Photothermal power station power prediction method and device and storage medium

Abstract

The invention relates to a photo-thermal power station power prediction method and device, and belongs to the field of new energy, and the method comprises the steps: firstly, generating solar radiation prediction data according to meteorological statistical data and real-time meteorological forecast data through employing a meteorological data processing model; secondly, the corrected photo-thermal efficiency is determined according to the photo-thermal efficiency of the heat collector, the cleaning and maintenance plan, the cleanliness attenuation and the control strategy of the heat collector of the photo-thermal power station; then, accumulated heat is determined; and finally, determining a generated power prediction value of the photo-thermal power station according to the accumulated heat. According to the photoelectric station power prediction method, historical data are utilized, the learning processing capability of the pre-trained meteorological data processing model is utilized, influences of maintenance, attenuation, operation strategies and the like are considered, and the accuracy of power prediction of the photoelectric station is improved.

Description

Technical Field

[0001] The present invention belongs to the field of new energy, and in particular relates to a method, device and storage medium for predicting power of a solar thermal power station. Background Art

[0002] Trough CSP power stations have the dual attributes of new energy and traditional thermal power. Due to the configuration of heat storage systems, they can deeply participate in the frequency and peak regulation of the power grid, becoming a grid-friendly new energy power station. However, the heat source of trough CSP power stations is solar radiation, which fluctuates and even fluctuates violently, thus affecting the stability and planned operation of trough CSP power stations. The accuracy of power prediction of CSP power stations is very important for the normal operation of power station energy storage scheduling and power grid scheduling.

[0003] However, in the prior art, the prediction accuracy of the power of a CSP plant is not high. How to improve the accuracy of the power prediction of a CSP plant is a technical problem that needs to be solved urgently. Summary of the invention

[0004] In view of the above deficiencies in the prior art, the purpose of the invention is to provide a method and device for predicting power of a solar thermal power plant, thereby improving the accuracy of power prediction of a solar thermal power plant.

[0005] In a first aspect of the present invention, a method for predicting power of a solar thermal power station is proposed, comprising:

[0006] S1, obtaining meteorological statistical data and real-time meteorological forecast data, and generating solar radiation prediction data according to the meteorological statistical data and real-time meteorological forecast data;

[0007] S2, determining the corrected photothermal efficiency based on the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and the collector control strategy of the CSP plant;

[0008] S3, determining the accumulated heat according to the solar radiation prediction data and the corrected light-heat efficiency;

[0009] S4, determining a predicted value of the power generation of the CSP station according to the accumulated heat.

[0010] Furthermore, generating solar radiation prediction data according to meteorological statistical data and real-time meteorological forecast data in S1 includes:

[0011] Input meteorological statistical data and real-time meteorological forecast data into the pre-trained meteorological data processing model to generate solar radiation forecast data for N consecutive days;

[0012] Wherein, N is an integer greater than or equal to 3 and less than or equal to 7;

[0013] The pre-trained meteorological data processing model is a meteorological data processing model trained with historical meteorological data and solar radiation data.

[0014] Furthermore, the corrected photothermal efficiency is determined according to the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and the control strategy of the collector of the photothermal power station, including:

[0015] Determine the corrected photothermal efficiency η according to the following formula m :

[0016] η m =η0*F c *F s ;

[0017] Among them, η0 is the solar thermal efficiency of the collector based on theoretical calculation, F c F is the comprehensive cleaning factor considering cleaning speed and cleanliness attenuation. s is the decrease factor of CSP efficiency affected by the power station maintenance plan and the collector control strategy of the trough CSP power station.

[0018] Further, the cumulative heat is determined based on the solar radiation prediction data and the corrected light-heat efficiency, including:

[0019] Determine the collector field power based on solar radiation forecast data and corrected photothermal efficiency;

[0020] Determine the accumulated heat according to the collector field power;

[0021] The collector field power is determined according to the following formula:

[0022] P SF =DNI×A SF ×η m ×F ptc ;

[0023] Among them, P SF is the collector field power, DNI is the solar radiation prediction data, A SF is the effective collector area of ​​the collector field, η m is the corrected photothermal efficiency, F ptc is the loss factor affected by time.

[0024] Furthermore, determining the predicted value of the power generation of the CSP station based on the accumulated heat includes:

[0025] Determine the temperature and flow rate of the heat transfer medium according to the system design parameters, the heat transfer medium physical property database and the heat collection field power;

[0026] Determining the amount of heat consumed by the collector field when it changes from a first temperature to a second temperature, wherein the second temperature is higher than the first temperature;

[0027] Determine the thermal power and heat entering the power generation area;

[0028] The predicted value of the power generation power of the solar thermal power station is determined according to the power station status database, the operation strategy database and the thermal power and heat entering the power generation area.

