Partition control method and system for renewable energy direct-current micro-grid hydrogen production

Abstract

The invention discloses a zone control method and system for renewable energy direct current micro-grid hydrogen production, and belongs to the technical field of electric power control, and the method comprises the steps: S10, obtaining photovoltaic power inputted to a preset electrolytic cell, collecting the hydrogen production amount of the preset electrolytic cell based on the change of the photovoltaic power, and generating a database; s20, in the database, collecting at least two groups of photovoltaic power corresponding to different time periods, and analyzing the change rule of the photovoltaic power in different time periods; the different time periods comprise the noon period and the afternoon period; and S30, distinguishing the collected photovoltaic power in different time periods according to a stable change mode and a non-stable change mode, and collecting the photovoltaic power in the non-stable change mode. According to the invention, through real-time monitoring and analysis of the photovoltaic power, especially in an unstable change period with large power fluctuation, the abnormal state of the electrolytic cell can be found in time, and unstable hydrogen production amount or equipment damage caused by photovoltaic power fluctuation is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of power control, and in particular to a zoning control method and system for hydrogen production in a renewable energy DC microgrid. Background Art

[0002] Hydrogen production in a DC microgrid is a new energy system that combines a DC microgrid with water electrolysis hydrogen production technology.

[0003] A DC microgrid consists of distributed power sources (such as solar photovoltaics, wind power generation, etc.), energy storage devices (such as lithium batteries, supercapacitors, etc.), loads, and a DC bus. It adopts DC power transmission to adapt to the characteristics of renewable energy power generation. In order to apply DC microgrid hydrogen production to different scenarios, the application document with the patent application number CN202110996785.2 provides a decision-making method for hydrogen production in a renewable energy DC microgrid, including Step 1: The energy management system of the renewable energy DC microgrid monitors the operation data in real time to obtain the power information of each unit at the current moment, including hydrogen production power, wind power, photovoltaic power, energy storage unit power, and the state of charge (SOC) of the energy storage unit; Step 2: Use the power information of each unit at the current moment as input, combine the power prediction information of each unit at the next moment t + 1, including the predicted value of hydrogen production power at the next moment, the predicted value of wind power at the next moment, and the predicted value of photovoltaic power at the next moment, and make a judgment based on the change degree of hydrogen production power, and calculate the power value of the energy storage unit at the next moment as the output. This technical solution can adjust the power of the energy storage unit, thereby optimizing the operation of the DC microgrid.

[0004] Another application document with the patent application number CN202110998425.6 provides a zoning control method for hydrogen production in a renewable energy DC microgrid, including Step 1: Monitor the operation data. When each unit is operating, the energy management system obtains the current DC microgrid voltage value, fan port power value, photovoltaic port power value, energy storage port power value, AC load power value, and hydrogen production power value; Step 2: Determine the working zone based on the set value and preset value and calculate the hydrogen production power at the next moment in combination with the prediction information. Specifically, set the steady-state value of the DC microgrid voltage and the maximum fluctuation range. This technical solution facilitates the hydrogen production device to make timely adjustments, which is conducive to ensuring the high efficiency of hydrogen production and the real-time balance of the power of the DC microgrid.

[0005] However, the output power of renewable energy (such as wind power and photovoltaics) is intermittent and volatile, and most of the existing zoning control strategies are based on static or quasi-static zoning modes, which are difficult to adapt to the rapid change of power in real time. In this case, it is impossible to smooth the fluctuation of photovoltaic power. When the power fluctuation is large, it is difficult to maintain the voltage and power balance within the zone, resulting in a decrease in the efficiency of the hydrogen production system and even affecting the service life of the electrolyzer. Summary of the Invention

[0006] In view of the above existing problems in the field of power control technology, the present invention is proposed.

[0007] Therefore, one of the objectives of the present invention is to provide a zoning control method and system for hydrogen production in a renewable energy DC microgrid. Through real-time monitoring and analysis of photovoltaic power, especially during unstable change periods with large power fluctuations, it can timely detect abnormal states of electrolyzers and avoid unstable hydrogen production or equipment damage caused by photovoltaic power fluctuations.

