Multi-element flexible load feature extraction method based on hydrogen energy demand response

Abstract

The invention discloses a multi-element flexible load feature extraction method based on hydrogen energy demand response, and relates to the technical field of hydrogen energy demand resource planning. In order to construct an optimization control model responding to a power grid signal, hydrogen production efficiency maximization and power utilization planning rationalization are realized. The method specifically comprises the following steps: obtaining new energy power generation power characteristic data, predicting daily average generating capacity data according to the data, obtaining all-day time-of-use electricity price characteristic data of a commercial power grid, and dividing the data into peak / flat / valley time periods; according to the multi-element flexible load feature extraction method and the control strategy, the electric energy use strategy and the hydrogen production and hydrogen supply equipment operation strategy suitable for the whole hydrogen energy supply project can be formulated according to the stirring filtering of the new energy generating capacity, so that the energy consumption is reduced on the premise that the stable and sufficient hydrogen supply amount is ensured. The power consumption of the hydrogen energy supply project in the peak period and the flat period of the power grid is effectively reduced, and the comprehensive energy efficiency and the green power consumption rate of the hydrogen energy supply project are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of hydrogen energy demand resource planning technology, and in particular to a method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response. Background Technology

[0002] Flexible loads refer to equipment or systems that can flexibly adjust their electricity consumption time and amount according to the grid demand. Existing water electrolysis hydrogen production processes consume a large amount of electricity to produce hydrogen. Therefore, in order to save electricity resources and reduce the electricity cost of hydrogen production, the hydrogen production industry usually uses wind-solar coupled hydrogen production systems.

[0003] The wind-solar coupled hydrogen production system includes modules such as new energy power generation, water electrolysis for hydrogen production, hydrogen storage, and hydrogen refueling stations. With the increasing development of renewable energy power generation, the power grid dispatching field is focusing on the development and utilization of renewable energy. In addition to the inherent random fluctuations and large fluctuation amplitudes of new energy power generation, it also has the characteristics of large-scale uncontrollability. When there is an imbalance between power supply and demand in the internal equipment of the hydrogen production system, if the power grid cannot absorb the surplus power, it will lead to energy waste and economic losses. When there is a shortage of new energy power generation, if the power grid price fluctuates greatly, it will lead to an increase in the cost of hydrogen production.

[0004] Therefore, it is crucial to effectively combine the power grid, new energy power generation, and hydrogen production systems based on hydrogen energy demand. The size and matching relationship of hydrogen production capacity, new energy power generation capacity, and hydrogen storage capacity have a significant impact on hydrogen production costs. Therefore, there is an urgent need for a multi-dimensional flexible load feature extraction method based on hydrogen energy demand response. Based on the characteristic data such as the electricity demand of the hydrogen production system, hydrogen production demand, electricity and hydrogen storage capacity, and renewable energy power generation, an optimized control model that responds to the grid signal can be constructed to maximize hydrogen production efficiency and rationalize electricity planning. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a multi-dimensional flexible load feature extraction method based on hydrogen energy demand response.

[0006] To achieve the above objectives, the present invention adopts the following technical solution, comprising the following steps: S1: Obtain the characteristic data of new energy power generation and predict the daily average power generation data based on the data; S2: Obtain the time-of-use electricity price characteristics of the municipal power grid throughout the day, divided into three time periods: peak, flat, and valley. S3: Obtain real-time remaining energy storage capacity characteristic data of energy storage devices; S4: Acquire real-time power, hydrogen production rate, and power consumption characteristics during daily start-up and shutdown periods of the hydrogen production equipment; S5: Acquire real-time operating status and real-time power consumption characteristics of hydrogen delivery equipment; S6: Obtain real-time storage capacity characteristic data of hydrogen storage equipment; S7: Obtain daily hydrogen refueling demand characteristic data; S8: Develop a multi-faceted flexible load control strategy based on the characteristics of new energy power generation, the characteristics of the daily time-of-use electricity price of the municipal power grid, the characteristics of the real-time remaining energy storage capacity of energy storage equipment, the characteristics of the power consumption of hydrogen production equipment, the characteristics of the power consumption of hydrogen transportation equipment, and the characteristics of the real-time storage capacity of hydrogen storage equipment.

