Hydrogen-blended gas unit control system and method based on spot market trading

Abstract

The present invention relates to the technical field of hydrogen-blended gas unit control. Specifically disclosed are a hydrogen-blended gas unit control system and method based on spot market trading. The system comprises: a demand calculation module, which is used for acquiring historical unit operation data, and determining a unit load demand value of the current gas unit on the basis of the historical unit operation data; a supply calculation module, which is used for acquiring wind and solar condition data, and determining a wind and solar supply value on the basis of the wind and solar condition data; and a hydrogen-blending control module, which is used for predicting a unit electricity price on the basis of the unit load demand value of the current gas unit and the wind and solar supply value, determining a hydrogen-blending ratio of the gas unit on the basis of the obtained predicted electricity price, and performing hydrogen-blending control on the gas unit on the basis of the hydrogen-blending ratio of the gas unit. By means of the present invention, a unit electricity price is predicted in view of wind and solar condition data, and hydrogen-blending control is performed on a gas unit on the basis of an electricity price prediction result, thereby effectively improving the operation economy of the gas unit.

Description

A control system and method for hydrogen-blended gas turbine units based on spot market trading Technical Field

[0001] This invention relates to the field of hydrogen-blended gas turbine control technology, and more specifically, to a control system and method for hydrogen-blended gas turbines based on spot market transactions. Background Technology

[0002] In the context of electricity spot market trading, the tight supply and demand in the electricity spot market is directly related to electricity prices. With the continuous development of wind and solar energy, the operating space and number of traditional thermal power plants are being squeezed, leading to a severe imbalance between supply and demand in the electricity spot market. This is especially true during periods of high wind and solar power generation, when electricity prices can remain at zero for extended periods, sometimes exceeding ten hours. Furthermore, due to persistently high natural gas prices, fuel costs account for 90% of the cost of gas turbine units, severely restricting their operational economics and significantly limiting their flexible start-up and shutdown, low-carbon, and environmentally friendly characteristics.

[0003] With the continuous development of water electrolysis hydrogen production technology, the cost of electrolyzers in water electrolysis hydrogen production has been decreasing year by year, while the efficiency of electrolyzers has been gradually increasing, providing a technological foundation for hydrogen production by gas turbine units. Water electrolysis hydrogen production systems mainly include a rectification system, an electrolyzer, and a purification system. Rectification system technology is mature and widely used. Electrolyzer types mainly include alkaline water electrolyzers, proton exchange membrane electrolyzers, and solid oxide electrolyzers. Among these, alkaline water electrolyzer technology is mature and commercialized, with a cost of 2000-4000 RMB / KW and an energy consumption level of 4-5 KWh / Nm³. 3 For a plant with an annual hydrogen production capacity of 2 million cubic meters, electricity costs account for approximately 75% (with an electricity price of 0.5 yuan / kWh). Therefore, how to control hydrogen blending in gas turbine units to improve their operational economy has become a pressing technical problem to be solved in this field. Summary of the Invention

[0004] The purpose of this invention is to provide a control system and method for hydrogen-blended gas turbine units based on spot market transactions, in order to solve the problem of low operating economy of gas turbine units in the prior art.

[0005] To achieve the above objectives, the present invention provides a hydrogen-blended gas turbine unit control system based on spot market transactions, comprising:

[0006] The demand calculation module is used to obtain historical unit operating data and determine the current unit load demand value of the gas turbine based on the historical unit operating data;

[0007] The supply calculation module is used to acquire wind and solar conditions data and determine the wind and solar supply value based on the wind and solar conditions data.

[0008] The hydrogen blending control module is used to predict the electricity price of the gas turbine unit based on the current unit load demand and wind and solar power supply, determine the hydrogen blending ratio of the gas turbine unit according to the predicted electricity price, and control the hydrogen blending of the gas turbine unit according to the hydrogen blending ratio.

[0009] Furthermore, the demand calculation module determines the current unit load demand value of the gas turbine unit based on historical unit operating data, including:

[0010] Based on historical unit operating data, determine the operating data of each historical unit and the corresponding power generation of the gas turbine unit, and calculate the correlation coefficient between the operating data of each historical unit and the power generation of the gas turbine unit.

