Operation prediction method and device for multi-energy complementary system

Abstract

The invention relates to an operation prediction method and device for a multi-energy complementary system, and belongs to the technical field of multi-energy complementary systems, and the method comprises the steps: obtaining meteorological statistical data and real-time meteorological forecast data, and generating meteorological forecast data according to the meteorological statistical data and the real-time meteorological forecast data; determining a power generation power prediction value of the photo-thermal power station according to the meteorological prediction data of different time types, and determining power generation power prediction values of other energy points; determining an operation strategy based on the generated power prediction value of the photo-thermal power station, the generated power prediction values of other energy points and historical operation data; and visualizing and displaying the running strategy. According to the method, stable, efficient and economical operation of the multi-energy complementary system is realized.

Description

Technical Field

[0001] This invention belongs to the field of multi-energy complementary system technology, and particularly relates to a method and apparatus for predicting the operation of multi-energy complementary systems. Background Technology

[0002] Under the new power system, the proportion of photovoltaic (PV) and wind power generation is gradually increasing, resulting in a lack of rotational inertia in the power grid. Simultaneously, the instability of PV and wind power generation poses a significant impact on the grid, especially given the simultaneous and peak-shaving characteristics of PV. Concentrated solar power (CSP) plants, however, combine the green attributes of new energy with the flexible regulation attributes of traditional thermal power. With the configuration of long-term thermal storage systems, they can deeply participate in grid frequency and peak regulation, playing a crucial role in multi-energy complementary new energy power grids. Therefore, how to better achieve operational prediction for multi-energy complementary systems has become an urgent problem to be solved. Summary of the Invention

[0003] In view of the shortcomings of the prior art, the purpose of the invention is to provide a method and device for predicting the operation of a multi-energy complementary system.

[0004] In a first aspect, the present invention proposes a method for predicting the operation of a multi-energy complementary system, comprising: S1, acquiring meteorological statistical data and real-time meteorological forecast data, and generating meteorological forecast data based on the meteorological statistical data and the real-time meteorological forecast data; S2, determining the predicted power generation value of a solar thermal power plant and the predicted power generation value of other energy points based on the meteorological forecast data of different time types; S3, determining an operation strategy based on the predicted power generation value of the solar thermal power plant, the predicted power generation value of the other energy points, and historical operation data; and S4, visualizing and displaying the operation strategy.

[0005] Furthermore, determining the predicted power generation value of the solar thermal power plant based on the meteorological forecast data of different time types includes: determining the corrected solar thermal efficiency based on the collector's solar thermal efficiency, cleaning and maintenance plan, cleanliness degradation, and solar thermal power plant collector control strategy; determining the cumulative heat based on the meteorological forecast data and the corrected solar thermal efficiency; and determining the predicted power generation value of the solar thermal power plant based on the cumulative heat.

[0006] Furthermore, based on the predicted power generation of the solar thermal power plant, the predicted power generation of the other energy points, and historical operating data, an operating strategy is determined, including: inputting the predicted power generation of the solar thermal power plant, the predicted power generation of the other energy points, and historical operating data into the model; and having the model determine the corresponding operating strategy based on the priority of the output energy.

[0007] Furthermore, the types of output energy include a first type, a second type, and a third type, and the priorities of the output energy include a first priority, a second priority, and a third priority. Specifically, if the type of output energy is the first type, the corresponding priority of the output energy is the first priority; if the type of output energy is the second type, the corresponding priority of the output energy is the second priority; and if the type of output energy is the third type, the corresponding priority of the output energy is the third priority.

[0008] Further, the predicted power generation values ​​of the solar thermal power plant and other energy points, along with historical operating data, are input into the model to obtain the type of output energy. This includes: inputting the predicted power generation values ​​of the solar thermal power plant and other energy points, along with historical operating data, into the model to determine the output power change rate for different time periods; if the output power change rate for each time period is not greater than a first threshold range, the type of output energy is determined to be the first type; if the output energy type is determined to be the first type, the second type and the third type are determined.