[0007] Preferably, in S1, the new energy power generation characteristic data includes wind power generation and photovoltaic power generation characteristic data, with the unit being kWh. Based on the hourly power generation of wind power and photovoltaic power generation equipment under corresponding temperature, wind force, humidity, and light intensity weather conditions, a new energy power generation prediction model for wind power and photovoltaic power generation equipment under corresponding weather conditions is obtained through big data model analysis and training.

[0008] Furthermore, in S3, the energy storage device is a battery pack.

[0009] A further preferred embodiment: In step S4, the hydrogen production equipment includes a rectifier transformer, a rectifier cabinet, an electrolyzer, a gas-liquid separation device, and a purification device.

[0010] As a preferred embodiment of the present invention: in step S5, the hydrogen delivery equipment includes a hydrogen diaphragm compressor, a delivery pipeline, and a hydrogen filling column.

[0011] As a further preferred embodiment of the present invention: in step S6, the hydrogen storage device is a group of multiple 22MPa hydrogen storage cylinders.

[0012] As a further aspect of the present invention: in S7, the daily hydrogen demand characteristic data is used to predict the hydrogen consumption for the next day based on the historical average daily hydrogen consumption and the average daily hydrogen consumption from Monday to Sunday using a hydrogen demand prediction model.

[0013] Based on the aforementioned scheme: In S2, the hydrogen demand for the next day is predicted by the hydrogen demand prediction model, and the power generation of new energy sources for the next day is predicted by the new energy power generation prediction model based on the weather data for the next day. Subsequently, based on the demand for hydrogen, the electrical energy required for the hydrogen production equipment to produce that amount of hydrogen is predicted. Then, the predicted renewable energy generation is subtracted from the required electrical energy to predict the grid's electricity demand for the next day. Finally, through a multi-faceted flexible load control strategy, the equipment in the hydrogen production and hydrogen transportation system is controlled to manage its operating load according to the peak, flat, and valley periods of the power grid.

[0014] Based on the aforementioned scheme: In S8, the multi-dimensional flexible load control strategy includes the following operational scenario classifications: A1: When the intensity of wind / photovoltaic power generation is high and the grid electricity price is at its peak, the system first detects the real-time hydrogen storage capacity of the hydrogen storage equipment. When the hydrogen storage capacity is less than the set minimum value, the system executes the hydrogen production equipment stable operation strategy. When the hydrogen storage capacity is greater than the set minimum value, the system executes the hydrogen production equipment shutdown operation strategy. A2: When the intensity of wind / solar power generation is high and the grid electricity price is in a normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will operate at low power. A3: When wind / solar power generation is high and grid electricity prices are in off-peak hours, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully. A4: When the wind / solar power generation intensity is moderate and the grid electricity price is at its peak, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly; if it is greater than the set minimum value, the hydrogen production equipment will be suspended. A5: When the wind / solar power generation intensity is moderate and the grid electricity price is in the normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly; if it is greater than the set minimum value, the hydrogen production equipment will operate at low power. A6: When the intensity of wind / solar power generation is moderate and the grid electricity price is in the off-peak period, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully. A7: When the intensity of wind / solar power generation is low and the grid electricity price is at its peak, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will be suspended. A8: When the wind / solar power generation intensity is low and the grid electricity price is in the normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will operate at low power. A9: When wind / solar power generation intensity is low and grid electricity prices are in off-peak hours, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully.