[0029] Further, determining the predicted value of the power generation power of the solar thermal power station according to the temperature and flow of the heat transfer medium, the power station status database, the operation strategy database and the thermal power and heat entering the power generation area includes:

[0030] Determine the predicted power generation value P according to the following formula e :

[0031] P e =P t_PB ×η et ×F st ;

[0032] Where: P t_PB is the thermal power entering the power generation area; η et is the cycle efficiency based on the power station status database; F st It is the factor affecting the cycle efficiency based on the operation strategy;

[0033] The cycle efficiency η et Related to the temperature and flow rate of the heat transfer medium.

[0034] Furthermore, the photovoltaic thermal power station power prediction method of the present invention further includes:

[0035] Determine the predicted value of the power and heat of the heat storage according to the power station status database, the operation strategy database and the thermal power and heat entering the power generation area;

[0036] The power prediction value P of the heat storage t_TES Determined according to the following formula:

[0037] P t_TES =P t_SF -P t_PB ;

[0038] Where: P t_SF is the collector field output power, P t_PB is the power entering the power generation area, P t_TES is the predicted value of power entering the heat storage;

[0039] The predicted heat value of heat storage is determined according to the following formula:

[0040] H t_TES =H t_SF -H t_PB ;

[0041] Where: H t_SF is the heat output of the collector field, H t_PB is the heat entering the power generation area, Ht_TES is the predicted value of heat entering the heat storage.

[0042] A second aspect of the present invention provides a device for implementing a method for predicting power of a solar thermal power station, comprising:

[0043] A solar radiation prediction module is configured to obtain meteorological statistical data and real-time meteorological forecast data, and generate solar radiation prediction data according to the meteorological statistical data and real-time meteorological forecast data;

[0044] A thermal efficiency calculation module, configured to determine a corrected photothermal efficiency according to the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and a control strategy of the collector of the photothermal power station;

[0045] A cumulative heat calculation module, configured to determine the cumulative heat according to the solar radiation prediction data and the corrected photothermal efficiency;

[0046] The power prediction module is configured to determine a predicted value of power generation of the solar thermal power station according to the accumulated heat.

[0047] A third aspect of the present invention provides a device for implementing a method for predicting power of a solar thermal power station, comprising: a memory, a processor, and a user interface;

[0048] Memory for storing computer programs;

[0049] User interface, used to interact with users;

[0050] The processor is used to read the computer program in the memory, and when the processor executes the computer program, the above-mentioned method for predicting power of a solar thermal power station is implemented.

[0051] In a fourth aspect of the present invention, a processor-readable storage medium is provided, wherein the processor-readable storage medium stores a computer program, and when the processor executes the computer program, the above-mentioned method for predicting power of a solar thermal power station is implemented.

[0052] The beneficial effects of the present invention are as follows:

[0053] The method and device for predicting the power of a solar thermal power station described in the present invention generate solar radiation prediction data through meteorological statistical data and weather forecast data, and then determine the corrected photothermal efficiency in combination with the photothermal efficiency of the collector, the cleaning and maintenance plan, the cleanliness attenuation and the control strategy of the collector of the solar thermal power station, and then determine the cumulative heat according to the solar radiation prediction data and the corrected photothermal efficiency, and finally determine the predicted value of the power generation of the solar thermal power station according to the cumulative heat. The method of the present invention inputs meteorological statistical data and weather forecast data into a meteorological data processing model to obtain solar radiation prediction data, making the solar radiation prediction data more accurate. The influence of the maintenance work of the collector on the thermal efficiency is then comprehensively considered, thereby further improving the accuracy of the prediction of the power generation of the solar thermal power station. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are only used to illustrate specific embodiments and are not considered to limit the present invention. In the entire drawings, the same reference symbols represent the same components. Obviously, the drawings described below are only some embodiments recorded in the embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0055] Figure 1 This is a flow chart of a method for predicting power of a solar thermal power station according to an embodiment of the present invention;

[0056] Figure 2 Schematic diagram of data relationships related to an embodiment of the present invention.

[0057] Figure 3 Schematic diagram of a power prediction device for a solar thermal power station according to an embodiment of the present invention

[0058] Figure 4 This is another schematic diagram of power prediction for a solar thermal power station according to an embodiment of the present invention.

[0059] Reference numerals:

[0060] S1, step 1; S2, step 2; S3, step 3; S4, step 4; 201, meteorological statistical data; 202, real-time meteorological forecast data; 203, solar radiation prediction data; 204, corrected photothermal efficiency; 205, accumulated heat; 206, system state parameters; 207, operation strategy; 207, power generation power prediction value; 301, solar radiation prediction module; 302, thermal efficiency calculation module; 303, accumulated heat calculation module; 304, prediction module; 401, processor; 402, memory; 403 user interface. DETAILED DESCRIPTION

[0061] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making creative work should fall within the scope of protection of the present invention.

[0062] Furthermore, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily obscuring the concepts disclosed in the present invention.