[0011] Historical unit operation data with a correlation coefficient greater than the first preset threshold are selected, and key operating parameters of the gas turbine units are determined based on the selected historical unit operation data;

[0012] The key operating parameters are normalized, and the load correction parameters are determined based on the normalized key operating parameters.

[0013] Obtain the initial unit load demand value of the gas turbine unit, and correct the initial unit load demand value according to the load correction parameters to obtain the current unit load demand value of the gas turbine unit.

[0014] Furthermore, the determination of key operating parameters of the gas turbine unit based on the selected historical unit operating data includes:

[0015] The historical unit operation data selected are sorted according to the magnitude of the correlation coefficient, and weight values ​​are assigned to each corresponding operation data according to the sorting results of the historical unit operation data.

[0016] Obtain the change curve of the current unit operation data, perform curve fitting on the change curve of the current unit operation data, and obtain the fitting equation of the current unit operation data;

[0017] The regression coefficients of the corresponding fitted equations are corrected according to the weight values ​​of each running data, and the predicted values ​​of the running data are determined based on the fitted equations after the regression coefficients are corrected.

[0018] After normalizing the predicted values ​​of each operating data point, the summation is performed to obtain the key operating parameters of the gas turbine unit.

[0019] Furthermore, the supply calculation module determines the wind and solar supply value based on wind and solar condition data, including:

[0020] Acquire changes in landscape conditions data and plot landscape condition change curves based on these changes.

[0021] The wind and solar stability parameters are determined based on the wind and solar condition change curves, and the wind and solar supply values ​​are determined based on the wind and solar stability parameters.

[0022] Furthermore, determining the wind and solar stability parameters based on the wind and solar condition variation curve includes:

[0023] A rolling time window is set according to a preset time period. The curve of changes in scenery conditions is divided according to the rolling time window to obtain several sub-curves.

[0024] Calculate the average value of each sub-curve, and plot the average value curve based on the average value of each sub-curve;

[0025] Filter out the peak values ​​and corresponding time periods in the average value change curve, and determine the interval between any two adjacent peak values ​​based on the peak values ​​and corresponding time periods in the average value change curve.

[0026] Filter out the time intervals that are greater than the second preset threshold, obtain the difference between the maximum and minimum values ​​within the time intervals that are greater than the second preset threshold, calculate the average of all differences, and obtain the fluctuation deviation value.

[0027] The number of time intervals exceeding the second preset threshold is counted, and the number of time intervals exceeding the second preset threshold is multiplied by the fluctuation deviation value to obtain the wind-solar stability parameter.

[0028] Furthermore, determining the wind and solar supply value based on wind and solar stability parameters includes:

[0029] Determine the range correction parameter based on the wind and light stability parameter, obtain the initial wind and light stability range, and multiply the range correction parameter by the initial wind and light stability range to obtain the wind and light stability range.

[0030] Obtain the wind and solar power generation capacity within the stable range of wind and solar power, and determine the wind and solar power supply value based on the wind and solar power generation capacity within the stable range of wind and solar power.

[0031] Furthermore, the determination of the range correction parameters based on the wind-solar stability parameters includes:

[0032] The range correction parameter is determined according to the formula for calculating the range correction factor, specifically as follows:

[0033]

[0034] Where R is the range correction coefficient, Ra is the initial range correction coefficient, Sa is the preset stability tolerance value, S is the wind and light stability parameter, and Q is the preset adjustment coefficient.

[0035] Furthermore, the hydrogen blending control module predicts the unit's electricity price based on the current unit load demand and wind / solar power supply, including:

[0036] Obtain historical unit load demand values ​​and historical wind and solar power supply values ​​and corresponding unit electricity prices, and establish training and test sets based on historical unit load demand values, historical wind and solar power supply values ​​and corresponding unit electricity prices;

[0037] An initial electricity price prediction model is established, and the initial electricity price prediction model is trained based on the training set and the test set to obtain a trained electricity price prediction model.

[0038] Input the current unit load demand of the gas turbine and the supply of wind and solar power into the trained electricity price prediction model to obtain the predicted electricity price.