[0015] The beneficial effects of this invention are as follows: 1. By using this multi-variable flexible load characteristic extraction method and control strategy, it is possible to effectively filter the fluctuations in new energy power generation and formulate suitable power usage strategies and hydrogen production and supply equipment operation strategies for the entire hydrogen energy supply project. This will effectively reduce the power consumption of the hydrogen energy supply project during peak and off-peak hours while ensuring a stable and sufficient hydrogen supply, thereby effectively improving the overall energy efficiency and green electricity consumption rate of the hydrogen energy supply project.

[0016] 2. This multi-element flexible load characteristic extraction method and control strategy can flexibly switch hydrogen production equipment between full load, stable, low power, and suspension operation modes based on real-time hydrogen storage (min value), new energy power generation intensity, and peak and off-peak electricity prices. This ensures that the hydrogen supply always meets the needs of equipment such as mining heavy trucks and hydrogen refueling stations, avoids the risk of hydrogen supply interruption, and improves the stability of wind-solar coupled hydrogen production system operation.

[0017] 3. By using flexible feature extraction, new energy power generation prediction models, and hydrogen demand prediction models, the high wind-solar coupling hydrogen production system can plan power allocation in advance, offsetting the impact of the randomness and intermittency of wind and solar power on the hydrogen production process. It integrates hydrogen production equipment, hydrogen transportation equipment, and hydrogen storage equipment to achieve energy efficiency management of the entire high wind-solar coupling hydrogen production chain. It concentrates hydrogen production during off-peak electricity price periods to reduce the energy consumption per unit of hydrogen production, and relies on hydrogen storage supply and wind and solar power generation during peak periods to reduce dependence on the external power grid. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the multi-element flexible load feature extraction method based on hydrogen energy demand response proposed in this invention. Figure 2 This is a schematic diagram of the operation steps of the multi-element flexible load feature extraction method based on hydrogen energy demand response proposed in this invention. Figure 3 This is a schematic diagram of the power grid distribution under high power generation intensity of new energy sources, based on the multi-dimensional flexible load feature extraction method proposed in this invention, according to the present invention. Figure 4 This is a schematic diagram of the power grid distribution when considering the power generation intensity in a new energy source based on the multi-dimensional flexible load feature extraction method of hydrogen energy demand response proposed in this invention. Figure 5 This is a schematic diagram of the power grid distribution when the power generation intensity of new energy sources is low, based on the multi-dimensional flexible load feature extraction method proposed in this invention, which is based on hydrogen energy demand response. Detailed Implementation

[0019] The technical solution of the present invention will be further described in detail below with reference to specific embodiments.

[0020] Example 1: A method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response, such as... Figure 1-2 As shown, it includes the following steps: S1: Obtain the characteristic data of new energy power generation and predict the daily average power generation data based on the data; S2: Obtain the time-of-use electricity price characteristics of the municipal power grid throughout the day, divided into three time periods: peak, flat, and valley. S3: Obtain real-time remaining energy storage capacity characteristic data of energy storage devices; S4: Acquire real-time power, hydrogen production rate, and power consumption characteristics during daily start-up and shutdown periods of the hydrogen production equipment; S5: Acquire real-time operating status and real-time power consumption characteristics of hydrogen delivery equipment; S6: Obtain real-time storage capacity characteristic data of hydrogen storage equipment; S7: Obtain daily hydrogen refueling demand characteristic data; S8: Develop a multi-faceted flexible load control strategy based on the characteristics of new energy power generation, the characteristics of the daily time-of-use electricity price of the municipal power grid, the characteristics of the real-time remaining energy storage capacity of energy storage equipment, the characteristics of the power consumption of hydrogen production equipment, the characteristics of the power consumption of hydrogen transportation equipment, and the characteristics of the real-time storage capacity of hydrogen storage equipment.

