Offshore wind power energy storage configuration method

Abstract

An offshore wind power energy storage configuration method belongs to the technical field of offshore wind power energy storage, and comprises the following steps: firstly building a wind power plant and an energy storage station and sharing hydrogen resources, calculating the energy storage capacity according to factors such as electric hydrogen production power, determining the capacity of energy storage equipment according to a power ratio, and obtaining an energy storage configuration ratio according to predicted power generation power; and finally, when the predicted power is not matched with the actual power, peak regulation and frequency modulation are carried out by an energy storage station, and hydrogen resource management energy is shared. According to the method, multiple factors are comprehensively considered, the energy storage demand is accurately calculated, and the energy storage and the wind power plant are optimized and coordinated through accurate prediction and effective control. The energy utilization efficiency is improved through hydrogen resource sharing, multiple energy storage and power generation modes are complementary, the capacity of the system for coping with complex working conditions is enhanced, and the stability, reliability and economical efficiency of the offshore wind power system are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of offshore wind power energy storage, and in particular relates to an offshore wind power energy storage configuration method. Background Art

[0002] Under the general trend of global energy transformation, offshore wind power has become a key development direction in the field of renewable energy due to its abundant resource reserves and relatively stable wind energy environment. However, offshore wind power faces many technical difficulties in practical applications, which seriously restrict its further large-scale and efficient access to the power system and stable operation.

[0003] At present, some energy storage technologies have been applied or studied to address the problem of unstable offshore wind power. Traditional battery energy storage systems are one of the more common solutions. Battery energy storage has certain advantages in regulating power fluctuations in a short period of time. For example, lithium-ion batteries can quickly respond to changes in wind power and switch between charge and discharge within seconds to minutes to balance power imbalances in local periods. However, battery energy storage also has obvious limitations. First, its energy density is relatively limited. When dealing with long-term and large-scale energy storage needs, large battery packs are often required, which not only increases the construction cost of the system, but also occupies a large amount of offshore space resources. Secondly, the service life of the battery is greatly affected by the number of charge and discharge cycles and environmental factors. Frequent deep charge and discharge operations will accelerate the attenuation of battery performance, resulting in high maintenance costs in the later stage, and the need to replace the battery regularly, further increasing operating costs and environmental pressures.

[0004] In addition to battery energy storage, some other energy storage technologies such as pumped storage have certain applications in onshore wind power storage, but due to the special geographical environment and construction conditions at sea, it is difficult to implement them on a large scale in offshore wind farms. Although the pure hydrogen energy storage system has potential in terms of energy storage capacity and energy density, its energy conversion efficiency still needs to be improved, especially in the process of producing hydrogen from electricity, there is a large energy loss, and the storage, transportation and utilization of hydrogen require complex infrastructure and safety measures. The current technical level is still difficult to achieve efficient, safe and economical large-scale application.

[0005] In terms of wind power forecasting, although existing forecasting methods have made some progress, their accuracy still needs to be improved. Traditional forecasting methods based on physical models, such as models built based on meteorological data and wind turbine aerodynamic principles, are difficult to accurately simulate the rapid changes in wind speed and direction and the nonlinear relationship between them and wind turbine power generation under complex marine meteorological conditions. Data-driven forecasting models, such as neural networks, can handle complex nonlinear data, but they are too dependent on data and require a large amount of historical data for training. In addition, when faced with missing data, anomalies, or new meteorological conditions, the model's generalization ability is insufficient and the forecast error is large.

[0006] In addition, the existing offshore wind power energy storage system has deficiencies in overall energy management and coordinated operation. In most cases, the coordination between the energy storage system and the wind farm is not close and intelligent enough, and there is a lack of comprehensive optimization scheduling strategies for various energy storage forms (such as battery energy storage and hydrogen energy storage) and wind farm power generation. For example, under different wind power output scenarios and electricity demand conditions, the charging and discharging processes of battery energy storage and hydrogen energy storage cannot be effectively coordinated, resulting in a waste of energy storage resources or the inability to give full play to the energy storage system's smoothing effect on wind power fluctuations, which in turn affects the stability, reliability and economy of the entire offshore wind power system.

[0007] In summary, the main problem solved by the present invention is: how to optimize the comprehensive management of energy storage and wind farm energy, and solve the problems of insufficient coordination between existing energy storage and wind farms and lack of scheduling strategies. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide an offshore wind power energy storage configuration method, which utilizes hydrogen resource sharing to improve energy utilization efficiency, complements multiple energy storage and power generation methods, enhances the system's ability to cope with complex working conditions, and significantly improves the stability, reliability and economy of the offshore wind power system.

[0009] In order to solve the above technical problems, the technical solution adopted by the present invention is: A method for configuring offshore wind power energy storage, comprising the following steps: Step 1: Build a wind farm and an energy storage station so that the energy storage station and the wind farm can share hydrogen resources. At the same time, the energy storage station, wind farm, and fuel cell station are connected through a transportation hub, and the energy storage station is configured in the same proportion as the wind farm. Step 2: Calculate the energy storage capacity required for hydrogen production based on the power, energy and efficiency of hydrogen production; Step 3: According to the power ratio relationship, the capacity of the energy storage device is obtained; the power ratio includes the ratio of wind power to energy storage power, the ratio of hydrogen fuel cell power to energy storage power, and the ratio of electric hydrogen production power to energy storage power; Step 4: Determine the energy storage configuration ratio based on the predicted power generation; Step 5: Predict the power generation of the wind farm; Step 6: When the predicted power of offshore wind power does not match the actual power, use the energy storage station to adjust the peak or frequency to increase the accuracy of the prediction, and make up for the prediction deviation through the energy storage station's consumption or output. The energy storage station and wind farm share hydrogen resources to achieve comprehensive energy management.

[0010] Preferably, in step 1, the energy storage station configuration is in the same proportion as the wind farm, which means that the configuration parameters of the energy storage station and the corresponding parameters of the wind farm are set in the same proportional relationship; the configuration parameters include capacity and power.

[0011] Preferably, the calculation process of step 2 is as follows: According to power Definition, power is the energy per unit time, that is: , For electric hydrogen production : ,in : Electric hydrogen production time is the time required to complete the electric hydrogen production process; : Electricity-to-hydrogen power, which indicates the amount of electricity used to produce hydrogen per unit time; : The energy required for hydrogen production by electricity is the total energy required to complete the hydrogen production process; So ; Due to the efficiency problem of the electric hydrogen production process, the energy actually required to be obtained from the energy storage device is greater than the energy required for theoretical hydrogen production; according to the efficiency calculation formula: , For the hydrogen production process, ,in, : The efficiency of hydrogen production from electricity is a dimensionless coefficient that indicates the efficiency of converting electrical energy into the chemical energy of hydrogen; Indicates the output energy of hydrogen produced by electricity; so ; The energy storage capacity required for hydrogen production is In fact, it is the capacity of the energy storage equipment that provides energy for the hydrogen production process, that is, ; The calculation formula for the energy storage capacity required for hydrogen production by electricity is: ; :The energy storage capacity required for hydrogen production from electricity is used to measure the capacity of the energy storage equipment required to provide energy for the hydrogen production process from electricity.

[0012] Preferably, in step 3, the ratio of wind power to energy storage power is as follows: Assume that wind power reaches its maximum value at a certain moment , and the charging power limit of the energy storage device is , the power ratio is set as ,in is a coefficient less than or equal to 1, determined according to the performance of the energy storage device and system requirements; During the discharge process, when the wind power is lower than the load demand, the energy storage device needs to discharge to supplement the power; assuming the load demand power is , wind power is , the discharge power of the energy storage device is , the power ratio relationship is expressed as: ; According to the power ratio relationship and the wind power prediction curve, the charging and discharging power required by the energy storage device in different time periods is calculated, and then the capacity of the energy storage device is obtained: by integrating the wind power prediction curve, the total amount of energy that needs to be stored in a certain period of time is obtained. , combined with the charging and discharging efficiency of the energy storage device , calculate the capacity of the energy storage device ; in, : The maximum value of wind power at a certain moment; : Charging power limit of energy storage equipment; : A coefficient less than or equal to 1, determined according to the performance of the energy storage equipment and system requirements, used to express the proportional relationship between the peak wind power and the energy storage charging power; : Load demand power; : Wind power; : Discharge power of energy storage equipment; : The total amount of energy that needs to be stored within a certain period of time; : Charging and discharging efficiency of energy storage equipment; : Energy storage equipment capacity.

