL and U AEL Respectively represent the power and voltage of the AEL electrolyzer; the relationship between voltage and current is determined by the polarization curve:

[0095]

[0096] in, is the reversible voltage of the AEL electrolyzer; r 1,AEL 、r 2,AEL 、s AEL ,t 1,AEL ,t 2,AEL and t 3,AEL is an empirical coefficient, which can be obtained based on the dynamic operation experiment of the AEL electrolyzer; based on the voltage-current curve, the power-current curve of the AEL electrolyzer can be obtained; by combining the gas impurity model (1)-(3) and the power-current curve (4)-(5), eliminating the electrolysis current, the relationship between the gas impurity ratio and power of the AEL electrolyzer can be obtained:

[0097]

[0098] Among them, a AEL and b AEL is the constant of the AEL electrolyzer gas impurity response, which can be obtained from equations (1)-(5) and the dynamic operation experiment of the AEL electrolyzer;

[0099] The gas impurity response of the PEM electrolyzer is similar to that of the AEL electrolyzer. The only difference is that the gas impurities in the anode half-cell of the PEM electrolyzer consist of only two parts: pressure difference permeation and concentration difference diffusion, namely:

[0100]

[0101] in, It represents the number of moles of impurities in the gas-liquid separator on the anode side of the PEM electrolyzer; They represent the molar flow rates of impurities caused by concentration diffusion and pressure difference penetration in the anode half-cell of the PEM electrolyzer respectively; is the molar flow rate of gas impurities flowing out of the gas-liquid separator on the anode side of the PEM electrolyzer;

[0102] The same modeling of the PEM electrolyzer can derive the relationship between its gas impurity ratio and power:

[0103]

[0104] Among them, HTO PEM is the gas impurity ratio of the PEM electrolyzer; P PEM is the power of the PEM electrolyzer; a PEM and b PEM The constants that also represent the gas impurity response of the PEM electrolyzer can be obtained from the dynamic operation experiment of the PEM electrolyzer;

[0105] Step 1.2: According to the step size discretization of the scheduling problem, the dynamic constraint model of electrolyzer safety suitable for microgrid scheduling is obtained;

[0106] In step 1.2, the dynamic gas impurity models (6) and (8) of the AEL electrolyzer and PEM electrolyzer are discretized to obtain a dynamic safety constraint model suitable for microgrid scheduling:

[0107]

[0108] Among them, Δt is the step size of the day-ahead scheduling; t end Indicates the number of time steps or dimensions of each variable for day-ahead scheduling, which is related to the scheduling step size:

[0109]

[0110] Step 2: After obtaining the dynamic safety constraint model of the AEL electrolyzer and the PEM electrolyzer, a dispatch model is constructed according to the operating characteristics of the microgrid;

[0111] Step 2 includes the following steps:

[0112] Step 2.1: Microgrid operation characteristic model;

[0113] In step 2.1, the source and load power of the microgrid should be balanced:

[0114] P fuel (t)+P PV (t) = P AEL (t)+P PEM (t)+P load (t)+P sto (t)+P grid (t) (12)

[0115] Among them, P fuel and P PV Represent the output power of fuel cell and photovoltaic respectively; P AEL and PPEM Respectively represent the power consumed by AEL electrolyzer and PEM electrolyzer for hydrogen production; P load Represents the power of the electrical load in the microgrid; P sto Indicates the power of electrochemical energy storage. A positive value indicates charging, while a negative value indicates discharging. grid Represents the amount of electricity exchanged between the microgrid and the power system. A positive power indicates that the microgrid sells electricity to the upper-level power grid, and a negative power indicates that the microgrid purchases electricity from the upper-level power grid. PV and P load is the known day-ahead forecast value, and P grid , P sto , P AEL , P PEM and P fuel is the optimization variable that needs to be solved by the scheduling model;

[0116] There is a direct coupling between the power and the flow of hydrogen in the microgrid; the electrolyzer is the only source of hydrogen in the microgrid, and the relationship between its hydrogen production and power can be expressed by a quadratic function:

[0117]

[0118] in, and are the molar flow rates of hydrogen produced by the AEL electrolyzer and the PEM electrolyzer, respectively; h AEL,1 、h AEL,2 、h AEL,3 、h PEM,1 、h PEM,2 and h PEM,3 is the hydrogen production coefficient of the electrolyzer;