[0021] In S1, the new energy power generation characteristic data includes wind power generation and photovoltaic power generation characteristic data, with the unit being kWh. Based on the hourly power generation of wind and photovoltaic power generation equipment under corresponding temperature, wind, humidity, and light intensity weather conditions, a new energy power generation prediction model for wind and photovoltaic power generation equipment under corresponding weather conditions is obtained through big data model analysis and training. The new energy power generation prediction model includes a wind power prediction sub-model and a photovoltaic power generation prediction sub-model. The input values ​​of the wind power prediction sub-model are temperature (°C), wind speed (m / s), humidity (%), and historical power generation during the same period (kWh). Then, based on the prediction of the wind power prediction sub-model trained with big data, the model outputs the hourly wind power generation (kWh) for each time period of the day. The input values ​​for the photovoltaic power generation prediction sub-model are temperature (°C), light intensity (W / m²), and humidity (%). Then, based on the predictions of the photovoltaic power generation prediction sub-model trained with big data, the output is the hourly photovoltaic power generation (kWh) for each time period of the day.

[0022] In S3, the energy storage device is a battery pack; In S4, the hydrogen production equipment includes a rectifier transformer, a rectifier cabinet, an electrolyzer, a gas-liquid separation device, and a purification device; In S5, the hydrogen delivery equipment includes a hydrogen diaphragm compressor, a delivery pipeline, and a hydrogen filling column; In S6, the hydrogen storage equipment consists of multiple sets of 22MPa hydrogen storage cylinders; In S7, the daily hydrogen demand characteristic data is used to predict the hydrogen consumption for the next day based on the historical average daily hydrogen consumption and the average daily hydrogen consumption from Monday to Sunday using a hydrogen demand prediction model. In S2, the hydrogen demand for the next day is predicted based on the hydrogen demand prediction model, and the power generation of new energy sources for the next day is predicted based on the weather data for the next day through the new energy power generation prediction model. Subsequently, based on the demand for hydrogen, the electrical energy required for the hydrogen production equipment to produce that amount of hydrogen is predicted. Then, the predicted renewable energy generation is subtracted from the required electrical energy to predict the grid's electricity demand for the next day. Finally, through a multi-faceted flexible load control strategy, the equipment in the hydrogen production and hydrogen transportation system is controlled to manage its operating load according to the peak, flat, and valley periods of the power grid.

[0023] In S8, the multi-dimensional flexible load control strategy includes the following operational scenario classifications: A1: When the intensity of wind / photovoltaic power generation is high and the grid electricity price is at its peak, the system first detects the real-time hydrogen storage capacity of the hydrogen storage equipment. When the hydrogen storage capacity is less than the set minimum value, the system executes the hydrogen production equipment stable operation strategy. When the hydrogen storage capacity is greater than the set minimum value, the system executes the hydrogen production equipment shutdown operation strategy. A2: When the intensity of wind / solar power generation is high and the grid electricity price is in a normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will operate at low power. A3: When wind / solar power generation is high and grid electricity prices are in off-peak hours, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully. A4: When the wind / solar power generation intensity is moderate and the grid electricity price is at its peak, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly; if it is greater than the set minimum value, the hydrogen production equipment will be suspended. A5: When the wind / solar power generation intensity is moderate and the grid electricity price is in the normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly; if it is greater than the set minimum value, the hydrogen production equipment will operate at low power. A6: When the intensity of wind / solar power generation is moderate and the grid electricity price is in the off-peak period, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully. A7: When the intensity of wind / solar power generation is low and the grid electricity price is at its peak, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will be suspended. A8: When the wind / solar power generation intensity is low and the grid electricity price is in the normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will operate at low power. A9: When wind / solar power generation intensity is low and grid electricity prices are in off-peak hours, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully.

[0024] The strategy design for A1-A9 is shown in the table below: Application Example 1: There is currently a wind-solar coupled hydrogen production project integrating new energy power generation, water electrolysis for hydrogen production, hydrogen storage, and a hydrogen refueling station, in which: Wind power component: This project uses one 5MW wind turbine unit. The annual power generation of the wind farm is 11468.3MWh, the annual average equivalent utilization hours are 2293.66h, and the capacity factor is 26.18%.