[0008] To solve the above technical problems, the present invention provides the following technical solutions: On the one hand, the present invention provides a zoning control method for hydrogen production in a renewable energy DC microgrid, including the following steps: Step S10: Obtain the photovoltaic power input to a preset electrolyzer, collect the hydrogen production amount of the preset electrolyzer based on the change of the photovoltaic power, and generate a database; Step S20: In the database, collect at least two sets of photovoltaic power corresponding to different time periods, and analyze the change rules of the photovoltaic power in different time periods; the different time periods include the noon period and the afternoon period; Step S30: In different time periods, distinguish the collected photovoltaic power in the ways of stable change and unstable change, mark the power data corresponding to the collected unstable change photovoltaic power as reference data, collect the first data that appears in the reference data, and analyze the change characteristics of the reference data based on the first data. The analysis methods include time domain analysis; The time domain analysis includes power time series analysis and power change rate analysis. The power time series analysis includes recording photovoltaic power data in chronological order to obtain the overall change trend and short-term fluctuation of photovoltaic power over time; The power change rate analysis includes calculating the change rate of photovoltaic power at different time intervals; Step S40: Based on the first data, analyze the time node corresponding to its appearance time, collect 5 to 10 power data that are earlier than the appearance of the first data according to the time node, and mark the 5 to 10 power data that are earlier than the appearance of the first data as determination data; Step S50: Based on the change of the determination data, collect the change of the hydrogen production amount of the preset electrolyzer, and analyze the associated influence of the change of the determination data on the change of the hydrogen production amount; if the change trend of the hydrogen production amount is the same as the change trend of the determination data, it is determined that the preset electrolyzer is in an abnormal state; otherwise, it is not determined.

[0009] As a preferred embodiment of the present invention, in step S30, the non-steady change is measured on a time scale, and the time scale includes a 1-minute time scale and a 5-minute time scale. Among them, in the 1-minute time scale, the fluctuation of the photovoltaic power is greater than 10%; in the 5-minute time scale, the fluctuation of the photovoltaic power is greater than 20%.

[0010] As a preferred embodiment of the present invention, in step S50, analyze the correlation effect of the change of the determination data on the change of the hydrogen production amount. The analysis method includes taking the first three power data in the determination data as the analysis object, based on the first power data in the analysis object, obtaining the time interval when the latter two power data appear, analyzing the change characteristics of the latter two power data relative to the first power data during the time interval, and calculating the change of the hydrogen production amount of the preset electrolyzer based on the change characteristics, which is calculated according to the following formula: ; where represents the th time to obtain the th hydrogen production amount of the preset electrolyzer in the analysis object; In the above formula, represents the th time to obtain the th hydrogen production amount of the preset electrolyzer within the time interval, represents the change amount of the hydrogen production amount within two said time intervals, represents the time interval corresponding to the change amount, represents the duration of two said time intervals.

[0011] As a preferred embodiment of the present invention, according to the change of the hydrogen production amount within two said time intervals, obtain the interval duration between the second power data and the first power data in the analysis object. During the interval duration, if the hydrogen production amount changes in a decreasing trend, it is determined that the preset electrolyzer is in an abnormal state; otherwise, it is not determined.

[0012] As a preferred embodiment of the present invention, if it is determined that the preset electrolyzer is in an abnormal state, then mark the interval duration between the second power data and the first power data obtained in the analysis object as the reference duration, and based on the reference duration, obtain the interval duration between the third power data and the second power data, mark the interval duration as the verification duration, collect the change amount of the hydrogen production amount of the preset electrolyzer from the reference duration to the verification duration. If the change amount changes in a stable trend, the determination of the abnormal state of the preset electrolyzer is lifted; otherwise, it is not lifted.

[0013] As a preferred embodiment of the present invention, the following steps are included: generating a dataset corresponding to the hydrogen production amount of a preset electrolytic cell according to the change amount, obtaining 5 to 8 hydrogen production amounts with the most occurrences and the least occurrences in the dataset, and calculating the regular influence of the fluctuation of the photovoltaic power on the two data based on the hydrogen production amount data with the most occurrences and the least occurrences, which is calculated by the following formula: ; where represents the th obtained change value of the th photovoltaic power from the reference duration to the verification duration; In the above formula, represents the acquisition duration preset for obtaining the photovoltaic power from the reference duration to the verification duration, represents the change value of the photovoltaic power obtained during the acquisition duration, and the change value includes the maximum photovoltaic power and the minimum photovoltaic power obtained; represents the hydrogen production amount data corresponding to the th obtained photovoltaic power and the th photovoltaic power during the acquisition duration.