[0009] Further, when the output energy type is determined to be the first type, determining the second type and the third type includes: when the output energy type is determined to be the first type, calculating the matching degree between the output power of the multi-energy complementary system and the power demanded by the user in terms of time and magnitude; when the matching degree between the output power of the multi-energy complementary system and the power demanded by the user in terms of both time and magnitude is not less than a second threshold range, determining the output energy type to be the second type; when the output energy type is determined to be the first type and the output energy type is determined to be the second type, calculating the comprehensive cost per kilowatt-hour; when the comprehensive cost per kilowatt-hour is not greater than a third threshold range, determining the output energy type to be the third type.

[0010] Furthermore, according to Calculate the time and magnitude matching degree between the output power of the multi-energy complementary system and the power demanded by the user, where p 2-t p represents the output power of the multi-energy complementary system at time t. 1-t Let η represent the power demanded by the user at time t, η represent the degree of matching between the output power of the multi-energy complementary system and the power demanded by the user in terms of time and magnitude, and t represent time t, which takes the value of an integer from 1 to i, with the time intervals between any t = i and t = i-1 being the same; according to Calculate the overall cost per kilowatt-hour, where p 2_t c represents the output power of the multi-energy complementary system at time t. t C represents the cost of the output power of the multi-energy complementary system at time t.wei This represents the overall cost per kilowatt-hour.

[0011] A second aspect of the present invention provides an operation prediction device for a multi-energy complementary system, comprising: a generation module for acquiring meteorological statistical data and real-time meteorological forecast data, and generating meteorological forecast data based on the meteorological statistical data and the real-time meteorological forecast data; a first determination module for determining the predicted power generation value of a solar thermal power plant and the predicted power generation value of other energy points based on the meteorological forecast data of different time types; a second determination module for determining an operation strategy based on the predicted power generation value of the solar thermal power plant, the predicted power generation value of the other energy points, and historical operation data; and a display module for visualizing and displaying the operation strategy.

[0012] A third aspect of the present invention provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method described in any one aspect of the present invention.

[0013] A fourth aspect of the present invention provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to perform the method described in any one of the first aspects of the present invention.

[0014] The beneficial effects of this invention are as follows:

[0015] The method and apparatus for predicting the operation of a multi-energy complementary system as described in this invention acquires meteorological statistical data and real-time weather forecast data; generates meteorological forecast data based on the meteorological statistical data and real-time weather forecast data; determines the predicted power generation value of the solar thermal power plant and the predicted power generation value of other energy sources based on meteorological forecast data of different time periods; determines the operation strategy based on the predicted power generation value of the solar thermal power plant, the predicted power generation value of other energy sources, and historical operation data; and visualizes and displays the operation strategy. This method achieves stable, efficient, and economical operation of the multi-energy complementary system. Attached Figure Description

[0016] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. It is obvious that the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings.

[0017] Figure 1This is a flowchart of an operation prediction method for a multi-energy complementary system according to an embodiment of the present invention;

[0018] Figure 2 This is a flowchart of an operation prediction method for a multi-energy complementary system according to a specific embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram of an apparatus for predicting the operation of a multi-energy complementary system according to an embodiment of the present invention;

[0020] Figure 4 This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0021] 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 with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these descriptions are merely 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 those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts disclosed in this invention.

[0023] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The terms "installed," "connected," and "linked" 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 communication of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0024] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of methods and systems consistent with some aspects of the invention as detailed in the appended claims.

[0025] This invention proposes a method, apparatus, and related equipment for predicting the operation of a multi-energy complementary system. Specifically, the following description of the method, apparatus, and related equipment for predicting the operation of a multi-energy complementary system according to embodiments of this invention is based on the accompanying drawings.

[0026] Figure 1 This is a flowchart of a method for predicting the operation of a multi-energy complementary system according to an embodiment of the present invention. It should be noted that the method for predicting the operation of a multi-energy complementary system according to this embodiment can be applied to a device for predicting the operation of a multi-energy complementary system according to this embodiment. This device can be configured on an electronic device or in a server. This application does not limit the scope of this application.