[0025] Photovoltaic component: This project uses 650Wp monocrystalline silicon photovoltaic modules, with a total of 1540 battery modules installed, a total installed capacity of 1MWp, an average annual power generation of 1637.52MWh, and an average annual equivalent utilization hours of 1635.88h.

[0026] Electrolysis of water to produce hydrogen: 2 sets of 500Nm 3 A water electrolysis hydrogen production unit with a capacity of [number] h includes two rectifier transformers, two rectifier cabinets, and two 500Nm [units / hour]. 3 / h electrolytic cell, 2 sets of 500Nm 3 A gas-liquid separation unit with a capacity of / h and one 1000Nm 3 A purification device with a capacity of / h.

[0027] Hydrogen compression section: 3 sets of 500Nm 3 The hydrogen diaphragm compressor (including one reserved unit) has a discharge pressure of 22MPa.

[0028] Hydrogen storage section: 4 sets of 22MPa hydrogen storage cylinders (including 1 reserved set), each with a water volume of 21m³. 3 .

[0029] Hydrogen filling location: 1 hydrogen filling column and filling vehicle position. After being compressed by a 22MPa compressor, the hydrogen is transported to the hydrogen refueling station through pipeline or filled through the hydrogen filling column.

[0030] This project is a wind-solar coupled hydrogen production project, which adopts water electrolysis hydrogen production technology. The process flow is as follows: water, electricity and other public engineering conditions are input from the outside, and hydrogen and oxygen are generated by ionization in the rectifier cabinet and electrolyzer. After purification, the hydrogen enters the hydrogen buffer tank, and then is compressed by a 22MPa compressor and transported to the hydrogen refueling station through pipeline or filled into a long tube trailer through a hydrogen filling column. The oxygen is led to a high place for on-site discharge. The project is designed to produce hydrogen at a capacity of 1000 Nm³. 3 The project generates hydrogen per hour, which is planned to provide the daily operating hydrogen for 25 hydrogen fuel cell mining heavy trucks, 1 hydrogen fuel cell mining water truck, and 1 hydrogen fuel cell mining forklift in a certain mine.

[0031] When the intensity of new energy power generation is at a high level, based on the data of 11468.3 MWh of annual power generation from wind farms and 1637.52 MWh of annual average power generation from photovoltaic modules, and combined with on-site monitoring and statistical data analysis during actual use, it is concluded that the average power generation of wind power is 2000 kWh / hour and the average power generation of photovoltaic modules is 300 kWh / hour. When the intensity of new energy power generation is at a medium level, the average power generation of wind power is 1600 kWh / hour, and the average power generation of photovoltaic modules is 200 kWh / hour. When the intensity of new energy power generation is low, the average power generation of wind power is 1000 kWh / hour, and the average power generation of photovoltaic modules is 100 kWh / hour. In this project, two 500Nm... 3 The power consumption of an electrolytic cell with a capacity of 4400 kWh / hour is 4400 kWh / hour when running at full load, 3400 kWh / hour when running at stable load, and 2800 kWh / hour when running at low load. 2 sets of 500Nm 3 The power consumption of the gas-liquid separator is 4000 kWh / hour when operating at full load, 3000 kWh / hour when operating at stable load, and 2400 kWh / hour when operating at low load. 1 set 1000Nm 3 The power consumption of the purification unit is 4000 kWh / hour when running at full load, 3100 kWh / hour when running at stable load, and 2500 kWh / hour when running at low load. 3 sets of 500Nm 3 The power consumption of the hydrogen diaphragm compressor is 300 kWh / hour. Therefore, it can be calculated that the power consumption of the hydrogen production equipment in this project is 12400 kWh / hour when running at full load, 9500 kWh / hour when running smoothly, and 7700 kWh / hour when running at low load. The power consumption of the hydrogen transmission equipment is 300 kWh / hour when running. Since mining operations are conducted 24 hours a day, the 25 hydrogen fuel cell mining heavy trucks, 1 hydrogen fuel cell mining water truck, and 1 hydrogen fuel cell mining forklift all need to be refueled with hydrogen in shifts throughout the day. Therefore, the hydrogen production equipment needs to operate according to a multi-functional flexible load control strategy throughout the day to ensure normal production and transportation at the mine. When the time period is in A1 of the multi-dimensional flexible load control strategy, the hydrogen stored in the four 22MPa hydrogen storage cylinder groups can supply the mining equipment for about two hours. Since the peak period lasts for five to six hours throughout the day, when the hydrogen storage is less than the set minimum value two hours after entering the peak period, the system will control the hydrogen production equipment to operate smoothly. The wind power and photovoltaic power generation equipment can provide 2300 kWh / hour of power supply for the hydrogen production equipment and hydrogen transportation equipment (power consumption 9500 kWh / hour) under the smooth operation state. At this time, the remaining 7200 kWh / hour of power needs to be supplied by the power grid during the peak period, which lasts for about three hours. In this embodiment, the minimum value is 50m³.