[0013] Preferably, in step 3, the ratio of hydrogen fuel cell power to energy storage power is as follows: Hydrogen fuel cells play the role of supplementing power and regulating energy in the system. When the wind power forecast deviation is large or the energy storage device is insufficient, the hydrogen fuel cell needs to output power. Assume that the rated power of the hydrogen fuel cell is , the power of the energy storage device is , in order to ensure the stability of the system, the power ratio is set as: , in It is a coefficient determined based on the system reliability requirements and the performance of the hydrogen fuel cell; When the energy storage device is in a low power state, the hydrogen fuel cell needs to output enough power to meet the load demand, and it may also be necessary to charge the energy storage device; at this time, the power ratio relationship needs to consider the power generation efficiency of the hydrogen fuel cell. , Charging efficiency of energy storage equipment and load power requirements ; Get the relationship , through this relationship and known system parameters, the reasonable ratio of hydrogen fuel cell power and energy storage device power is further determined, thereby calculating the capacity of the energy storage device; in, : Rated power of hydrogen fuel cell; : Power of energy storage equipment; : A coefficient determined based on system reliability requirements and the performance of hydrogen fuel cells, used to express the proportional relationship between the power of hydrogen fuel cells and the power of energy storage equipment; : Power generation efficiency of hydrogen fuel cells; : Charging efficiency of energy storage equipment.

[0014] Preferably, in step 3, the ratio of the power of hydrogen production by electricity to the power of energy storage is as follows: The process of producing hydrogen by electricity consumes electricity, which comes from wind power. Assume that the power of producing hydrogen by electricity is , the output power of the energy storage device is , the power ratio relationship is expressed as: , in It is a coefficient determined based on the efficiency of hydrogen production from electricity and hydrogen demand factors; The energy efficiency of hydrogen production from electricity is known to be , the hydrogen energy required to be produced within a certain period of time is , then the energy required for hydrogen production is ; Based on the power of hydrogen production and the energy required , and the output power limit of the energy storage device, calculate the energy and time that the energy storage device needs to provide during the hydrogen production process, and then derive the capacity of the energy storage device: , in is the time period of hydrogen production from electricity; : Electricity-to-hydrogen power; : Output power of energy storage equipment; : A coefficient determined based on the efficiency of hydrogen production from electricity and hydrogen demand factors, used to express the proportional relationship between the power of hydrogen production from electricity and the output power of the energy storage device; : Energy efficiency of hydrogen production from electricity; : The amount of hydrogen energy that needs to be produced within a certain period of time; : The time period of hydrogen production by electricity; : Energy storage equipment capacity.

[0015] Preferably, the sub-steps of step 4 are as follows: (1) Perform short-term power forecasting, including hourly power forecasting and minute-level power forecasting; Prediction and calculation process of hourly power forecast: Based on historical data and real-time meteorological information, time series analysis methods or machine learning algorithms are used to predict the power generation of offshore wind farms in the next 1-6 hours; Analyze power fluctuations based on the predicted hourly power curve; if it is predicted that wind power will rise or fall significantly within the next hour, in order to stabilize output, the energy storage configuration ratio should be able to store excess energy when power rises and release sufficient energy when power drops; The calculation method is: Assume the predicted power change is The charging and discharging efficiencies of energy storage are and , then the energy storage configuration capacity or , the energy storage configuration ratio is based on the rated power of the wind farm Determine the proportionality factor ; in, : predicted hourly power change, : Charging efficiency of energy storage equipment; : Discharge efficiency of energy storage equipment; : Energy storage configuration capacity based on hourly power forecast; : Rated power of wind farm; : Hourly energy storage configuration ratio coefficient; Prediction and calculation process of minute-level power forecast: Use more sophisticated meteorological monitoring data and advanced forecasting models to predict power generation changes within the next 10-60 minutes; the energy storage configuration ratio needs to consider the rapid response capability of the energy storage equipment, assuming that the rapid response power is , minute-level energy storage configuration ratio coefficient At the same time, the energy storage capacity must be combined to ensure that the power output can be maintained for a certain period of time. The energy storage capacity is calculated according to the energy demand. , and further determine the proportional relationship with the rated power of the wind farm; in, : Rapid response power of energy storage equipment; : Minute-level energy storage configuration ratio coefficient; : Energy storage configuration capacity based on minute-level power forecast; : The number of minutes to maintain power output; (2) Conduct medium- and long-term power forecasts, including daily and weekly power forecasts; The prediction and calculation process of daily power forecast: Taking into account the historical daily power data, weather forecast and seasonal factors, multiple regression analysis or hybrid prediction model is used to predict the power curve of the wind farm in the next day; the daily power data of the same season and similar weather conditions in the past few years are analyzed, and the power range of the next day is predicted in combination with the current weather forecast information; according to the daily power forecast results, the energy storage configuration ratio is determined to balance the power supply and demand of the whole day; if the wind power is predicted to be higher during the day and lower at night, and the electricity demand during the day is relatively stable, the energy storage configuration should be able to store excess electricity during the day for use at night; assuming that the average excess power during the day is , the average power gap at night is , the charge-discharge cycle efficiency of energy storage is , then the energy storage configuration capacity , , take the larger capacity value as the basis for energy storage configuration, and the daily energy storage configuration ratio coefficient ; in, : average excess power during the day; : Average power gap at night; : Charge and discharge cycle efficiency of energy storage equipment; : Daytime energy storage configuration capacity based on daily power forecast; : Nighttime energy storage configuration capacity based on daily power forecast; : Charging time during the day; : Night discharge time; : Daily energy storage configuration ratio coefficient; The prediction and calculation process of weekly power forecast: forecast based on longer historical data, long-term weather forecast and energy demand trend in the surrounding areas of offshore wind farms; analyze the weekly power generation change patterns in different seasons in the past, combine the weather forecast for the next week and the weekly change trend of industrial and residential electricity consumption in the region, and predict the approximate range and fluctuation of the wind farm's power generation in the next week; for weekly power forecast, the energy storage configuration ratio is mainly considered to deal with the intermittent and volatility of wind power within a week, as well as the coordination with other energy supplies; if it is predicted that the wind power is low on certain days and the electricity demand in the region is high, the energy storage should be able to store enough energy to make up for the shortfall when the wind power is sufficient; set the maximum power gap within the week to be , energy storage configuration capacity , weekly energy storage configuration ratio coefficient ; in, : The maximum power gap within the week; : Energy storage configuration capacity based on weekly power forecast; : The total time that power gap may occur; : Weekly energy storage configuration ratio coefficient; Through the above prediction and analysis at different time scales, a more reasonable energy storage configuration ratio is comprehensively obtained to achieve the optimal configuration of the offshore wind power energy storage system, which is used to improve the stability, reliability and economy of offshore wind power.

[0016] Preferably, the sub-steps of step 5 are as follows: (1) Determine wind power: Sensors installed on each wind turbine in the offshore wind farm collect wind speed, wind direction, wind turbine blade speed, and cabin temperature parameters in real time. At the same time, collect meteorological data of the sea area where the wind farm is located. The meteorological data includes large-scale meteorological information provided by surrounding meteorological stations and local meteorological changes monitored by offshore buoys. Based on the collected data, the established wind power calculation model is used to determine the current wind power. (2) Predicting energy storage output: Monitor the energy storage system in real time to obtain the current power, charge and discharge current, and voltage parameters of the energy storage equipment; at the same time, monitor the health status of the energy storage system, including the change in the internal resistance and temperature distribution of the battery; the health status will affect the charge and discharge efficiency and power output capacity of the energy storage system; (3) Establish a prediction model: Establish an energy storage output prediction model based on the historical operation data and current state parameters of the energy storage system; use time series analysis methods to analyze the historical changes in the output of the energy storage system, and combine the current state data to predict the future energy storage output; if it is found that the energy storage system's discharge power shows a certain periodic change in certain time periods in the past when the power is within a specific range and the ambient temperature is stable, then use the ARIMA model to capture this periodicity and predict the future discharge power change trend; (4) Forecasting wind power Obtain longer-term weather forecast data, including wind speed, wind direction, temperature, and air pressure for the next few hours or even days; Combine weather forecast data with geographic information of the sea area where the wind farm is located; geographic information will affect the flow of wind, thereby changing the actual wind speed and direction at the wind turbine; (5) Optimize the prediction model: Build a wind power prediction model based on historical wind power data and integrated meteorological forecast data; use machine learning algorithms to continuously optimize the prediction model; (6) Based on the predicted wind power and energy storage output, formulate a charging and discharging control strategy for energy storage; when the predicted wind power is greater than the current power demand and the energy storage system is not fully charged, start the energy storage charging process: set a charging threshold, when the difference between wind power and power demand exceeds the threshold and the energy storage SOC is lower than the set upper limit, control the energy storage system to charge at an appropriate charging power; when the predicted wind power is less than the power demand, if the energy storage system has sufficient power, start the energy storage discharging process; determine the discharge threshold, when the difference between power demand and wind power exceeds the threshold and the energy storage SOC is higher than the set lower limit, control the energy storage system to discharge; the discharge power also needs to be adjusted according to the capacity and current status of the energy storage system to meet the power demand and maintain the stable operation of the system.