[0014] As a preferred embodiment of the present invention, the following steps are included: obtaining the hydrogen production amount data corresponding to the minimum photovoltaic power, and presetting a risk threshold according to the minimum photovoltaic power. When obtaining the hydrogen production amount of the preset electrolytic cell in a future period, within the preset acquisition duration, if the photovoltaic power is not lower than the risk threshold, it is determined that the hydrogen production amount of the preset electrolytic cell will change in a stable trend; otherwise, it is not determined.

[0015] As a preferred embodiment of the present invention, the following steps are included: if it is determined that the hydrogen production amount of the preset electrolytic cell will change in a stable trend, obtaining the minimum photovoltaic power corresponding to the determination result, calculating the intermediate value between the minimum photovoltaic power and the risk threshold. When obtaining the hydrogen production amount of the preset electrolytic cell in a future period, if the photovoltaic power fluctuates below the intermediate value and / or is lower than the intermediate value, it is determined that the preset electrolytic cell is in an abnormal state; otherwise, it is not determined.

[0016] On the other hand, the present invention provides a system applied to the zoning control method of a renewable energy DC microgrid hydrogen production as described above, including: A data acquisition module, configured to acquire the photovoltaic power input to a preset electrolytic cell, collect the hydrogen production amount of the preset electrolytic cell based on the change of the photovoltaic power, and generate a database; A data collection module, which responds to the database and is configured to collect at least two sets of photovoltaic powers corresponding to different time periods in the database, and analyze the change rules of the photovoltaic power in different time periods; the different time periods include the noon time period and the afternoon time period; A fusion processing module is used to distinguish and process the photovoltaic power collected in different time periods. The fusion processing module includes a distinguishing unit, an analyzing unit, and a determining unit; The distinguishing unit is used to distinguish the photovoltaic power collected in different time periods in a stable change and an unstable change manner, collect the photovoltaic power in the unstable change, and mark the power data corresponding to the collected photovoltaic power as reference data; The analyzing unit responds to the reference data, is used to collect the first data that appears in the reference data, and analyze the change characteristics of the reference data based on the first data; It further includes analyzing, based on the first data, the time node corresponding to its appearance time, collecting 5 to 10 power data earlier than the appearance of the first data according to the time node, and marking the 5 to 10 power data earlier than the appearance of the first data as determination data; The determining unit collects the change of the hydrogen production amount of the preset electrolytic cell based on the change of the determination data, and analyzes the associated influence of the change of the determination data on the change of the hydrogen production amount; if the change trend of the hydrogen production amount is the same as the change trend of the determination data, it is determined that the preset electrolytic cell is in an abnormal state; otherwise, it is not determined.

[0017] 1. Through the real-time monitoring and analysis of photovoltaic power, especially in the unstable change period with large power fluctuations, the present invention can timely detect the abnormal state of the electrolytic cell, and avoid the instability of hydrogen production amount or equipment damage caused by the photovoltaic power fluctuation; 2. When the present invention determines that the electrolytic cell is in an abnormal state, through the comparative analysis of the verification duration and the reference duration, it can quickly adjust the system operation strategy and reduce the decrease of hydrogen production efficiency caused by the abnormal state; 3. Through the dual analysis method of time scale and power fluctuation, the present invention can automatically identify the stable change and unstable change of photovoltaic power, providing support for the intelligent control of the hydrogen production system; 4. Through the generation of data sets and the analysis of regular influences, the present invention further optimizes the system operation strategy, and by dynamically adjusting the risk threshold and the intermediate value, it can flexibly respond to the hydrogen production requirements under different working conditions and improve the flexibility of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to these drawings. Among them: Figure 1A schematic diagram of the modular structure of a zoning control system for hydrogen production in a renewable energy DC microgrid according to an embodiment of the present invention; Figure 2 A schematic diagram of a method flow of an embodiment of the present invention; Numbers in the figure: 110 - data acquisition module; 120 - data collection module; 130 - fusion processing module; 1301 - distinction unit; 1302 - analysis unit; 1303 - determination unit. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0020] The present invention proposes a zoning control method and system for hydrogen production in a renewable energy DC microgrid, which improves the stability, adaptability and hydrogen production efficiency of the system through data collection, quantitative analysis, dynamic adjustment and risk warning.