[0032] When the period is in A2 of the multi-flexible load control strategy, the hydrogen in the hydrogen storage tank group has not been replenished. Therefore, the hydrogen production equipment needs to operate stably to ensure the normal supply of hydrogen. At this time, the wind power and photovoltaic power generation equipment can provide 2300 kWh / hour of electricity supply. The remaining 7200 kWh / hour of electricity needs to be supplied by the power grid during the normal period. When the period is in A3 of the multi-flexible load control strategy, the wind power and photovoltaic power generation equipment can provide 2300 kWh / hour of electricity supply. At this time, the hydrogen production equipment and hydrogen transmission equipment are operating at full load. The remaining 10100 kWh / hour of electricity needs to be supplied by the power grid during the off-peak period to allow the hydrogen production equipment to operate at full load, ensuring the demand for hydrogen while replenishing the hydrogen storage tank group. When the period is in A4 of the multi-dimensional flexible load control strategy, the hydrogen stored in the four 22MPa hydrogen storage cylinder groups can supply the mining equipment for about two hours. Since the normal period lasts for about seven hours, when the hydrogen storage is less than the set min value after two hours of normal period, the system will control the hydrogen production equipment to operate smoothly. At this time, the wind power and photovoltaic power generation equipment can provide 1800 kWh / hour of electricity supply. At this time, the hydrogen production equipment and hydrogen transmission equipment are in a stable operating state. The remaining 7700 kWh / hour of electricity needs to be supplied by the power grid during the normal period, which lasts for about three hours. When the period is in A5 of the multi-flexible load control strategy, the hydrogen in the hydrogen storage tank group has not been replenished. Therefore, the hydrogen production equipment needs to operate stably to ensure the normal supply of hydrogen. At this time, the wind power and photovoltaic power generation equipment can provide 1800 kWh / hour of electricity supply, and the remaining 7700 kWh / hour of electricity needs to be supplied by the power grid during the normal period. When the period is in A6 of the multi-flexible load control strategy, the wind power and photovoltaic power generation equipment can provide 1800 kWh / hour of electricity supply. At this time, the hydrogen production equipment and hydrogen transmission equipment are operating at full load. The remaining 10600 kWh / hour of electricity needs to be supplied by the power grid during the off-peak period to allow the hydrogen production equipment to operate at full load, ensuring the demand for hydrogen while replenishing the hydrogen storage tank group. When the time period is A7 in the multi-dimensional flexible load control strategy, the hydrogen stored in the four 22MPa hydrogen storage cylinder groups can supply the mining equipment for about two hours. Since the peak period lasts for five to six hours throughout the day, when the hydrogen storage is less than the set min value two hours after entering the peak period, the system will control the hydrogen production equipment to operate smoothly. At this time, the wind power and photovoltaic power generation equipment can provide 1100 kWh / hour of electricity supply. At this time, the hydrogen production equipment and hydrogen transmission equipment are in a stable operating state. The remaining 6600 kWh / hour of electricity needs to be supplied by the power grid during the peak period, which lasts for about three hours. When the period is A8 under the multi-flexible load control strategy, the hydrogen in the hydrogen storage tank group has not been replenished. Therefore, the hydrogen production equipment needs to operate stably to ensure a normal supply of hydrogen. At this time, the wind power and photovoltaic power generation equipment can provide 1100 kWh / hour of electricity supply, and the remaining 84000 kWh / hour of electricity needs to be supplied by the power grid during the normal period. When the period is in A9 of the multi-flexible load control strategy, the wind and photovoltaic power generation equipment can provide 1100 kWh / hour of electricity supply. At this time, the hydrogen production equipment and hydrogen transportation equipment are operating at high load. The remaining 11300 kWh / hour of electricity needs to be supplied by the power grid during the off-peak period to allow the hydrogen production equipment to operate at full load, ensuring the demand for hydrogen while replenishing the hydrogen storage tank group.