[0027] like Figure 1 As shown, the operation prediction method for multi-energy complementary systems includes:

[0028] S110: Acquire meteorological statistics and real-time weather forecast data, and generate meteorological prediction data based on the meteorological statistics and real-time weather forecast data.

[0029] Among these, meteorological statistics are historical meteorological statistics. There is a natural regularity between meteorological statistics and solar radiation; factors such as season, weather, temperature, and cloud cover all directly or indirectly affect the intensity of solar radiation. Therefore, historical meteorological statistics are crucial for predicting direct solar radiation. The natural regularity between historical meteorological data and direct solar radiation can be obtained through meteorological data processing models.

[0030] Among these, real-time weather forecast data shows a certain pattern in its relationship with solar radiation. This invention, based on typical year meteorological data, establishes the relationship between weather forecasts, cloud cover, and direct solar radiation, thus enabling the prediction of direct solar radiation using weather forecasts. Alternatively, the relationship between weather forecasts, cloud cover, and direct solar radiation can be obtained through a meteorological data processing model.

[0031] Meteorological forecast data includes, but is not limited to, irradiance and cloud cover.

[0032] Meteorological statistics and real-time weather forecasts can be input into a pre-trained meteorological data processing model to obtain meteorological forecast data.

[0033] S120 determines the predicted power generation of the solar thermal power plant based on meteorological forecast data of different time periods, as well as the predicted power generation of other energy sources.

[0034] In embodiments of the present invention, the solar thermal power plant is a parabolic trough solar thermal power plant, but it can also be other types of solar thermal power plants, such as Fresnel solar thermal power plants.

[0035] In embodiments of the present invention, other energy sources may be one or more of thermal power generation, photovoltaic power plants, wind power, electrochemical energy storage, and biomass power generation.

[0036] In embodiments of the present invention, different time types include short-term, medium-term, and long-term, wherein the short-term, medium-term, and long-term time can be set manually.

[0037] In embodiments of the present invention, a corrected solar thermal efficiency is determined based on the collector's solar thermal efficiency, cleaning and maintenance plans, cleanliness degradation, and the solar thermal power plant's collector control strategy; accumulated heat is determined based on meteorological forecast data and the corrected solar thermal efficiency; and the predicted power generation value of the solar thermal power plant is determined based on the accumulated heat. This allows for the determination of predicted power generation values ​​for solar thermal power plants under different time periods.

[0038] For example, in the case of photovoltaic power plants at other energy points, the predicted power generation value can be calculated using physical formulas based on solar radiation prediction data, combined with the photovoltaic power plant's component parameters (rated power, efficiency, tilt angle, azimuth angle), inverter efficiency, temperature loss coefficient, etc.

[0039] S130 determines the operation strategy based on the predicted power generation of the solar thermal power plant and other energy points, as well as historical operating data.

[0040] Historical operating data can be understood as a database formed by past operating data of the multi-energy complementary system, or the historical operating data of each energy unit of the multi-energy complementary system.

[0041] In embodiments of the present invention, the predicted power generation of the solar thermal power plant and other energy sources, along with historical operating data, are input into the model; the model then determines the corresponding operating strategy based on the priority of the output energy. Specific implementation details can be found in subsequent embodiments.

[0042] S140 visualizes and displays the operating strategy.

[0043] In embodiments of the present invention, the visualization of the operation strategy includes tables or graphs.

[0044] According to an embodiment of the present invention, a method for predicting the operation of a multi-energy complementary system involves acquiring meteorological statistical data and real-time weather forecast data, generating meteorological forecast data based on the meteorological statistical data and real-time weather forecast data, determining the predicted power generation value of the solar thermal power plant based on meteorological forecast data of different time periods, and determining the predicted power generation value of other energy sources; determining an operation strategy based on the predicted power generation value of the solar thermal power plant, the predicted power generation value of other energy sources, and historical operation data; and visualizing and displaying the operation strategy. This method achieves stable, efficient, and economical operation of the multi-energy complementary system.