[0021] The present invention is further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0022] Reference Figures 1 to 2 , is an embodiment of the present invention, which provides a partition control method for hydrogen production in a renewable energy DC microgrid, comprising the following steps: Step S10: Acquire the photovoltaic power input to the preset electrolyzer, collect the hydrogen production of the preset electrolyzer based on the change of the photovoltaic power, and generate a database; In this embodiment, by collecting photovoltaic power and hydrogen production data, an operation database of the system is established, which provides a data basis for subsequent analysis and control and a basis for dynamic adjustment of the system; Step S20: collecting at least two groups of photovoltaic power corresponding to different time periods in the database, and analyzing the variation pattern of photovoltaic power in different time periods; the different time periods include noon period and afternoon period; Through time-period differentiation analysis, the changing rules of photovoltaic power in different time periods are clarified, which is conducive to the formulation of targeted control strategies; At the same time, the system operating parameters can be adjusted according to the characteristics of different time periods to improve the adaptability and flexibility of the system; In this embodiment, during the noon period (11:00 - 13:00), the solar irradiance reaches its peak, and the photovoltaic power generation also reaches the highest point of the day. At this time, the power output is relatively stable, but there may be short-term fluctuations, especially in cloudy weather; this period is the "rich light period" of the photovoltaic system, which can be used to evaluate the maximum output capacity and stability of the photovoltaic system under high irradiance, as well as analyze the impact of power fluctuations on the hydrogen production of the electrolyzer; During the afternoon period (13:00 - 15:00), the solar irradiance begins to gradually decline, and the photovoltaic power generation also slowly decreases accordingly. At this time, the power output curve is relatively smooth, but it may still be affected by factors such as cloud cover. This period can be used to analyze the output characteristics of the photovoltaic system during the decline of irradiance, as well as evaluate the impact of the power decline rate on the power grid; Step S30: In different time periods, distinguish the collected photovoltaic power according to stable change and non-stable change methods, mark the power data corresponding to the collected non-stable change photovoltaic power as reference data, collect the first data that appears in the reference data, and analyze the change characteristics of the reference data based on the first data; The analysis methods include time-domain analysis. Time-domain analysis includes power time series analysis and power change rate analysis. Power time series analysis includes recording photovoltaic power data in chronological order to obtain the overall change trend and short-term fluctuation conditions of photovoltaic power over time; Power change rate analysis includes calculating the change rate of photovoltaic power within different time intervals; For example, within a day, usually the photovoltaic power gradually increases as the sun rises, reaches its peak around noon, and then gradually decreases as the sun sets. This trend reflects the influence of the solar altitude angle and sunshine duration on photovoltaic power. Through long-term trend analysis, seasonal changes can also be found. For example, in summer, the sunshine duration is long and the solar altitude angle is high, and the overall level of photovoltaic power will be higher than in winter; When analyzing the short-term fluctuation conditions of photovoltaic power data, due to factors such as cloud cover and atmospheric scattering, the photovoltaic power will fluctuate within a short period. For example, when a cloud quickly passes over the photovoltaic array, the photovoltaic power will drop sharply and then recover after the cloud passes. The short-term fluctuation amplitude of the power (such as the absolute value of the power difference between adjacent time points) can be calculated to quantify this fluctuation degree. This is very important for the hydrogen production system because severe power fluctuations may affect the stable operation of the electrolyzer, and corresponding control strategies need to be adopted to suppress the fluctuations; Non-stable change is measured on a time scale. The time scale includes a 1-minute time scale and a 5-minute time scale; among them, the 1-minute time scale means that the fluctuation of photovoltaic power is greater than 10%; the 5-minute time scale means that the fluctuation of photovoltaic power is greater than 20%; In a possible implementation of this embodiment, a quantization standard is proposed, which provides a clear quantization standard for power fluctuations, facilitating automatic system judgment; and through analysis on different time scales, it can adapt to power changes in different scenarios; in the future, the time scale and fluctuation amplitude can also be adjusted according to actual needs to improve the flexibility of the system; First, it can distinguish between stable and unstable changes in photovoltaic power, avoiding misjudgment caused by normal fluctuations; Second, by focusing on the unstable change period, it can quickly capture power fluctuations that may lead to system anomalies; Finally, through the analysis of unstable changes, it can give early warnings of possible system risks and enhance the stability of the system; In this embodiment, experience in hydrogen production in a DC microgrid shows that even in sufficient sunlight, the light intensity is still affected by various factors and fluctuates, such as cloud cover, atmospheric scattering, and changes in the solar altitude angle, etc. Among them, the change in the solar altitude angle is the continuous change of the position of the sun in the sky, resulting in a corresponding change in the light intensity per unit area; it also includes factors such as temperature influence and shadow occlusion; therefore, it is of practical significance to analyze the change characteristics of reference data based on unstable changes; Step S40: Based on the first data, analyze the time node corresponding to its appearance time, collect 5 - 10 power data that are earlier than the appearance of the first data according to the time node, and mark the 5 - 10 power data that are earlier than the appearance of the first data as judgment data; This embodiment can perform trend analysis. By collecting multiple data points and analyzing the power change trend, it provides a more comprehensive basis for subsequent judgment; At the same time, associating the power data with the time node can more accurately evaluate the impact of power changes on the system; Step S50: Based on the change of the judgment data, collect the change of the hydrogen production amount of the preset electrolyzer, and analyze the associated impact of the change of the judgment data on the change of the hydrogen production amount; if the change trend of the hydrogen production amount is the same as the change trend of the judgment data, it is determined that the preset electrolyzer is in an abnormal state; otherwise, it is not determined; It should be noted in this embodiment that whenever it is determined that the preset electrolyzer is in an abnormal state, a configured energy storage system (such as a battery) or a backup power supply can be connected to the preset electrolyzer to smooth the fluctuations of the photovoltaic power and ensure the