[0033] like Figure 3-5 As shown in the above application examples, the electricity consumption data obtained after actual application shows that when the new energy power generation equipment is at high power generation intensity, this hydrogen energy supply project can control the grid electricity consumption during peak hours to about 7200 kWh / hour, and the duration is about three hours. During normal hours, the grid electricity consumption is controlled to about 7200 kWh / hour, and during off-peak hours, the electricity consumption is controlled to about 10100 kWh / hour. When the new energy power generation equipment is at medium power generation intensity, this hydrogen energy supply project can control the power grid consumption during peak hours to about 7700 kWh / hour, and the duration is about three hours. During normal hours, the power grid consumption is controlled to about 7700 kWh / hour, and during off-peak hours, the power consumption is controlled to about 10600 kWh / hour. When the new energy power generation equipment is at a low power generation intensity, this hydrogen energy supply project can control the power grid consumption during peak hours to about 6600 kWh / hour, and the duration is about three hours. During normal hours, the power grid consumption is controlled to about 8400 kWh / hour, and during off-peak hours, the power consumption is controlled to about 11300 kWh / hour. This demonstrates that by using this multi-variable flexible load characteristic extraction method and control strategy, we can effectively filter the fluctuations in new energy power generation and formulate suitable power usage strategies and hydrogen production and supply equipment operation strategies for the entire hydrogen energy supply project. This will effectively reduce the electricity consumption of the hydrogen energy supply project during peak and off-peak hours while ensuring a stable and sufficient hydrogen supply, thereby effectively improving the overall energy efficiency and green electricity consumption rate of the hydrogen energy supply project.

[0034] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for extracting the characteristics of multi-element flexible loads based on hydrogen energy demand response, characterized in that, Includes the following steps: S1: Obtain the characteristic data of new energy power generation and predict the daily average power generation data based on the data; S2: Obtain the time-of-use electricity price characteristics of the municipal power grid throughout the day, divided into three time periods: peak, flat, and valley. S3: Obtain real-time remaining energy storage capacity characteristic data of energy storage devices; S4: Acquire real-time power, hydrogen production rate, and power consumption characteristics during daily start-up and shutdown periods of the hydrogen production equipment; S5: Acquire real-time operating status and real-time power consumption characteristics of hydrogen delivery equipment; S6: Obtain real-time storage capacity characteristic data of hydrogen storage equipment; S7: Obtain daily hydrogen refueling demand characteristic data; S8: Develop a multi-faceted flexible load control strategy based on the characteristics of new energy power generation, the characteristics of the daily time-of-use electricity price of the municipal power grid, the characteristics of the real-time remaining energy storage capacity of energy storage equipment, the characteristics of the power consumption of hydrogen production equipment, the characteristics of the power consumption of hydrogen transportation equipment, and the characteristics of the real-time storage capacity of hydrogen storage equipment.