[0063] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the orientation or position relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. The terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0064] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of methods and systems consistent with some aspects of the present invention as detailed in the appended claims.

[0065] Solar thermal power stations (such as trough solar thermal power stations) have the dual attributes of new energy and traditional thermal power. Due to the configuration of heat storage systems, they can deeply participate in the frequency and peak regulation of the power grid, becoming a grid-friendly new energy power station. Since solar radiation fluctuates or even fluctuates violently, it affects the stability and planned operation of trough solar thermal power stations. The accuracy of power prediction of solar thermal power stations is very important for the normal operation of power station energy storage scheduling and power grid scheduling, and is one of the important conditions for successful grid connection.

[0066] It should be noted that, in the present invention, the CSP power station is a trough CSP power station, and may also be other types of CSP power stations, such as a Fresnel CSP power station.

[0067] In the prior art, the heat source of a trough CSP power station is solar radiation, which fluctuates and even fluctuates violently, thus affecting the stability and planned operation of the trough CSP power station. The accuracy of the power prediction of a CSP power station is very important for the normal operation of the power station energy storage dispatch and the grid dispatch. However, in the prior art, the accuracy of the power prediction of a CSP power station is not high. How to improve the accuracy of the power prediction of a CSP power station is a technical problem that needs to be solved urgently.

[0068] In view of the problems existing in the above-mentioned prior art, the present invention proposes a method, device and storage medium for predicting power of a solar thermal power station, which improves the accuracy of power prediction of a solar thermal power station.

[0069] In a first aspect, the present invention provides a method for predicting power of a solar thermal power station, such as Figure 1 As shown, specifically, the method includes steps S1 to S4.

[0070] S1, obtaining meteorological statistical data and real-time meteorological forecast data, and generating solar radiation prediction data according to the meteorological statistical data and real-time meteorological forecast data;

[0071] S2, determining the corrected photothermal efficiency based on the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and the collector control strategy of the CSP plant;

[0072] S3, determining the accumulated heat according to the solar radiation prediction data and the corrected light-heat efficiency;

[0073] S4, determining a predicted value of the power generation of the CSP station according to the accumulated heat.

[0074] The power prediction method of the solar thermal power station of the present invention utilizes the relationship between historical meteorological data and solar radiation, and combines real-time meteorological forecast data to improve the accuracy of solar radiation prediction data. At the same time, the current photothermal efficiency value of the solar thermal power station collector, the influence of cleanliness and maintenance plan on power generation, the influence of collector cleanliness attenuation on power generation, and the influence of collector control strategy on power generation are also considered, and multiple factors are combined to predict the power generation, so as to more accurately predict the power generation.

[0075] In the present invention, the process of predicting the power generation by combining the above multiple factors will use relevant data, and the relationship between these data is as follows: Figure 2 As shown:

[0076] Meteorological statistical data 201 is historical meteorological statistical data. According to the natural regularity between meteorological statistical data and solar radiation, factors such as season, weather, temperature, cloud cover, etc. will directly or indirectly affect the intensity of solar radiation. Therefore, historical meteorological statistical data is very important for the prediction of direct solar radiation. The natural regularity between historical meteorological data and direct solar radiation can be obtained through the meteorological data processing model.

[0077] Real-time weather forecast data 202, there is also a certain regularity between real-time weather forecast data and solar radiation. In the present invention, based on typical annual weather data, the relationship between weather forecast, cloud content and direct solar radiation is established, so that direct solar radiation can be obtained by using weather forecast prediction. The relationship between weather forecast, cloud content and direct solar radiation can also be obtained through a weather data processing model.

[0078] Solar radiation prediction data 203 is obtained by inputting the meteorological statistical data 201 and the real-time meteorological forecast data 202 into a pre-trained meteorological data processing model to obtain solar radiation prediction data 203 .

[0079] As an optional example, meteorological statistical data and real-time meteorological forecast data are input into a pre-trained meteorological data processing model to generate solar radiation forecast data for consecutive N days;

[0080] Wherein, N is an integer greater than or equal to 3 and less than or equal to 7;

[0081] As an optional example, the pre-trained meteorological data processing model is a meteorological data processing model trained with historical meteorological data and solar radiation data. The model can be an artificial intelligence large model or a dedicated model for meteorological data processing. After pre-training, the pre-trained meteorological data processing model can learn the relationship between historical meteorological data and solar radiation data. After the training is completed, when a set of meteorological data is input, the corresponding predicted value of solar radiation data can be output.

[0082] As a preferred example, the predicted value of solar radiation data is solar radiation prediction data for N consecutive days, where N is an integer greater than or equal to 3 and less than or equal to 7.

[0083] Corrected photothermal efficiency 204, which is the photothermal efficiency corrected based on statistical data. In the present invention, based on the theoretical calculation of the photothermal efficiency of the parabolic trough solar thermal power station collector, and considering cleaning, planned maintenance, cleanliness attenuation, and parabolic trough solar thermal power station collector control strategy, the photothermal efficiency corrected based on statistical data is obtained.