[0045] To enable those skilled in the art to more readily understand the present invention, Figure 2 This is an operation prediction method for a power plant multi-energy complementary system according to a specific embodiment of the present invention, such as... Figure 2 As shown, the operation prediction method for the multi-energy complementary system of this power station includes:

[0046] S210: Obtain meteorological statistics and real-time weather forecast data, and generate meteorological prediction data based on the meteorological statistics and real-time weather forecast data.

[0047] S220 determines the predicted power generation of the solar thermal power plant based on meteorological forecast data of different time periods, as well as the predicted power generation of other energy sources.

[0048] In embodiments of the present invention, steps S210-S220 can be implemented with reference to the implementation of steps S110-S120 described above. Further details will not be provided here.

[0049] S230: Input the predicted power generation value of the solar thermal power plant and the predicted power generation value of other energy points, as well as historical operating data, into the model to obtain the type of output energy.

[0050] In embodiments of the present invention, the types of output energy include a first type, a second type, and a third type, wherein the first type can be energy stability, the second type can be user demand responsiveness, and the third type can be economic operation.

[0051] Among them, energy stability can be understood as the total output power of the entire multi-energy complementary system (including solar thermal, photovoltaic, wind power, etc.) being smooth, stable, and predictable, without drastic or rapid fluctuations.

[0052] User demand responsiveness can be understood as, after ensuring a stable foundation, pursuing a higher goal: that the electricity generated by the system, not only in terms of total quantity but also in terms of "time" and "quantity," closely matches the user's actual electricity needs. In other words, the system generates the exact amount of electricity the user requires, and at what time.

[0053] Economic operation can be understood as the top-level objective. Only after ensuring the system's stable operation and perfect satisfaction of user needs should we consider how to make money and save money. That is, among all the solutions that satisfy the first two conditions, we choose the one with the lowest total cost.

[0054] In an embodiment of the present invention, the predicted power generation value of the solar thermal power plant and the predicted power generation value of other energy points, as well as historical operating data, are input into the model to determine the output power change rate for different time types. If the output power change rate for different time types is not greater than a first threshold range, the output energy type is determined to be the first type (i.e., energy stability). If the output energy type is determined to be the first type, the second type and the third type are determined.

[0055] For example, the predicted power generation of concentrated solar power (CSP) plants and other energy sources, along with historical operating data, are input into the model. In a medium-term timeframe (e.g., one day) and an hourly scale, the model is then used to calculate the power output. Calculate the rate of change of output power over a day, where p t Let represent the output power at time t, where t is an integer ranging from 1 to i. Then, based on the method for calculating the output power change rate in the medium term, the output power change rates in the short and long term are calculated. Finally, if the output power change rates in the short, medium, and long term are all determined to be within a first threshold range, the output energy type is determined to be energy stable. For example, the first threshold range is 0%-20%.

[0056] In an embodiment of the present invention, to better match user load when the output energy type is determined to be the first type (i.e., stable energy), the matching degree between the output power of the multi-energy complementary system and the user's demand power in terms of time and magnitude is calculated. If the matching degree between the output power of the multi-energy complementary system and the user's demand power in terms of both time and magnitude is not less than a second threshold range, the output energy type is determined to be the second type (i.e., user demand response capability). For example, the second threshold range is 90%-100%.

[0057] The calculation of the matching degree between the output power of the multi-energy complementary system and the power demand of users in terms of time and magnitude is to assess whether the comprehensive energy output from energy points such as parabolic trough solar thermal power plants can meet the user's needs. If the matching degree is low, the operating strategy will provide prompts and feedback when the output cannot meet the load demand. If it can meet the load demand, the output will be an operating strategy that meets the load demand.

[0058] Among them, according to Calculate the time and magnitude matching degree between the output power of the multi-energy complementary system and the power demanded by the user, where p 2-tp represents the output power of the multi-energy complementary system at time t. 1-t Let η represent the power demanded by the user at time t, η represent the degree of matching between the output power of the multi-energy complementary system and the power demanded by the user in terms of time and magnitude, and t represent time t. The value of t is an integer from 1 to i, and the time interval between any t = i and t = i-1 is the same.