[0039] Furthermore, the hydrogen blending control module determines the hydrogen blending ratio of the unit based on the obtained predicted electricity price, including:

[0040] Obtain the preset allowable value for electricity price, calculate the difference between the predicted electricity price and the preset allowable value for electricity price, and determine whether the difference between the predicted electricity price and the preset allowable value for electricity price is greater than the third preset threshold.

[0041] If the difference between the predicted electricity price and the preset allowable electricity price is greater than the third preset threshold, then the first hydrogen blending ratio is set as the hydrogen blending ratio of the current unit.

[0042] If the difference between the predicted electricity price and the preset allowable electricity price is less than or equal to the third preset threshold, then determine whether the difference between the predicted electricity price and the preset allowable electricity price is greater than the fourth preset threshold.

[0043] If the difference between the predicted electricity price and the preset allowable electricity price is greater than the fourth preset threshold, then the second hydrogen blending ratio is set as the hydrogen blending ratio of the current unit.

[0044] If the difference between the predicted electricity price and the preset allowable electricity price is less than or equal to the fourth preset threshold, then the third hydrogen blending ratio is set as the hydrogen blending ratio of the current unit.

[0045] To achieve the above objectives, the present invention also provides a control method for hydrogen-blended gas turbine units based on spot market transactions, the method comprising:

[0046] Obtain historical unit operating data and determine the current unit load demand value of the gas turbine based on the historical unit operating data;

[0047] Obtain wind and solar conditions data, and determine the wind and solar supply value based on the wind and solar conditions data;

[0048] The electricity price of the gas turbine is predicted based on the current load demand and wind and solar power supply. The hydrogen blending ratio of the unit is determined based on the predicted electricity price, and the hydrogen blending of the gas turbine is controlled according to the hydrogen blending ratio.

[0049] The beneficial effects of this invention are as follows:

[0050] By applying the above technical solutions, this invention calculates more accurate unit load demand and wind and solar supply values ​​using historical unit operation data and wind and solar conditions data, thereby achieving accurate prediction of unit electricity prices. At the same time, the hydrogen blending ratio of the unit is adjusted based on the predicted electricity prices, effectively improving the operating economy of the gas turbine unit. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 shows the overall structure of a hydrogen-blended gas turbine control system based on spot market trading, as proposed in an embodiment of the present invention.

[0053] Figure 2 shows a flowchart of a hydrogen-blended gas turbine control method based on spot market transactions proposed in an embodiment of the present invention. Embodiments of the present invention

[0054] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0055] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0056] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0057] This invention provides a control system for a hydrogen-blended gas turbine unit based on spot market transactions, as shown in Figure 1, including:

[0058] The demand calculation module is used to acquire historical unit operation data and determine the current unit load demand value of the gas turbine based on the historical unit operation data; the supply calculation module is used to acquire wind and solar condition data and determine the wind and solar supply value based on the wind and solar condition data; the hydrogen blending control module is used to predict the unit electricity price based on the current unit load demand value and wind and solar supply value of the gas turbine, determine the hydrogen blending ratio of the gas turbine based on the obtained predicted electricity price, and control the hydrogen blending of the gas turbine based on the hydrogen blending ratio of the gas turbine.

[0059] In this embodiment, historical unit operating data includes multiple data points, specifically fuel flow rate, fuel calorific value, exhaust temperature, and exhaust pressure data. The current unit load demand of the gas turbine is determined using this historical operating data. Wind and solar condition data specifically include wind speed and solar irradiance data. The wind and solar supply value is determined using this wind and solar condition data. Based on the current unit load demand and wind and solar supply values, the unit's electricity price is predicted. During periods of low electricity prices, the hydrogen blending ratio of the gas turbine is reduced, allowing the hydrogen storage equipment to store a certain amount of hydrogen. During periods of high electricity prices, the hydrogen blending ratio is increased, allowing the unit to earn revenue from the electricity spot market through hydrogen-blended combustion, thereby improving the operational economy of the gas turbine.