[0084] As an optional example, the corrected photothermal efficiency may be determined according to the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and the control strategy of the collector of the photothermal power station:

[0085] Determine the corrected photothermal efficiency η according to the following formula m :

[0086] η m =η0*F c *F s ;

[0087] Among them, η0 is the solar thermal efficiency of the collector based on theoretical calculation, F c F is the comprehensive cleaning factor considering cleaning speed and cleanliness attenuation. s is the decrease factor of CSP efficiency affected by the power station maintenance plan and the collector control strategy of the trough CSP power station.

[0088] The collector photothermal efficiency η0 is the collector photothermal efficiency based on theoretical calculation, including the optical properties of the reflector and the collector tube, loss factors such as cosine loss, shadow loss, and end loss affected by the position of the sun, as well as the incident angle correction coefficient and the heat dissipation loss affected by wind speed.

[0089] Photothermal efficiency reduction factor F s It is the factor of the decrease of the photothermal efficiency under the influence of the power station maintenance plan and the control strategy of the parabolic trough solar thermal power station collector. In the present invention, the control strategy of the parabolic trough solar thermal power station collector refers to the way in which the collector is required to operate in order to achieve the power station's power generation, energy storage and other operating goals.

[0090] Accumulated heat 205. The accumulated heat 205 is determined according to the solar radiation prediction data 203 and the corrected light-heat efficiency 204. As an optional example, the following steps may be performed:

[0091] Determine the collector field power based on solar radiation forecast data and corrected photothermal efficiency;

[0092] The accumulated heat is determined based on the collector field power.

[0093] As an optional example, the power of the solar field can be determined based on the solar radiation prediction data and the corrected photothermal efficiency:

[0094] The thermal field power is determined according to the following formula:

[0095] P SF =DNI×A SF ×η m ×F pt c;

[0096] Among them, P SF is the collector field power, DNI is the solar radiation prediction data, A SF is the effective collector area of ​​the collector field, η m is the corrected photothermal efficiency, Fptc is the loss factor affected by time.

[0097] Among them, F ptc It is the loss factor affected by time taking into account factors such as cosine loss.

[0098] System state parameters 206 and operation strategy 207. In the present invention, the system state parameters 206 are obtained from the trough power plant system state parameter database. The operation strategy 207 is obtained from the operation strategy database.

[0099] As an optional example, the system status parameters include equipment availability, system efficiency, system temperature and pressure, initial liquid level of the heat storage system, etc. Operation strategies include full power generation, low power generation, pure collector field power generation, multi-heat source coupled power generation, etc.

[0100] Power generation prediction value 207. As an optional example, the power generation prediction value 207 of the solar thermal power station is determined according to the accumulated heat, which may be:

[0101] Determine the temperature and flow rate of the heat transfer medium based on the system design parameters, the heat transfer medium physical property database and the collector field power;

[0102] Determining the amount of heat consumed by the collector field when it changes from a first temperature to a second temperature, wherein the second temperature is higher than the first temperature;

[0103] Determine the thermal power and heat entering the power generation area;

[0104] The predicted value 207 of the power generation power of the CSP power station is determined according to the temperature and flow of the heat transfer medium, the power station status database, the operation strategy database, and the thermal power and heat entering the power generation area.

[0105] In the present invention, the power generation area is also referred to as a power island. The thermal power and heat entering the power generation area can be determined based on the heat transfer from the collector field to the power island, the accumulated heat, and the heat consumed by the collector field from the first temperature to the second temperature. In the present invention, the first temperature can be 100°C to 250°C, and the second temperature can be 260°C to 330°C.

[0106] As an optional example, determining the predicted value 207 of the power generation power of the solar thermal power station according to the temperature and flow of the heat transfer medium, the power station status database, the operation strategy database, and the thermal power and heat entering the power generation area includes:

[0107] Determine the predicted power generation value P according to the following formula e :

[0108] P e =P t_PB ×η et ×F st ;

[0109] Where: P t_PB is the thermal power entering the power generation area; η et is the cycle efficiency based on the power station status database; F st It is the factor affecting the cycle efficiency based on the operation strategy;

[0110] Cycle efficiency η et Related to the temperature and flow rate of the heat transfer medium.

[0111] It should be noted that the cumulative value of the predicted power generation value should converge to the heat entering the power generation area, that is, satisfy the following formula:

[0112]

[0113] Where: t s is the start time, t e is the end time. t_PB is the amount of heat entering the power generation area from the start time to the end time.