stable operation of the preset electrolyzer; In step S50, the correlation effect of the change of the judgment data on the change of the hydrogen production amount is analyzed, and the analysis method includes taking the first three power data in the judgment data as the analysis object, obtaining the time interval between the appearance of the last two power data based on the first power data in the analysis object, analyzing the change characteristics of the last two power data relative to the first power data in the time interval, and calculating the change of the hydrogen production amount of the preset electrolyzer based on the change characteristics, and calculating it according to the following formula: ;in, Indicates the first Get the preset electrolytic cell Hydrogen production capacity; In the above formula, Indicates the time interval The first The amount of hydrogen produced, represents the change in hydrogen production between two time intervals, represents the time interval corresponding to the change, Indicates the duration of two time intervals; In this embodiment, the relationship between power change and hydrogen production change is quantified to provide an accurate basis for system control; and based on the quantification results, the system can dynamically adjust the operating parameters to optimize the hydrogen production efficiency; In this embodiment, according to the change of hydrogen production within two time intervals, the interval between the second power data and the first power data is obtained in the analysis object. If the hydrogen production changes in a decreasing trend within the interval, it is determined that the preset electrolyzer is in an abnormal state; otherwise, it is not determined. On the basis of the above, in this embodiment, if it is determined that the preset electrolyzer is in an abnormal state, the interval time between the second power data and the first power data obtained is marked as the reference time in the analysis object, and the interval time between the third power data and the second power data is obtained based on the reference time, and the interval time is marked as the verification time, and the change in the hydrogen production of the preset electrolyzer from the reference time to the verification time is collected. If the change shows a stable trend, the determination of the abnormal state of the preset electrolyzer is lifted, otherwise, it is not lifted; The change amount shows a steady trend, indicating that the fluctuation range of the hydrogen production of the preset electrolyzer is less than 10% each time; By comparing the verification time with the reference time, the abnormal state of the electrolyzer can be dynamically verified to avoid misjudgment, reduce misjudgment caused by short-term fluctuations, and improve the stability of the system; In this embodiment, based on the experience of DC microgrid hydrogen production, it is shown that when the photovoltaic power fluctuates, the hydrogen production of the electrolyzer does not necessarily change all the time, and its change trend is not necessarily a monotonous decrease, but may also change steadily. The reason lies in the type of electrolyzer and the amplitude and frequency of power fluctuations; Among them, regarding the types of electrolyzers, there are alkaline electrolyzers (AEL) and proton exchange membrane electrolyzers (PEMEL); alkaline electrolyzers (AEL) have poor adaptability to power fluctuations. When the input power fluctuates rapidly, the AEL may not be able to respond in time, resulting in reduced hydrogen production efficiency and even frequent start-stop situations; for example, when a single photovoltaic input is used, the hydrogen production rate of the AEL may be reduced due to power fluctuations; The proton exchange membrane electrolyzer (PEMEL) has stronger load response characteristics and can better adapt to rapid power fluctuations. When the photovoltaic power fluctuates, the hydrogen production of PEMEL changes relatively smoothly and has stronger fluctuation adaptability. As for the amplitude and frequency of power fluctuations, if the photovoltaic power fluctuations are small and the frequency is low, the electrolyzer (especially PEMEL) can adapt by adjusting its own operating state, and the change in hydrogen production is relatively stable; therefore, in this embodiment, if the change amount shows a stable trend, the determination of the abnormal state of the preset electrolyzer is lifted, which has practical significance; At the same time, this embodiment generates a data set of hydrogen production corresponding to the preset electrolyzer according to the variation, obtains 5 to 8 hydrogen productions with the most and least occurrences in the data set, and calculates the regular influence of the fluctuation of photovoltaic power on the two data according to the hydrogen production data with the most and least occurrences, and calculates it by the following formula: ;in, Indicates the time from reference to verification. The first obtained The change value of photovoltaic power; In the above formula, Indicates the preset acquisition time for obtaining photovoltaic power from the reference time to the verification time. Indicates the change value of the photovoltaic power obtained during the acquisition time, and the change value includes the maximum photovoltaic power and the minimum photovoltaic power obtained; Indicates the first The first and The hydrogen production data corresponding to each photovoltaic power; In this embodiment, a hydrogen production data set is generated to analyze the influence of photovoltaic power fluctuation on hydrogen production; through data set analysis, data support is provided for system optimization; By identifying the patterns of PV power fluctuations and hydrogen production changes, a basis for system adjustment is provided; It should be emphasized in this embodiment that the hydrogen production data corresponding to the minimum photovoltaic power is obtained, and a risk threshold is preset according to the minimum photovoltaic power. When the hydrogen production of the preset electrolyzer is obtained in a future period, within a preset acquisition duration, if the photovoltaic power does not fall below the risk threshold, it is determined that the hydrogen production of the preset electrolyzer will change in a stable trend; otherwise, it is not determined. In this embodiment, a risk threshold is preset according to the minimum photovoltaic power to predict the change trend of future hydrogen production, and the risk threshold is used to anticipate possible abnormal states in the future, take measures in advance, and dynamically adjust the risk threshold according to real-time data to improve the flexibility of the system. On the above basis, if it is determined that the hydrogen production of the preset electrolyzer will change in a stable trend, the minimum photovoltaic power corresponding to the determination result is obtained, and the intermediate value between the minimum photovoltaic power and the risk threshold is calculated. When the hydrogen production of the preset electrolyzer is obtained in a future period, if the photovoltaic power fluctuates below the intermediate value and / or is lower than the intermediate value, it is determined that the preset electrolyzer is in an abnormal state; otherwise, it is not determined. In this embodiment, the intermediate value between the minimum photovoltaic power and the risk threshold is calculated for abnormal determination in a future period. By introducing the intermediate value, the accuracy of abnormal state determination is improved; and based on the determination result of the intermediate value, the system control strategy is optimized to improve the operation efficiency.