[0060] In some embodiments of the present invention, the demand calculation module determines the current unit load demand value of the gas turbine unit based on historical unit operating data, including: determining the historical unit operating data and the corresponding gas turbine unit power generation based on the historical unit operating data, calculating the correlation coefficient between the historical unit operating data and the gas turbine unit power generation; filtering out historical unit operating data with a correlation coefficient greater than a first preset threshold, determining the key operating parameters of the gas turbine unit based on the filtered historical unit operating data; normalizing the key operating parameters, determining load correction parameters based on the normalized key operating parameters; obtaining the initial unit load demand value of the gas turbine unit, correcting the initial unit load demand value based on the load correction parameters, and obtaining the current unit load demand value of the gas turbine unit.

[0061] In this embodiment, the correlation coefficient between the historical unit operation data and the power generation of the gas turbine is calculated based on the Pearson correlation coefficient algorithm. The key operating parameters of the gas turbine are obtained by using the correlation coefficient greater than the first preset threshold. The normalized key operating parameters are used as load correction parameters. The load correction parameters are multiplied by the initial unit load demand value to obtain the current unit load demand value of the gas turbine.

[0062] In some embodiments of the present invention, the step of determining the key operating parameters of the gas turbine unit based on the selected historical unit operating data includes: sorting the selected historical unit operating data according to the magnitude of the correlation coefficient; assigning weight values ​​to each corresponding operating data according to the sorting result of the historical unit operating data; obtaining the change curve of the current unit operating data; performing curve fitting on the change curve of the current unit operating data to obtain the fitting equation of the current unit operating data; correcting the regression coefficient of the corresponding fitting equation according to the weight value of each operating data; determining the predicted value of the operating data according to the fitting equation after correcting the regression coefficient; and summing the predicted values ​​of each operating data after normalization to obtain the key operating parameters of the gas turbine unit.

[0063] In this embodiment, weight values ​​are assigned to each operating data point by sorting them according to the correlation coefficient of historical unit operating data. The larger the correlation coefficient, the higher the corresponding weight value. The curve of the change of each operating data point of the current gas turbine unit is fitted using the least squares method. By multiplying the assigned weight value with the coefficient of the first term of the fitted equation, the regression coefficient of the fitted equation is corrected, thereby obtaining the predicted value of each operating data point and calculating the key operating parameters.

[0064] In some embodiments of the present invention, the supply calculation module determines the wind and solar supply value based on wind and solar condition data, including: acquiring the changes in wind and solar condition data, plotting a wind and solar condition change curve based on the changes in wind and solar condition data; determining wind and solar stability parameters based on the wind and solar condition change curve, and determining the wind and solar supply value based on the wind and solar stability parameters.

[0065] In this embodiment, wind speed data and light intensity data are determined using the meteorological data of the day. The wind and light conditions data are determined by calculating the weighted average of the wind speed data and light intensity data, and the wind and light conditions change curve is plotted to determine the wind and light supply value.

[0066] In some embodiments of the present invention, determining the wind and solar stability parameters based on the wind and solar condition change curve includes: setting a rolling time window according to a preset time period; dividing the wind and solar condition change curve according to the rolling time window to obtain several sub-change curves; calculating the average value of each sub-change curve; drawing an average value change curve based on the average value of each sub-change curve; filtering out the peak value and the time period corresponding to the peak value in the average value change curve; determining the interval time period between any two adjacent peak values ​​based on the peak value and the time period corresponding to the peak value in the average value change curve; filtering out the interval time periods greater than a second preset threshold; obtaining the difference between the maximum and minimum values ​​within the interval time periods greater than the second preset threshold; calculating the average value of all differences to obtain the fluctuation deviation value; counting the number of interval time periods greater than the second preset threshold; multiplying the number of interval time periods greater than the second preset threshold by the fluctuation deviation value to obtain the wind and solar stability parameters.

[0067] In this embodiment, by calculating the wind and solar stability parameters of the wind and solar condition change curve, the stability level of the wind and solar condition data can be obtained, which facilitates the subsequent calculation of the wind and solar supply value.