[0114] As an optional example, the method for predicting power of a solar thermal power station of the present invention further includes:

[0115] Determine a power prediction value of heat storage and a heat prediction value of heat storage according to a power station status database, an operation strategy database, and the thermal power and heat entering the power generation area;

[0116] The power prediction value P of the heat storage t_TES Determined according to the following formula:

[0117] P t_TES =P t_SF -Pt _PB ;

[0118] Where: P t_SF is the collector field output power, P t_PB is the power entering the power generation area, P t_TES is the predicted value of power entering the heat storage;

[0119] The predicted heat value of the heat storage is determined according to the following formula:

[0120] H t_TES =H t_SF -H t_PB ;

[0121] Where: H t_SF is the heat output of the collector field, H t_PB is the heat entering the power generation area, H t_TES is the predicted value of heat entering the heat storage.

[0122] It should be noted that P t_TESis the power prediction value entering the heat storage, and this prediction value is always less than or equal to the maximum power allowed by the heat storage. t_TES It is the predicted value of heat entering the heat storage, and the predicted value is always less than or equal to the maximum heat storage capacity allowed by the heat storage. It is related to the temperature of the heat transfer medium and is also limited by the liquid level of the heat storage system.

[0123] By the power prediction method of the solar thermal power station of the present invention, the solar radiation prediction data is generated by meteorological statistical data and weather forecast data, and the corrected photothermal efficiency is determined by combining the photothermal efficiency of the collector, the cleaning and maintenance plan, the cleanliness attenuation and the control strategy of the collector of the solar thermal power station, and then the cumulative heat is determined according to the solar radiation prediction data and the corrected photothermal efficiency, and finally the predicted value of the power generation of the solar thermal power station is determined according to the cumulative heat. The method of the present invention inputs the meteorological statistical data and the weather forecast data into the meteorological data processing model to obtain the solar radiation prediction data, so that the solar radiation prediction data is more accurate. Then the influence of the maintenance work of the collector on the thermal efficiency is comprehensively considered, thereby further improving the accuracy of the prediction of the power generation of the solar thermal power station.

[0124] In the second aspect, based on the same inventive concept, another specific embodiment of the present invention discloses a power prediction device for a solar thermal power station, such as Figure 3 As shown, including:

[0125] The solar radiation prediction module 301 is configured to obtain meteorological statistical data and real-time meteorological forecast data, and generate solar radiation prediction data according to the meteorological statistical data and the real-time meteorological forecast data;

[0126] The thermal efficiency calculation module 302 is configured to determine the corrected photothermal efficiency according to the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and the control strategy of the collector of the photothermal power station;

[0127] The cumulative heat calculation module 303 is configured to determine the cumulative heat according to the solar radiation prediction data and the corrected light-heat efficiency;

[0128] The power prediction module 304 is configured to determine a predicted value of power generation of the CSP station according to the accumulated heat.

[0129] As an optional example, the solar radiation prediction module 301 is further configured to input meteorological statistical data and real-time meteorological forecast data into a pre-trained meteorological data processing model to generate solar radiation prediction data for N consecutive days;

[0130] Wherein, N is an integer greater than or equal to 3 and less than or equal to 7;

[0131] The pre-trained meteorological data processing model is a meteorological data processing model trained with historical meteorological data and solar radiation data.

[0132] As an optional example, the thermal efficiency calculation module 302 is further configured to calculate the thermal efficiency according to the following formula:

[0133] The corrected photothermal efficiency η is determined by m :

[0134] η m =η0*F c *F s ;

[0135] Among them, η0 is the solar thermal efficiency of the collector based on theoretical calculation, F c F is the comprehensive cleaning factor considering cleaning speed and cleanliness attenuation. s is the decrease factor of CSP efficiency affected by the power station maintenance plan and the collector control strategy of the trough CSP power station.

[0136] As an optional example, the cumulative heat calculation module 303 is further configured to determine the power of the solar collector field according to the solar radiation prediction data and the corrected photothermal efficiency; and determine the cumulative heat according to the solar collector field power.

[0137] As an optional example, the power of the solar field can be determined based on the solar radiation prediction data and the corrected photothermal efficiency:

[0138] The thermal field power is determined according to the following formula:

[0139] P SF =DNI×A SF ×η m ×F ptc ;

[0140] Among them, P SF is the collector field power, DNI is the solar radiation prediction data, A SF is the effective collector area of ​​the collector field, η m is the corrected photothermal efficiency, F ptc is the loss factor affected by time.

[0141] Among them, F ptc The power prediction module 304 is a loss factor that takes into account the time influence of factors such as cosine loss. As an optional example, the power prediction module 304 is also configured to:

[0142] Determine the temperature and flow rate of the heat transfer medium according to the system design parameters, the heat transfer medium physical property database and the heat collection field power;

[0143] Determining the amount of heat consumed by the heat collecting field when the heat collecting field changes from a first temperature to a second temperature, wherein the second temperature is higher than the first temperature;

[0144] Determine the thermal power and heat entering the power generation area;

[0145] The predicted value of the CSP power generation capacity is determined based on the temperature and flow of the heat transfer medium, the power station status database, the operation strategy database, and the thermal power and heat entering the power generation area.