[0059] To minimize the overall cost per kilowatt-hour (kWh) when the output energy is stable and better matches user load, in embodiments of this invention, the overall kWh is calculated if the output energy type is determined to be either Type 1 (stable energy) or Type 2 (user demand responsiveness). If the overall kWh is not greater than a third threshold range, the output energy type is determined to be Type 3 (economical operation). For example, the third threshold range is 0%-30%.

[0060] Among them, according to Calculate the overall cost per kilowatt-hour, where p 2_t c represents the output power of the multi-energy complementary system at time t. t C represents the cost of the output power of the multi-energy complementary system at time t. wei This represents the overall cost per kilowatt-hour.

[0061] Among them, according to Determine the range of the third threshold, C avg_h This represents the historical average cost per kilowatt-hour.

[0062] S240 determines the priority of the output energy based on the type of output energy, and determines the corresponding operation strategy based on the priority of the output energy.

[0063] In embodiments of the present invention, the priority of the output energy includes a first priority, a second priority, and a third priority, wherein the type of the output energy is a first type, and the corresponding priority of the output energy is a first priority; the type of the output energy is a second type, and the corresponding priority of the output energy is a second priority; the type of the output energy is a third type, and the corresponding priority of the output energy is a third priority.

[0064] For example, if the output energy type is Type 1 (i.e., stable energy) and the corresponding output energy priority is first priority, the forced operation strategy should smooth power fluctuations and avoid drastic short-term increases or decreases, which requires means such as energy storage regulation and backup power dispatch. If the output energy type is Type 2 (i.e., user demand responsiveness) and the corresponding output energy priority is second priority, the operation strategy needs to dynamically match the load's power demand and time distribution, which may sacrifice some economic efficiency (such as forced generation during high-price periods). If the output energy type is Type 3 (i.e., economical operation) and the corresponding output energy priority is third priority, after satisfying the first two requirements, the operation strategy needs to select the energy combination with the lowest cost (such as prioritizing solar thermal and delaying the use of high-priced fuels).

[0065] S250 visualizes and displays the operating strategy.

[0066] According to the multi-energy complementary system operation prediction method of this invention, instead of using a single economic indicator, this method innovatively establishes a three-tiered progressive evaluation system: Energy Stability (first priority): prioritizing the smooth and stable output of the system to avoid large fluctuations that could impact the power grid. This is a basic requirement for grid connection. User Demand Response Capability (second priority): on the basis of stability, pursuing a high degree of matching with user load in terms of time and power values ​​to improve the quality of power supply services. Economic Operation (third priority): after meeting the goals of the first two higher priorities, maximizing the reduction of the overall cost per kilowatt-hour to achieve maximum economic benefits. Furthermore, based on different output energy types, it automatically matches and generates operation strategies with clear priorities. For example: First priority (stability): activating energy storage and calling on backup power to smooth fluctuations. Second priority (demand response): sacrificing economic efficiency when necessary (such as forced generation when electricity prices are high) to meet load demand. Third priority (economic): optimizing energy mix, prioritizing the use of low-cost energy (such as solar thermal) and delaying the use of high-priced fuels. This reduces the workload of dispatchers and minimizes delays and errors in human decision-making. This ensures that the system operates according to the optimal preset logic under any circumstances.

[0067] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0068] According to one aspect of the present invention, an operation prediction device for a multi-energy complementary system is also proposed. Figure 3 This is a schematic diagram of an operation prediction device for a multi-energy complementary system according to an embodiment of the present invention; as shown. Figure 3 As shown, it includes:

[0069] The generation module 310 is used to acquire meteorological statistical data and real-time weather forecast data, and generate meteorological prediction data based on the meteorological statistical data and the real-time weather forecast data;

[0070] The first determining module 320 is used to determine the predicted power generation value of the solar thermal power plant based on the meteorological forecast data of different time types, and to determine the predicted power generation value of other energy points.