[0068] In some embodiments of the present invention, determining the wind and solar supply value based on the wind and solar stability parameters includes: determining a range correction parameter based on the wind and solar stability parameters, obtaining an initial wind and solar stability range, multiplying the range correction parameter by the initial wind and solar stability range to obtain the wind and solar stability range; obtaining the wind and solar power generation within the wind and solar stability range, and determining the wind and solar supply value based on the wind and solar power generation within the wind and solar stability range.

[0069] In this embodiment, the initial wind-solar stability range is the length of the wind-solar stability period. The initial wind-solar stability range is corrected by the wind-solar stability parameters to obtain the wind-solar stability range. The wind and solar power generation is calculated by extracting the wind and solar condition data within the wind and solar stability range of the day, thereby obtaining the wind and solar supply value.

[0070] In some embodiments of the present invention, determining the range correction parameter based on the wind-solar stability parameter includes: determining the range correction parameter according to the range correction coefficient calculation formula, wherein the range correction coefficient calculation formula is specifically as follows:

[0071]

[0072] Where R is the range correction coefficient, Ra is the initial range correction coefficient, Sa is the preset stability tolerance value, S is the wind and light stability parameter, and Q is the preset adjustment coefficient.

[0073] In this embodiment, the range correction parameter is calculated using the wind and solar stability parameter. The smaller the wind and solar stability, the higher the corresponding range correction parameter, and the larger the wind and solar stability range is captured, thereby enabling accurate calculation of wind and solar power generation.

[0074] In some embodiments of the present invention, the hydrogen blending control module predicts the unit electricity price based on the current unit load demand value and wind and solar power supply value of the gas turbine unit, including: obtaining historical unit load demand values ​​and historical wind and solar power supply values ​​and corresponding unit electricity prices; establishing a training set and a test set based on the historical unit load demand values ​​and historical wind and solar power supply values ​​and corresponding unit electricity prices; establishing an initial electricity price prediction model; training the initial electricity price prediction model based on the training set and the test set to obtain a trained electricity price prediction model; and inputting the current unit load demand value and wind and solar power supply value of the gas turbine unit into the trained electricity price prediction model to obtain the predicted electricity price.

[0075] In this embodiment, a neural network model is established based on historical unit load demand values, historical wind and solar power supply values, and corresponding unit electricity prices, thereby enabling the prediction of unit electricity prices.

[0076] In some embodiments of the present invention, the hydrogen blending control module determines the hydrogen blending ratio of the unit based on the obtained predicted electricity price, including: obtaining a preset allowable electricity price value, calculating the difference between the predicted electricity price and the preset allowable electricity price value, and determining whether the difference between the predicted electricity price and the preset allowable electricity price value is greater than a third preset threshold; if the difference between the predicted electricity price and the preset allowable electricity price value is greater than the third preset threshold, then setting a first hydrogen blending ratio as the hydrogen blending ratio of the current unit; if the difference between the predicted electricity price and the preset allowable electricity price value is less than or equal to the third preset threshold, then determining whether the difference between the predicted electricity price and the preset allowable electricity price value is greater than a fourth preset threshold; if the difference between the predicted electricity price and the preset allowable electricity price value is greater than the fourth preset threshold, then setting a second hydrogen blending ratio as the hydrogen blending ratio of the current unit; if the difference between the predicted electricity price and the preset allowable electricity price value is less than or equal to the fourth preset threshold, then setting a third hydrogen blending ratio as the hydrogen blending ratio of the current unit.

[0077] In this embodiment, the first hydrogen blending ratio > the second hydrogen blending ratio > the third hydrogen blending ratio. The hydrogen blending ratio of the gas turbine unit is adjusted by predicting the electricity price. When the electricity price is low, the hydrogen blending ratio of the gas turbine unit is reduced, so that the hydrogen storage equipment stores a certain amount of hydrogen. When the electricity price is high, the hydrogen blending ratio of the gas turbine unit is increased, and the spot market revenue of electricity is earned through hydrogen blending combustion, thereby improving the operating economy of the gas turbine unit.