[0146] Among them, the power generation prediction value P is determined according to the following formula: e :

[0147] P e =P t_PB ×η et ×F st ;

[0148] Where: P t_PB is the thermal power entering the power generation area; η et is the cycle efficiency based on the power plant status database; F st It is the factor affecting the cycle efficiency based on the operation strategy;

[0149] Among them, the cycle efficiency η et Related to the temperature and flow rate of the heat transfer medium.

[0150] As an optional example, the power prediction module 304 is further configured to:

[0151] Determine the power prediction value and the heat prediction value of the heat storage according to the power station status database, the operation strategy database and the thermal power and heat entering the power generation area;

[0152] Thermal storage power prediction value P t_TES Determined according to the following formula:

[0153] P t_TES =P t_SF -P t_PB ;

[0154] Where: P t_SF is the collector field output power, P t_PB is the power entering the power generation area, P t_TES is the predicted value of power entering the heat storage;

[0155] The predicted heat value of heat storage is determined according to the following formula:

[0156] H t_TES =H t_SF -H t_PB ;

[0157] Where: H t_SF is the heat output of the collector field, H t_PB is the heat entering the power generation area, H t_TES is the predicted value of heat entering the heat storage.

[0158] It should be noted that the solar radiation prediction module 301 of the present device embodiment implements all the methods of the above method embodiment S1, solves the same technical problems, and achieves the same technical effects, and the similarities will not be repeated here.

[0159] It should be noted that the thermal efficiency calculation module 302 of the present device embodiment implements all the methods of the above method embodiment S2, solves the same technical problems, and achieves the same technical effects, and the similarities will not be repeated here.

[0160] It should be noted that the cumulative heat calculation module 303 of the present device embodiment implements all the methods of the above method embodiment S3, solves the same technical problems, and achieves the same technical effects, and the similarities will not be repeated.

[0161] It should be noted that the power prediction module 304 of the present device embodiment implements all the methods of the above method embodiment S4, solves the same technical problems, and achieves the same technical effects, and the similarities will not be repeated here.

[0162] In the third aspect, based on the same inventive concept, the present invention proposes a power prediction device for a solar thermal power station, such as Figure 4 As shown, it includes: a memory 402 and one or more processors 401.

[0163] The memory 402 stores one or more application programs, and the one or more application programs are suitable for being executed by the one or more processors 401 to implement:

[0164] S1, obtaining meteorological statistical data and real-time meteorological forecast data, and generating solar radiation prediction data according to the meteorological statistical data and real-time meteorological forecast data;

[0165] S2, determining the corrected photothermal efficiency based on the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and the collector control strategy of the CSP plant;

[0166] S3, determining the cumulative heat according to the solar radiation prediction data and the corrected light-heat efficiency;

[0167] S4, determining a predicted value of power generation of the solar thermal power station according to the accumulated heat.

[0168] like Figure 4 As shown, it includes: a processor 401 and a memory 402. The processor 401 and the memory 402 are connected, for example, through a bus interface.

[0169] The structure of the device does not constitute a limitation on the embodiments of the present invention.

[0170] Processor 401 may be a CPU, a general purpose processor, a DSP, an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 401 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0171] The bus interface may include a path to transfer information between the above components. The bus interface may be a PCI bus or an EISA bus, etc. The bus interface may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0172] The memory 402 may be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, or an EEPROM, a CD-ROM or other optical disk storage, an optical disk storage (including a compressed optical disk, a laser disk, an optical disk, a digital versatile disk, a Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0173] As an optional example, when the one or more application programs stored in the memory 402 are executed by the one or more processors 401, the following is achieved:

[0174] Inputting the meteorological statistical data and real-time meteorological forecast data into a pre-trained meteorological data processing model to generate solar radiation forecast data for consecutive N days;

[0175] Wherein, N is an integer greater than or equal to 3 and less than or equal to 7;

[0176] The pre-trained meteorological data processing model is a meteorological data processing model trained with historical meteorological data and solar radiation data.

[0177] As an optional example, when the one or more application programs stored in the memory 402 are executed by the one or more processors 401, the following is achieved:

[0178] Determine the corrected photothermal efficiency η according to the following formula m :

[0179] η m =η0*F c *F s ;

[0180] Among them, η0 is the solar thermal efficiency of the collector based on theoretical calculation, F c F is the comprehensive cleaning factor considering cleaning speed and cleanliness attenuation. s is the decrease factor of CSP efficiency affected by the power station maintenance plan and the collector control strategy of the trough CSP power station.

[0181] As an optional example, when the one or more application programs stored in the memory 402 are executed by the one or more processors 401, the following is achieved:

[0182] Determine the power of the solar collector field according to the solar radiation prediction data and the corrected photothermal efficiency;

[0183] The accumulated heat is determined according to the collector field power.