[0017] Preferably, the sub-steps of step 6 are: (1) The strategies for dealing with the mismatch between predicted power and actual power are as follows: establish a real-time power monitoring system to accurately measure and record the predicted power and actual power of offshore wind power; install high-precision power sensors on the transmission lines of wind farms to collect power data at a high frequency; compare the predicted power curve with the actual power curve to calculate the deviation between the two; when the deviation exceeds a preset threshold, it is determined that a power mismatch has occurred; When the actual offshore wind power is higher than the predicted power and the grid’s absorption capacity is limited, the energy storage station enters the charging peak load mode. The energy storage station receives excess wind power at an appropriate charging power based on the difference between the actual power and the predicted power and its own charging capacity. When the actual power of offshore wind power is lower than the predicted power and the power demand is large, the energy storage station discharges to load the peak. The energy storage station outputs electric energy to supplement the power grid or power-consuming equipment according to the size of the power gap and its own discharge capacity. The energy storage station participates in the frequency regulation of the power grid through rapid response control. When the power fluctuation of offshore wind power causes the frequency of the power grid to change, the energy storage station quickly adjusts the charging and discharging power. (2) The strategy of sharing hydrogen resources between energy storage stations and wind farms to achieve comprehensive energy management is as follows: the excess electricity generated by wind farms can be used to produce hydrogen through water electrolysis, and the produced hydrogen is stored in a hydrogen storage facility connected to the energy storage station; the hydrogen fuel cell in the energy storage station uses the stored hydrogen to generate electricity; during periods of excess wind power, the water electrolysis hydrogen production equipment operates at rated power and stores the produced hydrogen; when wind power is insufficient or electricity demand is peak, the hydrogen fuel cell uses the stored hydrogen to generate electricity and outputs electricity to supplement the power grid or the wind farm's internal power system; the capacity and pressure parameters of the hydrogen storage facility need to be reasonably designed based on the wind farm's power generation scale, the energy demand of the energy storage station, and the production and consumption rate of hydrogen; The energy management system is used to achieve the coordinated management of hydrogen resources between wind farms and energy storage stations. The energy management system is used to optimize the production, storage and use strategies of hydrogen based on wind power forecasts, actual power monitoring, energy storage station status and electricity demand information. Sharing hydrogen resources enables the effective use of excess electricity from wind farms, reducing wind curtailment. At the same time, energy storage stations use hydrogen fuel cells to flexibly supplement electricity in different energy supply and demand scenarios, improving the overall utilization efficiency of the entire energy system. The coordinated operation of energy storage stations and wind farms based on the sharing of hydrogen resources enhances the stability and reliability of the entire energy system. When faced with large fluctuations in wind power, grid failures or extreme weather conditions, the system can ensure a stable supply of electricity by switching and complementing a variety of energy storage and power generation methods.

[0018] An offshore wind power energy storage configuration optimization system adopts the offshore wind power energy storage configuration method.

[0019] The present invention can achieve the following beneficial effects: 1. The present invention can ensure that the capacity of energy storage equipment is highly adapted to the needs of wind farms through detailed power ratio relationships, such as precise matching of wind power and energy storage power, hydrogen fuel cell power and energy storage power, and electric hydrogen production power and energy storage power, as well as reasonable energy storage configuration ratios derived from predicted power generation at different time scales (hours, minutes, days, and weeks), effectively respond to various changes in wind power, and improve the efficiency of energy storage and release.

[0020] 2. Comprehensively apply a variety of advanced technologies to predict wind farm power generation, including integrating multi-source data (meteorological information, wind turbine parameters, geographic information, etc.) and using a variety of prediction models (such as time series analysis, machine learning algorithms, etc.). When the prediction is inaccurate, use energy storage stations to quickly adjust the peak and frequency, so that the system can respond to power fluctuations in a timely manner, ensure stable power output, reduce the impact on the power grid, and enhance the reliability of system operation.

[0021] 3. The energy storage station and the wind farm share hydrogen resources, realizing the coordinated management of hydrogen production, storage and utilization. Hydrogen is produced and stored when there is excess wind power, and hydrogen fuel cells are used to generate electricity to supplement when there is insufficient power or peak electricity demand. This not only makes full use of excess wind power and reduces wind abandonment, but also improves the flexibility and adaptability of the entire energy system in different supply and demand scenarios through hydrogen storage over a long period of time, and improves the comprehensive efficiency of energy utilization.

[0022] 4. The combination of multiple energy storage and power generation methods (battery energy storage, hydrogen energy storage, wind farm power generation) and intelligent switching complement each other, so that the system can still guarantee a stable supply of electricity in the face of complex working conditions such as large fluctuations in wind power, power grid failures or extreme weather. For example, when the power grid fails, the hydrogen fuel cell of the energy storage station can independently supply power to important equipment inside the wind farm, avoiding the shutdown of the wind farm, and improving the survivability and overall stability of the system in extreme situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0024] The preferred solution is Figure 1 As shown, a method for configuring offshore wind power energy storage comprises the following steps: Step 1: Build a wind farm and an energy storage station so that the energy storage station and the wind farm can share hydrogen resources. At the same time, connect the energy storage station, wind farm, and fuel cell station through a transportation hub, and the energy storage station should be configured in the same proportion as the wind farm.

[0025] Step 2: Calculate the energy storage capacity required for hydrogen production based on the power, energy and efficiency of hydrogen production.

[0026] Step 3: Obtain the capacity of the energy storage device according to the power ratio relationship. The power ratio includes the ratio of wind power to energy storage power, the ratio of hydrogen fuel cell power to energy storage power, and the ratio of electric hydrogen production power to energy storage power.

[0027] Step 4: Determine the energy storage configuration ratio based on the predicted power generation.

[0028] Step 5: Predict the power generation of the wind farm.

[0029] Step 6: When the predicted power of offshore wind power does not match the actual power, use the energy storage station to adjust the peak or frequency to increase the accuracy of the prediction, and make up for the prediction deviation through the energy storage station's consumption or output. The energy storage station and wind farm share hydrogen resources to achieve comprehensive energy management.

[0030] Furthermore, in step 1, the energy storage station configuration is in the same proportion as the wind farm, which means that the configuration parameters of the energy storage station and the corresponding parameters of the wind farm are set in the same proportion. The configuration parameters include capacity and power.

[0031] Furthermore, the calculation process of step 2 is as follows: According to the definition of power, power is the energy per unit time, that is , for the power of hydrogen production, ,So . Due to the efficiency problem of the electric hydrogen production process, the energy actually required from the energy storage device is greater than the energy required for theoretical hydrogen production (because part of the energy will be lost during the conversion process). According to the efficiency calculation formula: , For the hydrogen production process, , so . The energy storage capacity required for hydrogen production is In fact, it is the capacity of the energy storage equipment that provides energy for the hydrogen production process, that is, . The calculation formula for the energy storage capacity required for hydrogen production by electricity is: . in, : Electricity-to-hydrogen power, measured in watts, represents the amount of electricity used to produce hydrogen per unit time. : The energy required for hydrogen production from electricity, measured in joules, is the total energy required to complete the hydrogen production process.

[0032] : The efficiency of hydrogen production from electricity is a dimensionless coefficient that represents the efficiency of converting electrical energy into the chemical energy of hydrogen.