[0119] The fuel cell consumes hydrogen to generate electricity and supplies power to the microgrid when power is insufficient. The power supply and hydrogen consumption can be expressed as:

[0120]

[0121] in, is the molar flow rate of hydrogen consumed by the fuel cell; η cell is the hydrogen-to-electricity conversion coefficient of the fuel cell;

[0122] There is a balance between the hydrogen produced by the electrolyzer in the microgrid, the hydrogen consumed by the fuel cell, and the hydrogen stored in the hydrogen tank:

[0123]

[0124] in, is the molar flow rate of hydrogen flowing into the hydrogen storage tank; since the amount of hydrogen in the hydrogen storage tank is always not less than 0, then:

[0125]

[0126] in, Indicates the amount of hydrogen stored in the hydrogen storage tank at the initial moment;

[0127] At the same time, the hydrogen produced by the microgrid needs to meet the given day-ahead hydrogen production demand:

[0128]

[0129] in, is the day-ahead hydrogen production demand of the microgrid, which is a known value;

[0130] Models (12)-(18) are based on the microgrid operation characteristics model;

[0131] Step 2.2: Considering the operating characteristics of the microgrid, the optimal dispatching strategy is obtained by finding the maximum value of the objective function;

[0132] In step 2.2, in actual dispatching, the operating characteristics of the microgrid are usually considered, and the optimal dispatching strategy is obtained by finding the maximum value of the objective function, generally with economy as the goal; the economic objective function can be expressed as:

[0133]

[0134] Among them, w power and w H2 The prices for electricity and hydrogen sales;

[0135] In summary, the microgrid dispatch model considering the dynamic safety constraints of the electrolyzer can be expressed as:

[0136]

[0137] The present invention mainly optimizes the scheduling of a microgrid containing an electrolyzer, takes into account the dynamic hydrogen and oxygen impurity response of the electrolyzer, ensures the safety of the electrolyzer, and fully utilizes the response capability of the electrolyzer.

[0138] Embodiment 1:

[0139] The proposed scheduling method is simulated by taking a photovoltaic-hydrogen-storage microgrid as an example, and compared with the traditional scheduling method with a given power lower limit. The system power load curve and photovoltaic output curve are shown in Figure 2. Figure 2 and Figure 3 As shown;

[0140] The power allocation results of the electrolyzer in the light-hydrogen-storage microgrid are as follows Figure 4As shown in the figure; in the traditional method, the power lower limit given to PEM and AEL electrolyzers is the same. At the same time, due to the small difference in their hydrogen production efficiency, when the goal is to maximize the benefits, the power allocation results of PEM and AEL electrolyzers are basically the same; in the proposed method, there is no need to give a power lower limit in advance, and the scheduling algorithm can automatically optimize the power allocation through dynamic safety constraints; due to the different dynamic responses of hydrogen and oxygen impurities in PEM and AEL electrolyzers, the allocated electrolyzer power lower limits are quite different;

[0141] The dynamic response of hydrogen and oxygen impurities to the electrolytic cell power is as follows: Figure 5 As shown in the figure, in the traditional method, the power allocated to the PEM and AEL electrolyzers is the same. However, since the hydrogen-oxygen impurity crossover of the AEL electrolyzer is more serious than that of the PEM electrolyzer, the hydrogen-oxygen impurity ratio of the AEL electrolyzer is higher, always higher than the safety limit of 2%. For the PEM electrolyzer, although its hydrogen-oxygen impurity ratio is below the safety limit for a long time, it still exceeds the limit in some time periods, endangering the safety of the system.

[0142] For the proposed method, whether it is a PEM electrolyzer or an AEL electrolyzer, the hydrogen and oxygen impurity ratio is below the safety limit of 2% during the entire time period, ensuring the safety of the system; at the same time, in some time periods, the hydrogen and oxygen impurity ratio of the electrolyzer is equal to 2%, and the system is in a card edge operation state, making full use of the response capacity of the electrolyzer;

[0143] In addition, if Figure 6 and Figure 7 As shown in the figure, when the upper limit of the hydrogen and oxygen impurity ratio in the dynamic safety constraint is changed to 1.8%, the proposed method can still make the system's hydrogen and oxygen impurity ratio meet the demand and operate at the edge during part of the time to make full use of the response capability of the electrolyzer; this shows that the proposed method can flexibly control the safety of the electrolyzer in the microgrid.