[0078] Based on the same technical concept, as shown in Figure 2, the present invention also provides a control method for hydrogen-blended gas turbine units based on spot market transactions, the method comprising:

[0079] S101, Obtain historical unit operation data, and determine the current unit load demand value of the gas turbine based on the historical unit operation data;

[0080] S102, Obtain wind and solar conditions data, and determine the wind and solar supply value based on the wind and solar conditions data;

[0081] S103, based on the current unit load demand value and wind and solar power supply value, predict the unit electricity price, determine the hydrogen blending ratio of the gas turbine unit according to the obtained predicted electricity price, and control the hydrogen blending of the gas turbine unit according to the hydrogen blending ratio.

[0082] By applying the above technical solutions, this invention utilizes a demand calculation module to acquire historical unit operating data and determine the current unit load demand value of the gas turbine based on this data; a supply calculation module to acquire wind and solar condition data and determine the wind and solar supply value based on this data; and a hydrogen blending control module to predict the unit electricity price based on the current unit load demand value and wind and solar supply value, determine the unit hydrogen blending ratio based on the predicted electricity price, and perform hydrogen blending control (i.e., adjusting the hydrogen blending ratio of the gas turbine) based on the hydrogen blending ratio. This invention effectively improves the operating economy of gas turbine units by combining wind and solar condition data to predict unit electricity prices and then using these predicted prices to control hydrogen blending.

[0083] Through the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented in hardware or by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A control system for a hydrogen-blended gas turbine unit based on spot market trading, characterized in that, include: The demand calculation module is used to obtain historical unit operating data and determine the current unit load demand value of the gas turbine based on the historical unit operating data; The supply calculation module is used to acquire wind and solar conditions data and determine the wind and solar supply value based on the wind and solar conditions data. The hydrogen blending control module is used to predict the electricity price of the gas turbine unit based on the current unit load demand and wind and solar power supply, determine the hydrogen blending ratio of the gas turbine unit according to the predicted electricity price, and control the hydrogen blending of the gas turbine unit according to the hydrogen blending ratio.

2. The hydrogen-blended gas turbine control system based on spot market trading according to claim 1, characterized in that, The demand calculation module determines the current unit load demand value of the gas turbine unit based on historical unit operating data, including: Based on historical unit operating data, determine the operating data of each historical unit and the corresponding power generation of the gas turbine unit, and calculate the correlation coefficient between the operating data of each historical unit and the power generation of the gas turbine unit. Historical unit operation data with a correlation coefficient greater than the first preset threshold are selected, and key operating parameters of the gas turbine units are determined based on the selected historical unit operation data; The key operating parameters are normalized, and the load correction parameters are determined based on the normalized key operating parameters. Obtain the initial unit load demand value of the gas turbine unit, and correct the initial unit load demand value according to the load correction parameters to obtain the current unit load demand value of the gas turbine unit.

3. The hydrogen-blended gas turbine control system based on spot market trading according to claim 2, characterized in that, The determination of key operating parameters for gas turbine units based on the selected historical unit operating data includes: The historical unit operation data selected are sorted according to the magnitude of the correlation coefficient, and weight values ​​are assigned to each corresponding operation data according to the sorting results of the historical unit operation data. Obtain the change curve of the current unit operation data, perform curve fitting on the change curve of the current unit operation data, and obtain the fitting equation of the current unit operation data; The regression coefficients of the corresponding fitted equations are corrected according to the weight values ​​of each running data, and the predicted values ​​of the running data are determined based on the fitted equations after the regression coefficients are corrected. After normalizing the predicted values ​​of each operating data point, the summation is performed to obtain the key operating parameters of the gas turbine unit.

4. The hydrogen-blended gas turbine control system based on spot market trading according to claim 1, characterized in that, The supply calculation module determines the wind and solar supply value based on wind and solar condition data, including: Acquire changes in landscape conditions data and plot landscape condition change curves based on these changes. The wind and solar stability parameters are determined based on the wind and solar condition change curves, and the wind and solar supply values ​​are determined based on the wind and solar stability parameters.