[0033] : The energy storage capacity required for hydrogen production from electricity, expressed in watt-hours or other energy units, is used to measure the capacity of the energy storage equipment required to provide energy for the hydrogen production process from electricity. : Electricity-generated hydrogen time, in hours, is the time required to complete the electricity-generated hydrogen process.

[0034] Furthermore, in step 3, the ratio of wind power to energy storage power is as follows: In offshore wind power systems, wind power changes dynamically and is affected by natural factors such as wind speed and wind direction. In order to ensure that energy storage equipment can effectively store excess energy generated by wind power, it is necessary to consider the peak and valley values ​​of wind power.

[0035] For example, suppose that wind power reaches its maximum value at a certain moment , and the charging power limit of the energy storage device is , the power ratio is set as ,in is less than or equal to The coefficient is determined according to the performance of the energy storage device and the system requirements. This coefficient takes into account factors such as the efficiency and safety limits of the energy storage device during the charging process. Similarly, during the discharge process, when the wind power is lower than the load demand, the energy storage device needs to discharge to supplement the power. Assume that the load demand power is , wind power is , the discharge power of the energy storage device is , the power ratio relationship is expressed as (when According to these power ratio relationships and the wind power prediction curve, the charging and discharging power required by the energy storage device in different time periods is calculated, and then the capacity of the energy storage device is obtained. For example, by integrating the wind power prediction curve, the total amount of energy that needs to be stored in a certain period of time is obtained. , combined with the charging and discharging efficiency of the energy storage device , calculate the capacity of the energy storage device .

[0036] : The maximum value of wind power at a certain moment, in watts.

[0037] : Charging power limit of energy storage device, in watts. : one is less than or equal to The coefficient is determined according to the performance of the energy storage equipment and system requirements, and is used to express the proportional relationship between the peak wind power and the energy storage charging power.

[0038] : Load power demand, in watts.

[0039] : Wind power, in watts.

[0040] : The discharge power of the energy storage device, in watts.

[0041] : The total amount of energy that needs to be stored in a certain period of time, measured in joules.

[0042] : The charging and discharging efficiency of energy storage equipment (here, charging and discharging efficiency are uniformly represented. If there is a distinction in actual application, they can be defined as and ). : The capacity of energy storage equipment, in watt-hours or other energy units.

[0043] Furthermore, in step 3, the ratio of hydrogen fuel cell power to energy storage power is as follows: Hydrogen fuel cells play a role in supplementing power and regulating energy in the system. When the wind power forecast deviation is large or the energy storage device is insufficient, the hydrogen fuel cell needs to output power. Assume that the rated power of the hydrogen fuel cell is , the power of the energy storage device is In order to ensure the stability of the system, the power ratio relationship can be set as ,in It is a coefficient determined based on the system reliability requirements and the performance of the hydrogen fuel cell. For example, when the energy storage device is in a low power state, the hydrogen fuel cell needs to output enough power to meet the load demand, and it may also need to charge the energy storage device. At this time, the power ratio relationship needs to consider the power generation efficiency of the hydrogen fuel cell. , Charging efficiency of energy storage equipment and load power requirements . We can get the relationship Through this relationship and known system parameters, the reasonable ratio of hydrogen fuel cell power and energy storage device power can be further determined, thereby calculating the capacity of the energy storage device.

[0044] : The rated power of the hydrogen fuel cell, in watts.

[0045] : The power of the energy storage device in watts.

[0046] : A coefficient determined based on system reliability requirements and the performance of hydrogen fuel cells, used to express the proportional relationship between hydrogen fuel cell power and energy storage device power. : Power generation efficiency of hydrogen fuel cells. : Charging efficiency of energy storage equipment.

[0047] Furthermore, in step 3, the ratio of the power of hydrogen production from electricity to the power of energy storage is as follows: The process of producing hydrogen by electricity consumes electricity, which can come from wind power. Assume that the power of producing hydrogen by electricity is , the output power of the energy storage device is (used to provide the electricity required for hydrogen production), the power ratio relationship can be expressed as ,in It is a coefficient determined by factors such as the efficiency of hydrogen production from electricity and the demand for hydrogen. The power of hydrogen production from electricity is also related to the capacity of the energy storage device. For example, the energy efficiency of hydrogen production from electricity is known to be , the hydrogen energy required to be produced within a certain period of time is , then the energy required for hydrogen production is . According to the power of hydrogen production and the energy required , and the output power limit of the energy storage device, the energy and time that the energy storage device needs to provide during the hydrogen production process can be calculated, and then the capacity of the energy storage device can be obtained. ,in It is the time period for producing hydrogen from electricity.

[0048] : Electricity-to-hydrogen power, in watts. : The output power of the energy storage device, in watts.

[0049] : A coefficient determined based on factors such as the efficiency of hydrogen production from electricity and hydrogen demand, used to express the proportional relationship between the power of hydrogen production from electricity and the output power of the energy storage equipment.

[0050] : Energy efficiency of hydrogen production from electricity.

[0051] : The amount of hydrogen energy required to be produced within a certain period of time, in joules.

[0052] : The time period of hydrogen production by electricity, in hours. : The capacity of energy storage equipment, in watt-hours or other energy units.

[0053] Furthermore, the sub-steps of step 4 are as follows: 1. Short-term power forecast 1. Hourly power forecast: Forecast and calculation process: Based on historical data and real-time meteorological information (such as wind speed, wind direction, air pressure, etc.), use time series analysis methods (such as ARIMA model) or machine learning algorithms (such as neural network) to predict the power generation of offshore wind farms in the next 16 hours. For example, collect wind speed and power generation data in the same time period (such as 9:10 am) in the past few weeks or even months, and establish a model to predict the power generation trend in the next hour from the current moment. According to the predicted hourly power curve, analyze the power fluctuation. If it is predicted that the wind power will rise or fall significantly in the next hour, for example, it is expected to rise from 50MW to 80MW or fall to 30MW. In order to stabilize the output, the energy storage configuration ratio should be able to store excess energy when the power rises (such as the energy storage capacity needs to be able to store an energy increment of about 30MW), and release enough energy when the power decreases (such as providing a 20MW power supplement). The calculation method can be: Let the predicted power change be The charging and discharging efficiencies of energy storage are and , then the energy storage configuration capacity (while charging) or (When discharging), the energy storage configuration ratio can be based on the rated power of the wind farm Determine, such as the proportionality factor . : The predicted hourly power change in watts.

[0054] : Charging efficiency of energy storage equipment.

[0055] : Discharge efficiency of energy storage equipment.

[0056] : Energy storage configuration capacity based on hourly power forecast, in watt-hours or other energy units.

[0057] : Rated power of the wind farm, in watts.

[0058] : Hourly energy storage configuration ratio coefficient.

[0059] 2. Minute-level power prediction: Prediction and calculation process: Use more sophisticated meteorological monitoring data and advanced prediction models (such as the LSTM model in deep learning, which has good processing capabilities for time series data) to predict changes in power generation in the next 10-60 minutes. For example, by installing high-precision meteorological sensors near offshore wind farms, data such as wind speed and wind direction are collected every 1 minute, and historical data is input into the LSTM model to predict power changes in the next 30 minutes. For minute-level predictions, focus on rapid fluctuations in power to cope with instantaneous changes in power generation caused by gusts. If it is predicted that wind power may drop rapidly from 60MW to 40MW within 2 minutes in the next 30 minutes, energy storage should be able to provide 20MW of power support in a short time. At this time, the energy storage configuration ratio needs to take into account the rapid response capability of the energy storage equipment. Suppose the rapid response power is , minute-level energy storage configuration ratio coefficient: , At the same time, the energy storage capacity must be combined to ensure that the power output can be maintained for a certain period of time, such as calculating the energy storage capacity based on energy demand. is the number of minutes that power output needs to be maintained), and further determines the proportional relationship with the rated power of the wind farm. : The rapid response power of the energy storage device, in watts. : Minute-level energy storage configuration ratio coefficient.

[0060] : Energy storage configuration capacity based on minute-level power forecast, in watt-hours or other energy units.

[0061] : Number of minutes required to maintain power output.