[0071] The second determining module 330 is used to determine the operation strategy based on the predicted power generation value of the solar thermal power plant, the predicted power generation value of the other energy points, and historical operation data;

[0072] Display module 340 is used to visualize and display the operation strategy.

[0073] According to an embodiment of the present invention, the operation prediction device for a multi-energy complementary system acquires meteorological statistical data and real-time meteorological forecast data, generates meteorological forecast data based on the meteorological statistical data and real-time meteorological forecast data, determines the predicted power generation value of the solar thermal power plant based on meteorological forecast data of different time types, and determines the predicted power generation value of other energy points; based on the predicted power generation value of the solar thermal power plant, the predicted power generation value of other energy points, and historical operation data, determines the operation strategy; and visualizes and displays the operation strategy. This achieves stable, efficient, and economical operation of the multi-energy complementary system.

[0074] Optionally, the first determining module 320 is specifically used to determine the corrected solar thermal efficiency based on the solar collector's solar thermal efficiency, cleaning and maintenance plan, cleanliness degradation, and solar thermal power plant collector control strategy; determine the cumulative heat based on the meteorological forecast data and the corrected solar thermal efficiency; and determine the predicted power generation value of the solar thermal power plant based on the cumulative heat.

[0075] Optionally, the second determining module 330 is specifically used to input the predicted power generation value of the solar thermal power plant, the predicted power generation value of the other energy points, and historical operating data into the model, and the model determines the corresponding operating strategy based on the priority of the output energy.

[0076] Optionally, the type of output energy includes a first type, a second type, and a third type, and the priority of the output energy includes a first priority, a second priority, and a third priority, wherein the type of output energy is the first type, and the corresponding priority of the output energy is the first priority; the type of output energy is the second type, and the corresponding priority of the output energy is the second priority; the type of output energy is the third type, and the corresponding priority of the output energy is the third priority.

[0077] Optionally, the second determining module 330 is specifically used to input the predicted power generation value of the solar thermal power plant and the predicted power generation value of the other energy points, as well as historical operating data, into the model to determine the output power change rate for different time types; if the output power change rate for different time types is not greater than a first threshold range, the type of the output energy is determined to be the first type; if the output energy type is determined to be the first type, the second type and the third type are determined.

[0078] Optionally, the second determining module 330 is specifically configured to: calculate the matching degree of the output power of the multi-energy complementary system and the user's demand power in terms of time and magnitude when the type of output energy is determined to be the first type; determine the type of output energy to be the second type when the matching degree of the output power of the multi-energy complementary system and the user's demand power in terms of time and magnitude is not less than a second threshold range; calculate the comprehensive cost per kilowatt-hour when the type of output energy is determined to be the first type and the type of output energy is determined to be the second type; and determine the type of output energy to be the third type when the comprehensive cost per kilowatt-hour is not greater than a third threshold range.

[0079] Optionally, according to Calculate the time and magnitude matching degree between the output power of the multi-energy complementary system and the power demanded by the user, where p 2-t p represents the output power of the multi-energy complementary system at time t. 1-t Let η represent the power demanded by the user at time t, η represent the degree of matching between the output power of the multi-energy complementary system and the power demanded by the user in terms of time and magnitude, and t represent time t, which takes the value of an integer from 1 to i, with the time intervals between any t = i and t = i-1 being the same; according to Calculate the overall cost per kilowatt-hour, where p 2_t c represents the output power of the multi-energy complementary system at time t. t C represents the cost of the output power of the multi-energy complementary system at time t. wei This represents the overall cost per kilowatt-hour.

[0080] According to one aspect of the present invention, an electronic device is provided.

[0081] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Figure 4 As shown, an electronic device may include one or more ( Figure 4 Only one is shown in the image. A processor 102 (which may include, but is not limited to, a microprocessor unit (MPU) or a programmable logic device (PLD)) and a memory 104 for storing data are also shown. In one exemplary embodiment, the electronic device may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 4 The structure shown is for illustrative purposes only and does not limit the structure of the terminal device described above. For example, the terminal device may also include components that are more... Figure 4 The more or fewer components shown, or having the same Figure 4 Equivalent functions or ratios shown Figure 4 The functions shown have more different configurations.