[0184] As an optional example, the power of the solar field can be determined based on the solar radiation prediction data and the corrected photothermal efficiency:

[0185] The thermal field power is determined according to the following formula:

[0186] P SF =DNI×A SF ×η m ×F ptc ;

[0187] Among them, P SF is the collector field power, DNI is the solar radiation prediction data, A SF is the effective collector area of ​​the collector field, η m is the corrected photothermal efficiency, F ptc is the loss factor affected by time.

[0188] Among them, F ptc It is the loss factor affected by time taking into account factors such as cosine loss.

[0189] As an optional example, when the one or more application programs stored in the memory 402 are executed by the one or more processors 401, the following is achieved:

[0190] Determine the temperature and flow rate of the heat transfer medium according to the system design parameters, the heat transfer medium physical property database and the heat collection field power;

[0191] Determining the amount of heat consumed by the heat collecting field when the heat collecting field changes from a first temperature to a second temperature, wherein the second temperature is higher than the first temperature;

[0192] Determine the thermal power and heat entering the power generation area;

[0193] The predicted value of the power generation power of the solar thermal power station is determined according to the temperature and flow of the heat transfer medium, the power station status database, the operation strategy database and the thermal power and heat entering the power generation area.

[0194] As an optional example, when the one or more application programs stored in the memory 402 are executed by the one or more processors 401, the following is achieved:

[0195] Determine the predicted power generation value P according to the following formula e :

[0196] P e =P t_PB ×η et ×F st ;

[0197] Where: P t_PB is the thermal power entering the power generation area; η et is the cycle efficiency based on the power plant status database; F st It is the factor affecting the cycle efficiency based on the operation strategy;

[0198] The cycle efficiency η et Related to the temperature and flow rate of the heat transfer medium.

[0199] As an optional example, when the one or more application programs stored in the memory 402 are executed by the one or more processors 401, the following is achieved:

[0200] Determine a power prediction value of heat storage and a heat prediction value of heat storage according to a power station status database, an operation strategy database, and the thermal power and heat entering the power generation area;

[0201] The power prediction value P of the heat storage t_TES Determined according to the following formula:

[0202] P t_TES =P t_SF -P t_PB ;

[0203] Where: P t_SF is the collector field output power, P t_PB is the power entering the power generation area, P t_TES is the predicted value of power entering the heat storage;

[0204] The predicted heat value of the heat storage is determined according to the following formula:

[0205] H t_TES =H t_SF -H t_PB ;

[0206] Where: H t_SFis the heat output of the collector field, H t_PB is the heat entering the power generation area, H t_TES is the predicted value of heat entering the heat storage.

[0207] It should be noted that the power prediction device for a solar thermal power station of the present invention and the power prediction method for a solar thermal power station of the first aspect belong to the same inventive concept, solve the same technical problems, and achieve the same technical effects, and the similarities will not be repeated here.

[0208] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program can be loaded and executed by a processor according to the method for predicting power of a solar thermal power station described in the first aspect.

[0209] The applicant of the present invention has made a detailed explanation and description of the implementation examples of the present invention in conjunction with the drawings in the specification. However, those skilled in the art should understand that the above implementation examples are only preferred implementation schemes of the present invention, and the detailed description is only to help readers better understand the spirit of the present invention, but not to limit the scope of protection of the present invention. On the contrary, any improvements or modifications based on the inventive spirit of the present invention should fall within the scope of protection of the present invention.

[0210] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the above embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or replacements that can be easily thought of by those skilled in the art within the technical scope disclosed in the present invention should be covered within the protection scope of the present invention.

[0211] The applicant of the present invention has made a detailed explanation and description of the implementation examples of the present invention in conjunction with the drawings in the specification. However, those skilled in the art should understand that the above implementation examples are only preferred implementation schemes of the present invention, and the detailed description is only to help readers better understand the spirit of the present invention, but not to limit the scope of protection of the present invention. On the contrary, any improvements or modifications based on the inventive spirit of the present invention should fall within the scope of protection of the present invention.

[0212] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the above embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or replacements that can be easily thought of by those skilled in the art within the technical scope disclosed in the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for predicting power of a solar thermal power station, characterized in that: include: S1, obtaining meteorological statistical data and real-time meteorological forecast data, and generating solar radiation prediction data according to the meteorological statistical data and real-time meteorological forecast data; S2, determining the corrected photothermal efficiency based on the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and the collector control strategy of the CSP plant; S3, determining the cumulative heat according to the solar radiation prediction data and the corrected light-heat efficiency; S4, determining a predicted value of power generation of the solar thermal power station according to the accumulated heat.