[0062] 2. Medium and long-term power forecast 1. Daily power forecast: Forecast and calculation process: Comprehensively consider historical daily power generation data, weather forecasts (including forecasts of meteorological elements such as wind speed, wind direction, and temperature for the next 24 hours), and seasonal factors, and use multivariate regression analysis or hybrid prediction models (such as combining physical models and data-driven models) to predict the power generation curve of the wind farm in the next day. For example, analyze the daily power generation data under similar weather conditions in the same season in the past few years, and combine the current weather forecast information to predict the power generation range for the next day. Based on the daily power forecast results, determine the energy storage configuration ratio to balance the power supply and demand throughout the day. If it is predicted that the wind power is higher during the day and lower at night, and the electricity demand during the day is relatively stable, the energy storage configuration should be able to store excess electricity during the day for use at night. Assume that the average excess power during the day is , the average power gap at night is , the charge-discharge cycle efficiency of energy storage is , then the energy storage configuration capacity is the daytime charging time), is the night discharge time), take the larger capacity value as the basis for energy storage configuration, and the daily energy storage configuration ratio coefficient .

[0063] : Average excess power during the day, in watts ). : Average power deficit during the night, in watts ). : Charge and discharge cycle efficiency of energy storage equipment. : Daytime energy storage configuration capacity based on daily power forecast, in watt-hours ) or other energy units.

[0064] : Nighttime energy storage configuration capacity based on daily power forecast, in watt-hours ) or other energy units. : Daytime charging time, in hours ).

[0065] : Night discharge time, in hours ). : Daily energy storage configuration ratio coefficient.

[0066] 2. Weekly power forecast: Prediction and calculation process: predictions are made based on longer historical data (such as weekly power generation data from the past few months or even years), long-term weather forecasts, and energy demand trends in areas surrounding offshore wind farms. For example, by analyzing the weekly power generation variation patterns in different seasons in the past, combined with the weather forecast for the next week and the weekly variation trends of industrial and residential power consumption in the region, the approximate range and fluctuations of the wind farm's power generation in the next week are predicted. For weekly power forecasts, the energy storage configuration ratio For weekly power forecasts, the energy storage configuration ratio mainly considers coping with the intermittent and volatile nature of wind power within a week, as well as coordination with other energy supplies (such as grid power supply, backup power supply, etc.). If it is predicted that wind power is low on certain days and electricity demand in the region is high, energy storage should be able to store enough energy to make up for the shortfall when wind power is sufficient. Assume that the maximum power gap within a week is , energy storage configuration capacity is the total time of possible power gap), weekly energy storage configuration proportional coefficient .

[0067] : Maximum power shortfall during a week, in watts. : Energy storage configuration capacity based on weekly power forecast, in watt-hours or other energy units.

[0068] : The total time that the power gap may occur, in hours. : Weekly energy storage configuration ratio coefficient.

[0069] Through the above prediction and analysis at different time scales, a more reasonable energy storage configuration ratio is comprehensively obtained to achieve the optimal configuration of the offshore wind power energy storage system and improve the stability, reliability and economy of offshore wind power.

[0070] Furthermore, the sub-steps of step 5 are as follows: (1) Determine wind power: Sensors installed on each wind turbine in an offshore wind farm collect wind speed, wind direction, wind turbine blade speed, and cabin temperature parameters in real time. These data are the basis for determining wind power. For example, wind speed data is particularly critical because there is a specific functional relationship between wind power and wind speed (generally, between the cut-in wind speed and the rated wind speed, the power increases with the cube of the wind speed, and remains constant after exceeding the rated wind speed).

[0071] At the same time, meteorological data of the sea area where the wind farm is located is collected. The meteorological data includes large-scale meteorological information provided by surrounding meteorological stations and local meteorological changes monitored by offshore buoys. These meteorological data help to more fully understand the environmental factors that affect wind power. For example, changes in air pressure may affect air density, which in turn affects the power generation efficiency of wind turbines.

[0072] Based on the collected data, the established wind power calculation model is used to determine the current wind power; Common calculation models include models based on physical principles, which calculate power based on aerodynamic theory and the characteristic curve of the wind turbine. For example, according to Betz's law, the power captured by the wind turbine is related to wind speed, air density, fan blade radius, and power coefficient. The theoretical wind power can be calculated through the measured values ​​of these parameters and known wind turbine characteristics.

[0073] Data-driven models, such as neural network models, can also be used. A large amount of historical data (including wind speed, wind direction, temperature and other parameters and corresponding wind power data) is used to train the neural network so that the model can learn the complex mapping relationship between the data. When the parameters collected in real time are input, the neural network can quickly predict the current wind power. The advantage of this model is that it can adapt to complex nonlinear relationships and can continuously optimize the prediction performance as new data accumulates.

[0074] (2) Predicting energy storage output: Monitor the energy storage system in real time to obtain the current power, charge and discharge current, and voltage parameters of the energy storage equipment; at the same time, monitor the health status of the energy storage system, including changes in the internal resistance of the battery and temperature distribution; the health status will affect the charge and discharge efficiency and power output capacity of the energy storage system; an increase in the internal resistance of the battery may lead to an increase in energy loss during the charge and discharge process, thereby affecting the accuracy of the prediction of the energy storage output.

[0075] For example, for a battery energy storage system, by monitoring the battery's state of charge (SOC), one can understand the proportion of the battery's remaining power and thus estimate its dischargeable and rechargeable amounts.

[0076] (3) Establish a prediction model: Establish a prediction model for energy storage output based on the historical operation data of the energy storage system (including charging and discharging power data under different power states and environmental conditions) and current state parameters. Time series analysis methods, such as the autoregressive moving average (ARIMA) model, can be used to analyze the historical changes in the output of the energy storage system and predict future energy storage output in combination with current state data. For example, if it is found that the discharge power of the energy storage system shows a certain periodic change during certain time periods in the past when the power is within a specific range and the ambient temperature is stable, then the ARIMA model can be used to capture this periodicity and predict future discharge power change trends.

[0077] For complex energy storage systems, such as hydrogen energy storage systems involving multiple links such as hydrogen generation, storage and fuel cell power generation, more complex models may be needed, such as hybrid models that combine physical and chemical process models and data-driven models. For example, physical and chemical processes such as the energy conversion efficiency in the process of hydrogen production and the impact of pressure and temperature changes in hydrogen storage on fuel cell power generation can be considered, and historical data can be used to optimize some empirical parameters in the model to improve the accuracy of energy storage output prediction.

[0078] (4) Forecasting wind power Obtain longer-term weather forecast data, including detailed weather information such as wind speed, wind direction, temperature, and air pressure for the next few hours or even days. These weather forecast data can come from professional meteorological agencies or numerical weather forecast models. For example, the global weather forecast data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) has high accuracy and resolution, which can provide strong support for offshore wind power forecasting.

[0079] Combine weather forecast data with geographic information of the sea area where the wind farm is located (such as topography, ocean roughness, etc.). Geographic information will affect the flow of wind, thereby changing the actual wind speed and direction at the wind turbine. For example, islands or shoals on the sea surface may cause local wind speed acceleration or wind direction changes. Taking these geographical factors into account through geographic information system (GIS) technology can more accurately predict the actual wind energy resources at the wind turbine.

[0080] (5) Optimize the prediction model: Build a wind power prediction model based on historical wind power data and integrated meteorological forecast data. Machine learning algorithms such as support vector machine (SVM), random forest (RF) or convolutional neural network (CNN) in deep learning algorithms can be used. These models can learn the complex relationship between meteorological data and wind power. For example, the random forest algorithm can classify and predict the changes in wind power under different combinations of meteorological factors by constructing multiple decision trees, thereby improving the robustness of the prediction.

[0081] Continuously optimize the prediction model, use cross-validation and other techniques to evaluate the performance of the model, and adjust the model parameters or structure based on the evaluation results. For example, if the model is found to have large prediction errors under certain specific meteorological conditions, such as strong wind shear, the prediction accuracy of the model under these special conditions can be improved by adding relevant data features (such as vertical gradient of wind speed) or adjusting the decision rules of the model.

[0082] (6) Based on the predicted wind power and energy storage output, formulate a charging and discharging control strategy for energy storage. When the predicted wind power is greater than the current power demand and the energy storage system is not fully charged, start the energy storage charging process. For example, set a charging threshold. When the difference between wind power and power demand exceeds the threshold and the energy storage SOC is lower than the set upper limit (such as 90%), control the energy storage system to charge at an appropriate charging power. The size of the charging power can be determined based on the characteristics and current state of the energy storage system, ensuring efficient charging while avoiding excessive pressure on the energy storage system.