5. The hydrogen-blended gas turbine control system based on spot market trading according to claim 4, characterized in that, The determination of wind and solar stability parameters based on wind and solar condition variation curves includes: A rolling time window is set according to a preset time period. The curve of changes in scenery conditions is divided according to the rolling time window to obtain several sub-curves. Calculate the average value of each sub-curve, and plot the average value curve based on the average value of each sub-curve; Filter out the peak values ​​and corresponding time periods in the average value change curve, and determine the interval between any two adjacent peak values ​​based on the peak values ​​and corresponding time periods in the average value change curve. Filter out the time intervals that are greater than the second preset threshold, obtain the difference between the maximum and minimum values ​​within the time intervals that are greater than the second preset threshold, calculate the average of all differences, and obtain the fluctuation deviation value. The number of time intervals exceeding the second preset threshold is counted, and the number of time intervals exceeding the second preset threshold is multiplied by the fluctuation deviation value to obtain the wind-solar stability parameter.

6. The hydrogen-blended gas turbine control system based on spot market trading according to claim 5, characterized in that, The process of determining the wind and solar supply value based on wind and solar stability parameters includes: Determine the range correction parameter based on the wind and light stability parameter, obtain the initial wind and light stability range, and multiply the range correction parameter by the initial wind and light stability range to obtain the wind and light stability range. Obtain the wind and solar power generation capacity within the stable range of wind and solar power, and determine the wind and solar power supply value based on the wind and solar power generation capacity within the stable range of wind and solar power.

7. The hydrogen-blended gas turbine control system based on spot market trading according to claim 6, characterized in that, The determination of the range correction parameters based on wind and solar stability parameters includes: The range correction parameter is determined according to the range correction factor calculation formula, which is as follows: Where R is the range correction coefficient, Ra is the initial range correction coefficient, Sa is the preset stability tolerance value, S is the wind and light stability parameter, and Q is the preset adjustment coefficient.

8. The hydrogen-blended gas turbine control system based on spot market trading according to claim 1, characterized in that, The hydrogen blending control module predicts the unit's electricity price based on the current unit load demand and wind / solar power supply, including: Obtain historical unit load demand values ​​and historical wind and solar power supply values ​​and corresponding unit electricity prices, and establish training and test sets based on historical unit load demand values, historical wind and solar power supply values ​​and corresponding unit electricity prices; An initial electricity price prediction model is established, and the initial electricity price prediction model is trained based on the training set and the test set to obtain a trained electricity price prediction model. Input the current unit load demand of the gas turbine and the supply of wind and solar power into the trained electricity price prediction model to obtain the predicted electricity price.

9. The hydrogen-blended gas turbine control system based on spot market trading according to claim 1, characterized in that, The hydrogen blending control module determines the hydrogen blending ratio of the unit based on the obtained predicted electricity price, including: Obtain the preset allowable value for electricity price, calculate the difference between the predicted electricity price and the preset allowable value for electricity price, and determine whether the difference between the predicted electricity price and the preset allowable value for electricity price is greater than the third preset threshold. If the difference between the predicted electricity price and the preset allowable electricity price is greater than the third preset threshold, then the first hydrogen blending ratio is set as the hydrogen blending ratio of the current unit. If the difference between the predicted electricity price and the preset allowable electricity price is less than or equal to the third preset threshold, then determine whether the difference between the predicted electricity price and the preset allowable electricity price is greater than the fourth preset threshold. If the difference between the predicted electricity price and the preset allowable electricity price is greater than the fourth preset threshold, then the second hydrogen blending ratio is set as the hydrogen blending ratio of the current unit. If the difference between the predicted electricity price and the preset allowable electricity price is less than or equal to the fourth preset threshold, then the third hydrogen blending ratio is set as the hydrogen blending ratio of the current unit.

10. A control method for hydrogen-blended gas turbine units based on spot market transactions, characterized in that, The method includes: Obtain historical unit operating data and determine the current unit load demand value of the gas turbine based on the historical unit operating data; Obtain wind and solar conditions data, and determine the wind and solar supply value based on the wind and solar conditions data; The electricity price of the gas turbine is predicted based on the current load demand and wind and solar power supply. The hydrogen blending ratio of the gas turbine is determined based on the predicted electricity price, and hydrogen blending control is carried out on the gas turbine based on the hydrogen blending ratio.

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