2. The method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response according to claim 1, characterized in that, In S1, the new energy power generation characteristic data includes wind power generation and photovoltaic power generation characteristic data, with the unit being kWh. Based on the hourly power generation of wind and photovoltaic power generation equipment under corresponding temperature, wind, humidity, and light intensity weather conditions, a new energy power generation prediction model for wind and photovoltaic power generation equipment under corresponding weather conditions is obtained through big data model analysis and training.

3. The method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response according to claim 2, characterized in that, In S3, the energy storage device is a battery pack.

4. The method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response according to claim 3, characterized in that, In S4, the hydrogen production equipment includes a rectifier transformer, a rectifier cabinet, an electrolyzer, a gas-liquid separation device, and a purification device.

5. The method for extracting features of multiple flexible loads based on hydrogen energy demand response according to claim 4, characterized in that, In S5, the hydrogen delivery equipment includes a hydrogen diaphragm compressor, a delivery pipeline, and a hydrogen filling column.

6. The method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response according to claim 5, characterized in that, In S6, the hydrogen storage equipment consists of multiple sets of 22MPa hydrogen storage cylinders.

7. The method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response according to claim 6, characterized in that, In step S7, the daily hydrogen demand characteristic data is used to predict the hydrogen consumption for the next day based on the historical average daily hydrogen consumption and the average daily hydrogen consumption from Monday to Sunday using a hydrogen demand prediction model.

8. The method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response according to claim 6, characterized in that, In S2, the hydrogen demand for the next day is predicted based on the hydrogen demand prediction model, and the power generation of new energy sources for the next day is predicted based on the weather data for the next day through the new energy power generation prediction model. Subsequently, based on the demand for hydrogen, the electrical energy required for the hydrogen production equipment to produce that amount of hydrogen is predicted. Then, the predicted renewable energy generation is subtracted from the required electrical energy to predict the grid's electricity demand for the next day. Finally, through a multi-faceted flexible load control strategy, the equipment in the hydrogen production and hydrogen transportation system is controlled to manage its operating load according to the peak, flat, and valley periods of the power grid.

9. The method for extracting the characteristics of multiple flexible loads based on hydrogen energy demand response according to claim 7, characterized in that, In S8, the multi-dimensional flexible load control strategy includes the following operational scenario classifications: A1: When the intensity of wind / photovoltaic power generation is high and the grid electricity price is at its peak, the system first detects the real-time hydrogen storage capacity of the hydrogen storage equipment. When the hydrogen storage capacity is less than the set minimum value, the system executes the hydrogen production equipment stable operation strategy. When the hydrogen storage capacity is greater than the set minimum value, the system executes the hydrogen production equipment shutdown operation strategy. A2: When the intensity of wind / solar power generation is high and the grid electricity price is in a normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will operate at low power. A3: When wind / solar power generation is high and grid electricity prices are in off-peak hours, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully. A4: When the wind / solar power generation intensity is moderate and the grid electricity price is at its peak, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly; if it is greater than the set minimum value, the hydrogen production equipment will be suspended. A5: When the wind / solar power generation intensity is moderate and the grid electricity price is in the normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly; if it is greater than the set minimum value, the hydrogen production equipment will operate at low power. A6: When the intensity of wind / solar power generation is moderate and the grid electricity price is in the off-peak period, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully. A7: When the intensity of wind / solar power generation is low and the grid electricity price is at its peak, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will be suspended. A8: When the wind / solar power generation intensity is low and the grid electricity price is in the normal range, if the hydrogen storage is less than the set minimum value, the hydrogen production equipment will operate smoothly. If the storage is greater than the set minimum value, the hydrogen production equipment will operate at low power. A9: When wind / solar power generation intensity is low and grid electricity prices are in off-peak hours, the hydrogen production equipment should be operated at full load to allow the hydrogen storage equipment to store hydrogen fully and the electrical energy storage equipment to store electrical energy fully.

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