[0083] When the predicted wind power is less than the power demand, if the energy storage system has enough power, the energy storage discharge process is started. Determine the discharge threshold. When the difference between the power demand and the wind power exceeds the threshold and the energy storage SOC is higher than the set lower limit (such as 20%), control the energy storage system to discharge. The discharge power also needs to be adjusted according to the capacity and current state of the energy storage system to meet the power demand and maintain the stable operation of the system.

[0084] In this embodiment, an energy management system (EMS) is used to specifically perform the charging and discharging operations of energy storage. According to the formulated control strategy, EMS sends charging and discharging instructions to the energy storage system, and controls the power conversion device (such as inverter) of the energy storage equipment to convert and transmit electrical energy. For example, when charging, EMS controls the inverter to convert the AC power generated by wind power into DC power suitable for charging the energy storage system, and adjusts the charging current and voltage; when discharging, the inverter is controlled to convert the DC power output by the energy storage system into AC power and feed it into the power grid or directly supply the power-consuming equipment. At the same time, EMS monitors the operating status of the energy storage system in real time to ensure the safety and stability of the charging and discharging process, such as monitoring whether the battery temperature and voltage are within the normal range, and adjusting the charging and discharging strategy or taking protective measures in a timely manner if an abnormal situation occurs.

[0085] In this embodiment, the wind power and the charging and discharging power of the energy storage system are synthesized and calculated to obtain the total power generation. When the energy storage system is in a charging state, the total power generation is equal to the wind power minus the energy storage charging power; when the energy storage system is in a discharging state, the total power generation is equal to the wind power plus the energy storage discharging power. For example, if the current wind power is 50MW and the energy storage charging power is 10MW, the total power generation is 40MW; if the energy storage discharging power is 8MW, the total power generation is 58MW. The output total power generation is monitored in real time to ensure that it meets the grid access requirements and the needs of electrical equipment. The monitored total power generation data is fed back to the control system and energy management system of the wind farm to further optimize and adjust the wind power prediction, energy storage charging and discharging control and other links. For example, if it is found that the total power generation fluctuates greatly and exceeds the range allowed by the power grid, the system can adjust the charging and discharging strategy of the energy storage, such as increasing the discharge power of the energy storage to smooth the fluctuation, or adjusting the parameters of the wind power prediction model to improve the prediction accuracy, thereby optimizing the subsequent power output control.

[0086] Furthermore, the sub-steps of step 6 are: 1. Strategies for dealing with mismatch between predicted power and actual power: 1. Power monitoring and deviation judgment: A real-time power monitoring system is established to accurately measure and record the predicted power and actual power of offshore wind power. For example, high-precision power sensors are installed on the transmission lines of wind farms to collect power data at a high frequency (such as several times per second). By comparing the predicted power curve and the actual power curve, the deviation between the two is calculated (including the size and duration of the deviation). When the deviation exceeds the pre-set threshold, it is determined that a power mismatch has occurred. The setting of the threshold can be determined based on factors such as the scale of the wind farm, grid access requirements, and the performance of the energy storage system. For example, for a large offshore wind farm, the power deviation threshold may be set at about 10% of the rated power.

[0087] 2. Peak shaving operation: Charging peak shaving: When the actual power of offshore wind power is higher than the predicted power and the grid's absorption capacity is limited, the energy storage station enters the charging peak shaving mode. The energy storage station receives excess wind power energy at an appropriate charging power based on the difference between the actual power and the predicted power and its own charging capacity. For example, if the actual wind power is 20MW higher than the predicted power, and the maximum charging power of the energy storage station is 15MW, the energy storage station charges at 15MW and processes the excess 5MW energy through other means (such as wind abandonment control or coordination with other adjustable loads). During the charging process, the energy storage station needs to consider factors such as the battery's state of charge (SOC), charging efficiency, and battery health status. Generally speaking, when the battery SOC is low, a larger charging current can be used, but as the SOC increases, the charging current needs to be gradually reduced to avoid overcharging and extend battery life.

[0088] Discharge peak shaving: When the actual power of offshore wind power is lower than the predicted power and the power demand is large, the energy storage station performs discharge peak shaving. The energy storage station outputs electric energy to supplement the power grid or power-consuming equipment according to the size of the power gap and its own discharge capacity. For example, if the power demand is 15MW higher than the actual power of wind power, the discharge power of the energy storage station can reach 10MW, then the energy storage station discharges at a power of 10MW, and the remaining 5MW power gap can be made up by other backup power sources or grid adjustments. During the discharge process, attention should also be paid to the status of the energy storage system, such as the battery SOC cannot be lower than a too low safety threshold (such as 20%), to ensure the continuous operation capability and stability of the energy storage system.

[0089] 3. FM operation: The energy storage station participates in the frequency regulation of the power grid through rapid response control. When the power fluctuation of offshore wind power causes the frequency of the power grid to change, the energy storage station quickly adjusts the charging and discharging power. For example, when the frequency of the power grid increases (indicating excess power generation), the energy storage station increases the charging power, absorbs excess electric energy, and reduces the frequency of the power grid; when the frequency of the power grid decreases (insufficient power generation), the energy storage station increases the discharge power, replenishes electric energy, and recovers the frequency of the power grid. The frequency regulation response speed of the energy storage station is usually required to be completed within a few seconds or even less, which requires the support of advanced power electronic control technology and the high power density characteristics of the energy storage equipment. For example, the use of advanced inverter control systems can quickly adjust the charging and discharging power of the energy storage station according to slight changes in the power grid frequency (such as ±0.1Hz), and the adjustment range can reach about 10%20% of the rated power of the energy storage station.

[0090] 2. Energy storage stations and wind farms share hydrogen resources to achieve comprehensive energy management 1. Hydrogen resource sharing model: Shared hydrogen production and storage: The excess electricity generated by the wind farm can be used to produce hydrogen by electrolysis of water, and the produced hydrogen is stored in a hydrogen storage facility connected to the energy storage station. The hydrogen fuel cell in the energy storage station can use this stored hydrogen to generate electricity. For example, during periods of excess wind power, the water electrolysis hydrogen production equipment operates at rated power and stores the produced hydrogen; when wind power is insufficient or electricity demand is peak, the hydrogen fuel cell uses the stored hydrogen to generate electricity and outputs electricity to supplement the power grid or the wind farm's internal power system. Parameters such as the capacity and pressure of the hydrogen storage facility need to be reasonably designed based on factors such as the power generation scale of the wind farm, the energy requirements of the energy storage station, and the production and consumption rate of hydrogen. For example, for a 100MW offshore wind farm, the capacity of the supporting hydrogen storage facility may be designed to store hydrogen production for several hours to several days to cope with different energy supply and demand situations.

[0091] Coordinated management of energy flows: Coordinated management of hydrogen resources between wind farms and energy storage stations is achieved through the energy management system (EMS). EMS optimizes hydrogen production, storage, and use strategies based on information such as wind power forecasts, actual power monitoring, energy storage station status (including battery power, hydrogen fuel cell status, etc.), and electricity demand. For example, when it is predicted that wind power will continue to be low for a period of time in the future and the battery power of the energy storage station is insufficient, EMS arranges in advance to increase hydrogen production and storage so that energy demand can be met through hydrogen fuel cell power generation when needed; when wind power is high and the energy storage station battery is close to full, hydrogen production is reduced, and excess electricity is stored in the battery first to improve energy efficiency.

[0092] 2. Comprehensive management benefits: Improve energy efficiency: Sharing hydrogen resources allows the excess electricity of wind farms to be effectively utilized, reducing the phenomenon of wind abandonment. At the same time, the energy storage station uses hydrogen fuel cells to flexibly supplement electricity in different energy supply and demand scenarios, improving the overall utilization efficiency of the entire energy system. For example, compared with simple battery energy storage, after the introduction of hydrogen energy storage, in the case of long-term low wind speed or high electricity demand, the stored hydrogen can be used to continuously supply electricity, so that the annual power generation utilization rate of the wind farm can be increased by about 5%-10%.

[0093] Enhanced system stability and reliability: The coordinated operation of energy storage stations and wind farms based on the sharing of hydrogen resources enhances the stability and reliability of the entire energy system. In the face of large fluctuations in wind power, grid failures, or extreme weather, the system can ensure a stable supply of electricity by switching and complementing a variety of energy storage and power generation methods. For example, when a short-term grid failure occurs, the energy storage station can use hydrogen fuel cells to independently power important equipment within the wind farm, maintain the basic operation of the wind farm, and avoid shutdown of the entire wind farm due to grid failures, thereby improving the survivability and reliability of the wind farm under complex working conditions.