[0023] Based on the above, through the real-time monitoring and analysis of the photovoltaic power, especially in the non-stable change period with large power fluctuations, the present application can timely detect the abnormal state of the electrolyzer and avoid the instability of hydrogen production or equipment damage caused by the fluctuation of photovoltaic power.

[0024] Combined with the above-mentioned partition control method for hydrogen production in a renewable energy DC microgrid, this embodiment also proposes a system applied to this method, as follows: A data acquisition module 110, configured to acquire the photovoltaic power input to a preset electrolyzer, collect the hydrogen production of the preset electrolyzer based on the change of the photovoltaic power, and generate a database. A data collection module 120, which responds to the database and is configured to collect at least two sets of photovoltaic powers corresponding to different periods in the database and analyze the change rules of the photovoltaic power in different periods; different periods include the noon period and the afternoon period. A fusion processing module 130, configured to perform discrimination processing on the photovoltaic powers collected in different periods. The fusion processing module 130 includes a discrimination unit 1301, an analysis unit 1302, and a determination unit 1303. The discrimination unit 1301 is configured to discriminate the photovoltaic powers collected in different periods in a stable change and a non-stable change manner, collect the photovoltaic power in the non-stable change, and mark the power data corresponding to the collected photovoltaic power as reference data. The analysis unit 1302 responds to the reference data, is used to collect the first data that appears in the reference data, and analyzes the change characteristics of the reference data based on the first data; It further includes analyzing the time node corresponding to the appearance time based on the first data, collecting 5 to 10 power data that are earlier than the appearance of the first data according to the time node, and marking the 5 to 10 power data that are earlier than the appearance of the first data as determination data; The determination unit 1303 collects the change in the hydrogen production amount of the preset electrolytic cell based on the change in the determination data, and analyzes the associated influence of the change in the determination data on the change in the hydrogen production amount; if the change trend of the hydrogen production amount is the same as the change trend of the determination data, it is determined that the preset electrolytic cell is in an abnormal state; otherwise, it is not determined.