[0144] It should be noted that in the above embodiments, as long as the technical solutions are not contradictory, they can be arranged and combined, and those skilled in the art can exhaust all possibilities based on the mathematical knowledge of arrangement and combination. Therefore, the present invention will no longer describe the technical solutions after arrangement and combination one by one, but it should be understood that the technical solutions after arrangement and combination have been disclosed by the present invention.

[0145] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A solar-hydrogen-storage microgrid scheduling method considering dynamic safety constraints of electrolyzers, characterized by: The following steps are involved: Step 1: Conduct dynamic operation experiments on the AEL electrolyzer and PEM electrolyzer in the microgrid to obtain the hydrogen and oxygen impurity response characteristics and obtain a dynamic model of the hydrogen and oxygen impurity ratio of the electrolyzer; Step 2: Construct a dispatch model based on the operating characteristics of the microgrid.

2. A light-hydrogen-storage microgrid scheduling method considering dynamic safety constraints of electrolyzers according to claim 1, characterized in that: Step one includes the following steps: Step 1.1: Based on the voltage-current curve, the power-current curve of the electrolytic cell is obtained; the gas impurity model and the power-current curve are combined, and the electrolysis current is eliminated to obtain the relationship between the gas impurity ratio and the power of the electrolytic cell; Step 1.2: According to the step size of the scheduling problem, the dynamic security constraint model suitable for microgrid scheduling is obtained.

3. A light-hydrogen-storage microgrid scheduling method considering dynamic safety constraints of electrolyzers according to claim 2, characterized in that: In step 1.1, the dynamic model of hydrogen and oxygen impurity ratio of AEL electrolyzer can be expressed as: Among them, HTO AEL (t) and are the proportion and molar number of impurities in the gas-liquid separator on the anode side of the AEL electrolyzer at time t; p AEL , and T AEL are the pressure, volume and temperature of the gas in the gas-liquid separator on the anode side of the AEL electrolyzer; R is the ideal gas constant. The number of moles of gas impurities in the gas-liquid separator on the anode side is related to the gas impurities in the half-cell on the anode side of the electrolyzer: in, and are the molar flow rates of impurities caused by concentration diffusion, pressure difference permeation and alkali solution circulation in the anode half-cell of the AEL electrolyzer; is the molar flow rate of gas impurities flowing out of the gas-liquid separator on the anode side of the AEL electrolyzer, which is related to the electrolysis current of the AEL electrolyzer: Among them, I AEL is the electrolysis current of the AEL electrolytic cell; F is the Faraday constant; Based on (1)-(3), the relationship between the impurity ratio in the gas-liquid separator on the anode side of the AEL electrolyzer and the electrolysis current can be obtained; the power of the AEL electrolyzer is the product of the electrolysis current and the voltage: Among them, P AEL and U AEL Respectively represent the power and voltage of the AEL electrolyzer; the relationship between voltage and current is determined by the polarization curve: in, is the reversible voltage of the AEL electrolyzer; r 1,AEL 、r 2,AEL 、s AEL ,t 1,AEL ,t 2,AEL and t 3,AEL is an empirical coefficient, which can be obtained based on the dynamic operation experiment of the AEL electrolyzer; based on the voltage-current curve, the power-current curve of the AEL electrolyzer can be obtained; by combining the gas impurity model (1)-(3) and the power-current curve (4)-(5), eliminating the electrolysis current, the relationship between the gas impurity ratio and power of the AEL electrolyzer can be obtained: Among them, a AEL and b AEL is the constant of the AEL electrolyzer gas impurity response, which can be obtained from equations (1)-(5) and the dynamic operation experiment of the AEL electrolyzer; The difference between the gas impurity response of the PEM electrolyzer and the AEL electrolyzer is that the gas impurities in the anode side half-cell of the PEM electrolyzer are composed of only two parts: gas impurities caused by pressure difference penetration and concentration difference diffusion, namely: in, It represents the number of moles of impurities in the gas-liquid separator on the anode side of the PEM electrolyzer; They represent the molar flow rates of impurities caused by concentration diffusion and pressure difference penetration in the anode half-cell of the PEM electrolyzer respectively; is the molar flow rate of gas impurities flowing out of the gas-liquid separator on the anode side of the PEM electrolyzer; Modeling the PEM electrolyzer provides the relationship between its gas impurity ratio and power: Among them, HTO PEM is the gas impurity ratio of the PEM electrolyzer; P PEM is the power of the PEM electrolyzer; a PEM and b PEM The constant representing the gas impurity response of the PEM electrolyzer can be obtained from the dynamic operation experiment of the PEM electrolyzer.