2. A method for predicting power of a solar thermal power station according to claim 1, characterized in that: Generating solar radiation prediction data according to the meteorological statistical data and the real-time meteorological forecast data in S1 includes: Inputting the meteorological statistical data and real-time meteorological forecast data into a pre-trained meteorological data processing model to generate solar radiation forecast data for consecutive N days; Wherein, N is an integer greater than or equal to 3 and less than or equal to 7; The pre-trained meteorological data processing model is a meteorological data processing model trained with historical meteorological data and solar radiation data.

3. A method for predicting power of a solar thermal power station according to claim 1, characterized in that: Determining the corrected photothermal efficiency according to the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and the control strategy of the photothermal power station collector as described in S2 includes: Determine the corrected photothermal efficiency η according to the following formula m : or m =η0*F c *F s ; Among them, η0 is the solar thermal efficiency of the collector based on theoretical calculation, F c F is the comprehensive cleaning factor considering cleaning speed and cleanliness attenuation. s is the decrease factor of CSP efficiency affected by the power station maintenance plan and the collector control strategy of the trough CSP power station.

4. A method for predicting power of a CSP plant according to claim 2, characterized in that: Determining the accumulated heat according to the solar radiation prediction data and the corrected light-heat efficiency comprises: Determine the power of the solar collector field according to the solar radiation prediction data and the corrected photothermal efficiency; Determining the accumulated heat according to the collector field power; The collector field power is determined according to the following formula: P SF =DNI×A SF ×η m ×F ptc ; Among them, P SF is the collector field power, DNI is the solar radiation prediction data, A SF is the effective collector area of ​​the collector field, η m is the corrected photothermal efficiency, F ptc is the loss factor affected by time.

5. A method for predicting power of a CSP plant according to claim 4, characterized in that: Determining the predicted value of the power generation power of the CSP station according to the accumulated heat comprises: Determine the temperature and flow rate of the heat transfer medium according to the system design parameters, the heat transfer medium physical property database and the heat collection field power; Determining the amount of heat consumed by the heat collecting field when the heat collecting field changes from a first temperature to a second temperature, wherein the second temperature is higher than the first temperature; Determine the thermal power and heat entering the power generation area; The predicted value of the power generation power of the solar thermal power station is determined according to the temperature and flow of the heat transfer medium, the power station status database, the operation strategy database and the thermal power and heat entering the power generation area.

6. A method for predicting power of a CSP plant according to claim 5, characterized in that: Determining the predicted value of the power generation power of the CSP power station according to the temperature and flow of the heat transfer medium, the power station status database, the operation strategy database, and the thermal power and heat entering the power generation area includes: Determine the predicted power generation value P according to the following formula e : P e =P t_PB ×η et ×F st ; Where: P t_PB is the thermal power entering the power generation area; η et is the cycle efficiency based on the power plant status database; F st It is the factor affecting the cycle efficiency based on the operation strategy; The cycle efficiency η et Related to the temperature and flow rate of the heat transfer medium.

7. A method for predicting power of a CSP plant according to claim 5, characterized in that: Also includes: Determine a power prediction value of heat storage and a heat prediction value of heat storage according to a power station status database, an operation strategy database, and the thermal power and heat entering the power generation area; The power prediction value P of the heat storage t_TES Determined according to the following formula: P t_TES =P t_SF -P t_PB ; Where: P t_SF is the collector field output power, P t_PB is the power entering the power generation area, P t_TES is the predicted value of power entering the heat storage; The predicted heat value of the heat storage is determined according to the following formula: H t_TES =H t_SF -H t_PB ; Where: H t_SF is the heat output of the collector field, H t_PB is the heat entering the power generation area, H t_TES is the predicted value of heat entering the heat storage.

8. A power prediction device for a solar thermal power station, characterized in that: Used to implement the method for predicting power of a solar thermal power station according to any one of claims 1 to 7, the device comprises: A solar radiation prediction module is configured to obtain meteorological statistical data and real-time meteorological forecast data, and generate solar radiation prediction data according to the meteorological statistical data and real-time meteorological forecast data; A thermal efficiency calculation module, configured to determine a corrected photothermal efficiency according to the collector photothermal efficiency, cleaning and maintenance plan, cleanliness attenuation and a control strategy of the collector of the photothermal power station; A cumulative heat calculation module, configured to determine the cumulative heat according to the solar radiation prediction data and the corrected photothermal efficiency; The power prediction module is configured to determine a predicted value of power generation of the solar thermal power station according to the accumulated heat.

9. A power prediction device for a solar thermal power station, characterized in that: including a memory, a processor and a user interface; The memory is used to store computer programs; The user interface is used to interact with the user; The processor is used to read the computer program in the memory, and when the processor executes the computer program, the method for predicting power of a solar thermal power station according to any one of claims 1 to 7 is implemented.

10. A processor-readable storage medium, characterized in that The processor-readable storage medium stores a computer program, and when the processor executes the computer program, the method for predicting power of a solar thermal power station according to any one of claims 1 to 11 is implemented.

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