[0025] In summary, the present invention realizes the refined control of the renewable energy DC microgrid hydrogen production system, and improves the stability, adaptability and hydrogen production efficiency of the system through means such as data collection, quantitative analysis, dynamic adjustment and risk warning.

[0026] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A zoning control method for hydrogen production in a renewable energy DC microgrid, characterized in that It includes the following steps: Step S10: Obtain the photovoltaic power input to a preset electrolyzer, collect the hydrogen production amount of the preset electrolyzer based on the change of the photovoltaic power, and generate a database; Step S20: In the database, collect at least two groups of photovoltaic powers corresponding to different time periods, and analyze the change law of the photovoltaic power in different time periods; the different time periods include the noon time period and the afternoon time period; Step S30: In different time periods, distinguish the collected photovoltaic powers in the ways of stable change and non-stable change, mark the power data corresponding to the collected non-stable change photovoltaic power as reference data, collect the first data that appears in the reference data, and analyze the change characteristics of the reference data based on the first data. The analysis methods include time domain analysis; The time domain analysis includes power time series analysis and power change rate analysis. The power time series analysis includes recording the photovoltaic power data in chronological order to obtain the overall change trend and short-term fluctuation of the photovoltaic power over time; The power change rate analysis includes calculating the change rate of the photovoltaic power at different time intervals; Step S40: Based on the first data, analyze the time node corresponding to its appearance time, collect 5-10 power data that are earlier than the appearance of the first data according to the time node, and mark the 5-10 power data that are earlier than the appearance of the first data as judgment data; Step S50: Collect the change of the hydrogen production amount of the preset electrolyzer based on the change of the judgment data, and analyze the associated influence of the change of the judgment data on the change of the hydrogen production amount; If the change trend of the hydrogen production amount is the same as the change trend of the judgment data, it is determined that the preset electrolyzer is in an abnormal state; Otherwise, no determination is made.

2. The zonal control method for hydrogen production in a renewable energy DC microgrid according to claim 1, wherein In the step S30, the non-stable change is measured on a time scale, and the time scale includes a 1-minute time scale and a 5-minute time scale; wherein, the 1-minute time scale means that the fluctuation of the photovoltaic power is greater than 10%; the 5-minute time scale means that the fluctuation of the photovoltaic power is greater than 20%.

3. The zoning control method for hydrogen production in a renewable energy DC microgrid according to claim 1, characterized in that, In the step S50, analyzing the associated influence of the change of the judgment data on the change of the hydrogen production amount, the analysis method includes taking the first three power data in the judgment data as the analysis object, based on the first power data in the analysis object, obtaining the time interval when the latter two power data appear, analyzing the change characteristics of the latter two power data relative to the first power data during the time interval, and calculating the change of the hydrogen production amount of the preset electrolyzer based on the change characteristics, which is calculated according to the following formula: ; wherein, represents the -th acquisition of the -th hydrogen production amount of the preset electrolytic cell in the analysis object; In the above formula, Indicates the number of The first The amount of hydrogen produced, represents the change in the amount of hydrogen produced between the two time intervals, represents the time interval corresponding to the change, Indicates the duration of the two time intervals.

4. The zoning control method for hydrogen production in a renewable energy DC microgrid according to claim 3, wherein, According to the change of the hydrogen production amount within two time intervals, obtain the interval duration between the second power data and the first power data in the analysis object. During the interval duration, if the hydrogen production amount changes in a decreasing trend, it is determined that the preset electrolyzer is in an abnormal state; Otherwise, no determination is made.