[0094] The above embodiments are only preferred technical solutions of the present invention and should not be regarded as limiting the present invention. The protection scope of the present invention shall be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A method for configuring offshore wind power energy storage, characterized in that The following steps are involved: Step 1: Build a wind farm and an energy storage station so that the energy storage station and the wind farm can share hydrogen resources. At the same time, the energy storage station, wind farm, and fuel cell station are connected through a transportation hub, and the energy storage station is configured in the same proportion as the wind farm. Step 2: Calculate the energy storage capacity required for hydrogen production based on the power, energy and efficiency of hydrogen production; Step 3: According to the power ratio relationship, the capacity of the energy storage device is obtained; the power ratio includes the ratio of wind power to energy storage power, the ratio of hydrogen fuel cell power to energy storage power, and the ratio of electric hydrogen production power to energy storage power; Step 4: Determine the energy storage configuration ratio based on the predicted power generation; Step 5: Predict the power generation of the wind farm; Step 6: When the predicted power of offshore wind power does not match the actual power, use the energy storage station to adjust the peak or frequency to increase the accuracy of the prediction, and make up for the prediction deviation through the energy storage station's consumption or output. The energy storage station and wind farm share hydrogen resources to achieve comprehensive energy management.

2. The offshore wind power energy storage configuration method according to claim 1, characterized in that: In step 1, the energy storage station configuration is in the same proportion as the wind farm, which means that the configuration parameters of the energy storage station and the corresponding parameters of the wind farm are set in the same proportional relationship; the configuration parameters include capacity and power.

3. The offshore wind power energy storage configuration method according to claim 1, characterized in that: The calculation process of step 2 is as follows: According to power Definition, power is the energy per unit time, that is: , For electric hydrogen production : ,in : Electric hydrogen production time is the time required to complete the electric hydrogen production process; : Electricity-to-hydrogen power, which indicates the amount of electricity used to produce hydrogen per unit time; : The energy required for hydrogen production by electricity is the total energy required to complete the hydrogen production process; So ; Due to the efficiency problem of the electric hydrogen production process, the energy actually required to be obtained from the energy storage device is greater than the energy required for theoretical hydrogen production; according to the efficiency calculation formula: , For the hydrogen production process, ,in, : The efficiency of hydrogen production from electricity is a dimensionless coefficient that indicates the efficiency of converting electrical energy into the chemical energy of hydrogen; Indicates the output energy of hydrogen produced by electricity; so ; The energy storage capacity required for hydrogen production is In fact, it is the capacity of the energy storage equipment that provides energy for the hydrogen production process, that is, ; The calculation formula for the energy storage capacity required for hydrogen production by electricity is: ; :The energy storage capacity required for hydrogen production from electricity is used to measure the capacity of the energy storage equipment required to provide energy for the hydrogen production process from electricity.

4. The offshore wind power energy storage configuration method according to claim 1, characterized in that: In step 3, the ratio of wind power to energy storage power is as follows: Assume that wind power reaches its maximum value at a certain moment , and the charging power limit of the energy storage device is , the power ratio is set as ,in is a coefficient less than or equal to 1, determined according to the performance of the energy storage device and system requirements; During the discharge process, when the wind power is lower than the load demand, the energy storage device needs to discharge to supplement the power; assuming the load demand power is , wind power is , the discharge power of the energy storage device is , the power ratio relationship is expressed as: ; According to the power ratio relationship and the wind power prediction curve, the charging and discharging power required by the energy storage device in different time periods is calculated, and then the capacity of the energy storage device is obtained: by integrating the wind power prediction curve, the total amount of energy that needs to be stored in a certain period of time is obtained. , combined with the charging and discharging efficiency of the energy storage device , calculate the capacity of the energy storage device ; in, : The maximum value of wind power at a certain moment; : Charging power limit of energy storage equipment; : A coefficient less than or equal to 1, determined according to the performance of the energy storage equipment and system requirements, used to express the proportional relationship between the peak wind power and the energy storage charging power; : Load demand power; : Wind power; : Discharge power of energy storage equipment; : The total amount of energy that needs to be stored within a certain period of time; : Charging and discharging efficiency of energy storage equipment; : Energy storage equipment capacity.

5. The offshore wind power energy storage configuration method according to claim 1, characterized in that: In step 3, the ratio of hydrogen fuel cell power to energy storage power is as follows: Hydrogen fuel cells play the role of supplementing power and regulating energy in the system. When the wind power forecast deviation is large or the energy storage device is insufficient, the hydrogen fuel cell needs to output power. Assume that the rated power of the hydrogen fuel cell is , the power of the energy storage device is , in order to ensure the stability of the system, the power ratio is set as: ， in It is a coefficient determined based on the system reliability requirements and the performance of the hydrogen fuel cell; When the energy storage device is in a low power state, the hydrogen fuel cell needs to output enough power to meet the load demand, and it may also be necessary to charge the energy storage device; at this time, the power ratio relationship needs to consider the power generation efficiency of the hydrogen fuel cell. , Charging efficiency of energy storage equipment and load power requirements ; Get the relationship , through this relationship and known system parameters, the reasonable ratio of hydrogen fuel cell power and energy storage device power is further determined, thereby calculating the capacity of the energy storage device; in, : Rated power of hydrogen fuel cell; : Power of energy storage equipment; : A coefficient determined based on system reliability requirements and the performance of hydrogen fuel cells, used to express the proportional relationship between the power of hydrogen fuel cells and the power of energy storage equipment; : Power generation efficiency of hydrogen fuel cells; : Charging efficiency of energy storage equipment.

6. The offshore wind power energy storage configuration method according to claim 1, characterized in that: In step 3, the ratio of hydrogen production power to energy storage power is as follows: The process of producing hydrogen by electricity consumes electricity, which comes from wind power. Assume that the power of producing hydrogen by electricity is , the output power of the energy storage device is , the power ratio relationship is expressed as: ， in It is a coefficient determined based on the efficiency of hydrogen production from electricity and hydrogen demand factors; The energy efficiency of hydrogen production from electricity is known to be , the hydrogen energy required to be produced within a certain period of time is , then the energy required for hydrogen production is ; Based on the power of hydrogen production and the energy required , and the output power limit of the energy storage device, calculate the energy and time that the energy storage device needs to provide during the hydrogen production process, and then derive the capacity of the energy storage device: ， in is the time period of hydrogen production from electricity; : Electricity-to-hydrogen power; : Output power of energy storage equipment; : A coefficient determined based on the efficiency of hydrogen production from electricity and hydrogen demand factors, used to express the proportional relationship between the power of hydrogen production from electricity and the output power of the energy storage device; : Energy efficiency of hydrogen production from electricity; : The amount of hydrogen energy that needs to be produced within a certain period of time; : The time period of hydrogen production by electricity; : Energy storage equipment capacity.