4. A method for scheduling a light-hydrogen-storage microgrid considering dynamic safety constraints of electrolyzers according to claim 3, characterized in that: In step 1.2, the dynamic gas impurity models (6) and (8) of the AEL electrolyzer and PEM electrolyzer are discretized to obtain a dynamic safety constraint model suitable for microgrid scheduling: Among them, Δt is the step size of the day-ahead scheduling; t end Indicates the number of time steps or dimensions of each variable for day-ahead scheduling, which is related to the scheduling step size:

5. A method for scheduling a light-hydrogen-storage microgrid considering dynamic safety constraints of electrolyzers according to claim 4, characterized in that: Step 2 includes the following steps: Step 2.1: Microgrid operation characteristic model; Step 2.2: Considering the operating characteristics of the microgrid, the optimal dispatching strategy is obtained by finding the maximum value of the objective function.

6. A method for scheduling a light-hydrogen-storage microgrid considering dynamic safety constraints of electrolyzers according to claim 5, characterized in that: In step 2.1, the source and load power of the microgrid should be balanced: P fuel (t)+P PV (t)=P AEL (t)+P PEM (t)+P load (t)+P sto (t)+P grid (t) (12) Among them, P fuel and P PV Represent the output power of fuel cell and photovoltaic respectively; P AEL and P PEM Respectively represent the power consumed by AEL electrolyzer and PEM electrolyzer for hydrogen production; P load Represents the power of the electrical load in the microgrid; P sto Indicates the power of electrochemical energy storage. A positive value indicates charging, while a negative value indicates discharging. grid Represents the amount of electricity exchanged between the microgrid and the power system. A positive power indicates that the microgrid sells electricity to the upper-level power grid, and a negative power indicates that the microgrid purchases electricity from the upper-level power grid. PV and P load is the known day-ahead forecast value, and P grid , P sto , P AEL , P PEM and P fuel is the optimization variable that needs to be solved by the scheduling model; There is a direct coupling between the power and the flow of hydrogen in the microgrid; the electrolyzer is the only source of hydrogen in the microgrid, and the relationship between its hydrogen production and power can be expressed by a quadratic function: in, and are the molar flow rates of hydrogen produced by the AEL electrolyzer and the PEM electrolyzer, respectively; h AEL,1 、h AEL,2 、h AEL,3 、h PEM,1 、h PEM,2 and h PEM,3 is the hydrogen production coefficient of the electrolyzer; The fuel cell consumes hydrogen to generate electricity and supplies power to the microgrid when power is insufficient. The power supply and hydrogen consumption can be expressed as: in, is the molar flow rate of hydrogen consumed by the fuel cell; η cell is the hydrogen-to-electricity conversion coefficient of the fuel cell; There is a balance between the hydrogen produced by the electrolyzer in the microgrid, the hydrogen consumed by the fuel cell, and the hydrogen stored in the hydrogen tank: in, is the molar flow rate of hydrogen flowing into the hydrogen storage tank; since the amount of hydrogen in the hydrogen storage tank is always not less than 0, then: in, Indicates the amount of hydrogen stored in the hydrogen storage tank at the initial moment; At the same time, the hydrogen produced by the microgrid needs to meet the given day-ahead hydrogen production demand: in, is the day-ahead hydrogen production demand of the microgrid, which is a known value.

7. A method for dispatching a photovoltaic-hydrogen-storage microgrid considering dynamic safety constraints of electrolyzers according to claim 6, characterized in that: In step 2.2, in actual dispatching, the operating characteristics of the microgrid are considered, and the optimal dispatching strategy is obtained by finding the maximum value of the objective function, with economy as the goal; the economic objective function can be expressed as: Among them, w power and The prices for electricity and hydrogen sales; In summary, the microgrid dispatch model considering the dynamic safety constraints of the electrolyzer can be expressed as:

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