5. The zoning control method for hydrogen production in a renewable energy DC microgrid according to claim 4, wherein, If it is determined that the preset electrolytic cell is in an abnormal state, the time interval between the second power data and the first power data obtained in the analysis object is marked as the reference time, and based on the reference time, the time interval between the third power data and the second power data is obtained, and the time interval is marked as the verification time. The change amount of the hydrogen production amount of the preset electrolytic cell from the reference time to the verification time is collected. If the change amount shows a stable trend, the determination of the abnormal state of the preset electrolytic cell is lifted; otherwise, it is not lifted.

6. The zoning control method for hydrogen production in a renewable energy DC microgrid according to claim 5, characterized in that, Generate a data set corresponding to the hydrogen production amount of the preset electrolytic cell according to the change amount. In the data set, obtain 5 to 8 hydrogen production amounts with the most occurrences and the fewest occurrences. Calculate the regular influence of the fluctuation of the photovoltaic power on the two data according to the hydrogen production amount data with the most occurrences and the fewest occurrences, and calculate it with the following formula: ; wherein, represents the change value of the th obtained th photovoltaic power during the period from the reference duration to the verification duration; In the above formula, represents the acquisition duration preset for acquiring the photovoltaic power from the reference duration to the verification duration, represents the change value of the photovoltaic power acquired during the acquisition duration, and the change value includes the maximum photovoltaic power and the minimum photovoltaic power acquired; represents the th acquisition during the acquisition duration and the hydrogen production data corresponding to the th photovoltaic power.

7. The zonal control method for hydrogen production in a renewable energy DC microgrid according to claim 6, characterized in that Obtain the hydrogen production amount data corresponding to the minimum photovoltaic power, and preset a risk threshold according to the minimum photovoltaic power. When the hydrogen production amount of the preset electrolytic cell is obtained in the future time period, within the preset acquisition time, if the photovoltaic power is not lower than the risk threshold, it is determined that the hydrogen production amount of the preset electrolytic cell will show a stable trend; otherwise, it is not determined.

8. The zoning control method for hydrogen production in a renewable energy DC microgrid according to claim 7, characterized in that, If it is determined that the hydrogen production amount of the preset electrolytic cell will show a stable trend, obtain the minimum photovoltaic power corresponding to the determination result, and calculate the intermediate value between the minimum photovoltaic power and the risk threshold. When the hydrogen production amount of the preset electrolytic cell is obtained in the future time period, if the photovoltaic power fluctuates below the intermediate value and / or is lower than the intermediate value, it is determined that the preset electrolytic cell is in an abnormal state; Otherwise, it is not determined.

9. A system applied to the zoning control method for hydrogen production in a renewable energy DC microgrid as described in claim 1, characterized in that, Including: A data acquisition module, which is used to acquire the photovoltaic power input to the preset electrolytic cell, collect the hydrogen production amount of the preset electrolytic cell based on the change of the photovoltaic power, and generate a database; A data collection module, which responds to the database and is used to collect at least two sets of photovoltaic powers corresponding to different time periods in the database, and analyze the change rules of the photovoltaic power in different time periods; the different time periods include the noon time period and the afternoon time period; A fusion processing module, which is used to distinguish the photovoltaic powers collected in different time periods. The fusion processing module includes a distinguishing unit, an analyzing unit and a determining unit; The distinguishing unit is used to distinguish the photovoltaic powers collected in different time periods in the way of stable change and non-stable change, collect the photovoltaic power in the non-stable change, and mark the power data corresponding to the collected photovoltaic power as reference data; The analyzing unit responds to the reference data and is used to collect the first data that appears in the reference data, and analyze the change characteristics of the reference data based on the first data; It also includes analyzing the time node corresponding to the appearance time based on the first data, collecting 5 to 10 power data that appear earlier than the first data according to the time node, and marking the 5 to 10 power data that appear earlier than the first data as determination data; The determination unit collects the change in the hydrogen production amount of the preset electrolytic cell based on the change in the determination data, and analyzes the associated influence of the change in the determination data on the change in the hydrogen production amount; If the change trend of the hydrogen production amount is the same as the change trend of the determination data, it is determined that the preset electrolytic cell is in an abnormal state; Otherwise, no determination is made.

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