7. The offshore wind power energy storage configuration method according to claim 1, characterized in that: The sub-steps of step 4 are as follows: (1) Perform short-term power forecasting, including hourly power forecasting and minute-level power forecasting; Prediction and calculation process of hourly power forecast: Based on historical data and real-time meteorological information, time series analysis methods or machine learning algorithms are used to predict the power generation of offshore wind farms in the next 1-6 hours; Analyze power fluctuations based on the predicted hourly power curve; if it is predicted that wind power will rise or fall significantly within the next hour, in order to stabilize output, the energy storage configuration ratio should be able to store excess energy when power rises and release sufficient energy when power drops; The calculation method is: Assume the predicted power change is The charging and discharging efficiencies of energy storage are and , then the energy storage configuration capacity or , the energy storage configuration ratio is based on the rated power of the wind farm Determine the proportionality factor ; in, : predicted hourly power change, : Charging efficiency of energy storage equipment; : Discharge efficiency of energy storage equipment; : Energy storage configuration capacity based on hourly power forecast; : Rated power of wind farm; : Hourly energy storage configuration ratio coefficient; Prediction and calculation process of minute-level power forecast: Use more sophisticated meteorological monitoring data and advanced forecasting models to predict power generation changes within the next 10-60 minutes; the energy storage configuration ratio needs to consider the rapid response capability of the energy storage equipment, assuming that the rapid response power is , minute-level energy storage configuration ratio coefficient At the same time, the energy storage capacity must be combined to ensure that the power output can be maintained for a certain period of time. The energy storage capacity is calculated according to the energy demand. , and further determine the proportional relationship with the rated power of the wind farm; in, : Rapid response power of energy storage equipment; : Minute-level energy storage configuration ratio coefficient; : Energy storage configuration capacity based on minute-level power forecast; : The number of minutes to maintain power output; (2) Conduct medium- and long-term power forecasts, including daily and weekly power forecasts; The prediction and calculation process of daily power forecast: Taking into account the historical daily power data, weather forecast and seasonal factors, multiple regression analysis or hybrid prediction model is used to predict the power curve of the wind farm in the next day; the daily power data of the same season and similar weather conditions in the past few years are analyzed, and the power range of the next day is predicted in combination with the current weather forecast information; according to the daily power forecast results, the energy storage configuration ratio is determined to balance the power supply and demand of the whole day; if the wind power is predicted to be higher during the day and lower at night, and the electricity demand during the day is relatively stable, the energy storage configuration should be able to store excess electricity during the day for use at night; assuming that the average excess power during the day is , the average power gap at night is , the charge-discharge cycle efficiency of energy storage is , then the energy storage configuration capacity , , take the larger capacity value as the basis for energy storage configuration, and the daily energy storage configuration ratio coefficient ; in, : average excess power during the day; : Average power gap at night; : Charge and discharge cycle efficiency of energy storage equipment; : Daytime energy storage configuration capacity based on daily power forecast; : Nighttime energy storage configuration capacity based on daily power forecast; : Charging time during the day; : Night discharge time; : Daily energy storage configuration ratio coefficient; The prediction and calculation process of weekly power forecast: forecast based on longer historical data, long-term weather forecast and energy demand trend in the surrounding areas of offshore wind farms; analyze the weekly power generation change patterns in different seasons in the past, combine the weather forecast for the next week and the weekly change trend of industrial and residential electricity consumption in the region, and predict the approximate range and fluctuation of the wind farm's power generation in the next week; for weekly power forecast, the energy storage configuration ratio is mainly considered to deal with the intermittent and volatility of wind power within a week, as well as the coordination with other energy supplies; if it is predicted that the wind power is low on certain days and the electricity demand in the region is high, the energy storage should be able to store enough energy to make up for the shortfall when the wind power is sufficient; set the maximum power gap within the week to be , energy storage configuration capacity , weekly energy storage configuration ratio coefficient ; in, : The maximum power gap within the week; : Energy storage configuration capacity based on weekly power forecast; : The total time that power gap may occur; : Weekly energy storage configuration ratio coefficient; Through the above prediction and analysis at different time scales, a more reasonable energy storage configuration ratio is comprehensively obtained to achieve the optimal configuration of the offshore wind power energy storage system, which is used to improve the stability, reliability and economy of offshore wind power.

8. The offshore wind power energy storage configuration method according to claim 1, characterized in that: The sub-steps of step 5 are as follows: (1) Determine wind power: Sensors installed on each wind turbine in the offshore wind farm collect wind speed, wind direction, wind turbine blade speed, and cabin temperature parameters in real time. At the same time, collect meteorological data of the sea area where the wind farm is located. The meteorological data includes large-scale meteorological information provided by surrounding meteorological stations and local meteorological changes monitored by offshore buoys. Based on the collected data, the established wind power calculation model is used to determine the current wind power. (2) Predicting energy storage output: Monitor the energy storage system in real time to obtain the current power, charge and discharge current, and voltage parameters of the energy storage equipment; at the same time, monitor the health status of the energy storage system, including the change in the internal resistance and temperature distribution of the battery; the health status will affect the charge and discharge efficiency and power output capacity of the energy storage system; (3) Establish a prediction model: Establish an energy storage output prediction model based on the historical operation data and current state parameters of the energy storage system; use time series analysis methods to analyze the historical changes in the output of the energy storage system, and combine the current state data to predict the future energy storage output; if it is found that the energy storage system's discharge power shows a certain periodic change in certain time periods in the past when the power is within a specific range and the ambient temperature is stable, then use the ARIMA model to capture this periodicity and predict the future discharge power change trend; (4) Forecasting wind power Obtain longer-term weather forecast data, including wind speed, wind direction, temperature, and air pressure for the next few hours or even days; Combine weather forecast data with geographic information of the sea area where the wind farm is located; geographic information will affect the flow of wind, thereby changing the actual wind speed and direction at the wind turbine; (5) Optimize the prediction model: Build a wind power prediction model based on historical wind power data and integrated meteorological forecast data; use machine learning algorithms to continuously optimize the prediction model; (6) Formulate a charging and discharging control strategy for energy storage based on the predicted wind power and energy storage output; when the predicted wind power is greater than the current power demand and the energy storage system is not fully charged, start the energy storage charging process: set a charging threshold, and when the difference between the wind power and the power demand exceeds the threshold and the energy storage SOC is lower than the set upper limit, control the energy storage system to charge at an appropriate charging power; when the predicted wind power is less than the power demand, if the energy storage system has sufficient power, start the energy storage discharging process; Determine the discharge threshold. When the difference between the power demand and the wind power exceeds the threshold and the energy storage SOC is higher than the set lower limit, control the energy storage system to discharge. The discharge power also needs to be adjusted according to the capacity and current status of the energy storage system to meet the power demand and maintain the stable operation of the system.

9. The offshore wind power energy storage configuration method according to claim 1, characterized in that: The sub-steps of step 6 are: (1) The strategies for dealing with the mismatch between predicted power and actual power are as follows: establish a real-time power monitoring system to accurately measure and record the predicted power and actual power of offshore wind power; install high-precision power sensors on the transmission lines of wind farms to collect power data at a high frequency; compare the predicted power curve with the actual power curve to calculate the deviation between the two; when the deviation exceeds a preset threshold, it is determined that a power mismatch has occurred; When the actual offshore wind power is higher than the predicted power and the grid’s absorption capacity is limited, the energy storage station enters the charging peak load mode. The energy storage station receives excess wind power at an appropriate charging power based on the difference between the actual power and the predicted power and its own charging capacity. When the actual power of offshore wind power is lower than the predicted power and the power demand is large, the energy storage station discharges to load the peak. The energy storage station outputs electric energy to supplement the power grid or power-consuming equipment according to the size of the power gap and its own discharge capacity. The energy storage station participates in the frequency regulation of the power grid through rapid response control. When the power fluctuation of offshore wind power causes the frequency of the power grid to change, the energy storage station quickly adjusts the charging and discharging power. (2) The strategy of sharing hydrogen resources between energy storage stations and wind farms to achieve comprehensive energy management is as follows: the excess electricity generated by wind farms can be used to produce hydrogen by electrolysis of water, and the produced hydrogen is stored in a hydrogen storage facility connected to the energy storage station; the hydrogen fuel cells in the energy storage station use the stored hydrogen to generate electricity; during periods of excess wind power, the water electrolysis hydrogen production equipment operates at rated power and stores the produced hydrogen; When wind power is insufficient or electricity demand is at a peak, hydrogen fuel cells use stored hydrogen to generate electricity, and output electricity to supplement the power grid or the wind farm's internal power system; the capacity and pressure parameters of hydrogen storage facilities need to be reasonably designed based on the power generation scale of the wind farm, the energy demand of the energy storage station, and the production and consumption rate of hydrogen; Achieve coordinated management of hydrogen resources between wind farms and energy storage stations through energy management systems; Optimize hydrogen production, storage and use strategies through the energy management system based on wind power forecasts, actual power monitoring, energy storage station status and electricity demand information; Sharing hydrogen resources enables the effective use of excess electricity from wind farms, reducing wind curtailment. At the same time, energy storage stations use hydrogen fuel cells to flexibly supplement electricity in different energy supply and demand scenarios, improving the overall utilization efficiency of the entire energy system. The coordinated operation of energy storage stations and wind farms based on the sharing of hydrogen resources enhances the stability and reliability of the entire energy system. When faced with large fluctuations in wind power, grid failures or extreme weather conditions, the system can ensure a stable supply of electricity by switching and complementing a variety of energy storage and power generation methods.

10. An offshore wind power energy storage configuration optimization system, characterized in that: An offshore wind power energy storage configuration method according to any one of claims 1-9 is adopted.

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