[0082] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the multi-energy complementary system operation prediction method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to terminal devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0083] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the switching device. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0084] This invention proposes a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute a method for predicting the operation of a multi-energy complementary system.

[0085] The applicant of this invention has provided a detailed description of the embodiments of the invention in conjunction with the accompanying drawings. However, those skilled in the art should understand that the above embodiments are merely preferred embodiments of the invention. The detailed description is only intended to help readers better understand the spirit of the invention and is not intended to limit the scope of protection of the invention. On the contrary, any improvements or modifications made based on the inventive spirit of the invention should fall within the scope of protection of the invention.

[0086] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0087] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the present invention 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; and these 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 the present invention. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A method for predicting the operation of a multi-energy complementary system, characterized in that, include: S1, acquire meteorological statistical data and real-time weather forecast data, and generate meteorological prediction data based on the meteorological statistical data and real-time weather forecast data; S2, determine the predicted power generation value of the solar thermal power plant based on the meteorological forecast data of different time types, and determine the predicted power generation value of other energy points; S3. Based on the predicted power generation of the solar thermal power plant, the predicted power generation of the other energy points, and historical operating data, determine the operating strategy; S4, visualize and display the aforementioned operating strategy.

2. The method for predicting the operation of a multi-energy complementary system according to claim 1, characterized in that, The predicted power generation of the solar thermal power plant is determined based on meteorological forecast data of different time periods, including: The modified solar thermal efficiency is determined based on the collector's solar thermal efficiency, cleaning and maintenance plan, cleanliness degradation, and solar thermal power plant collector control strategy. The cumulative heat is determined based on the meteorological forecast data and the corrected photothermal efficiency. The predicted power generation value of the solar thermal power plant is determined based on the accumulated heat.

3. The method for predicting the operation of a multi-energy complementary system according to claim 1, characterized in that, Based on the predicted power generation of the solar thermal power plant and the predicted power generation of other energy points, as well as historical operating data, an operating strategy is determined, including: The predicted power generation of the solar thermal power plant, the predicted power generation of other energy points, and historical operating data are input into the model, and the model determines the corresponding operating strategy based on the priority of the output energy.

4. The method for predicting the operation of a multi-energy complementary system according to claim 3, characterized in that, The types of output energy include a first type, a second type, and a third type, and the priorities of the output energy include a first priority, a second priority, and a third priority. Specifically, if the type of output energy is the first type, the corresponding priority of the output energy is the first priority; if the type of output energy is the second type, the corresponding priority of the output energy is the second priority; and if the type of output energy is the third type, the corresponding priority of the output energy is the third priority.

5. The method for predicting the operation of a multi-energy complementary system according to claim 4, characterized in that, The predicted power generation values ​​of the solar thermal power plant and other energy sources, along with historical operating data, are input into the model to obtain the types of output energy, including: The predicted power generation of the solar thermal power plant, the predicted power generation of other energy points, and historical operating data are input into the model to determine the output power change rate for different time periods. If the rate of change of output power in different time types is not greater than the first threshold range, the type of output energy is determined to be the first type; If the type of the output energy is determined to be the first type, then the second type and the third type are determined.

6. The method for predicting the operation of a multi-energy complementary system according to claim 5, characterized in that, If the output energy type is determined to be the first type, determining the second type and the third type includes: If the type of the output energy is determined to be the first type, calculate the matching degree between the output power of the multi-energy complementary system and the power demanded by the user in terms of time and magnitude. If the matching degree between the output power of the multi-energy complementary system and the power demanded by the user in both time and magnitude is not less than the second threshold range, the type of the output energy is determined to be the second type. If the type of the output energy is determined to be the first type and the type of the output energy is determined to be the second type, calculate the comprehensive cost per kilowatt-hour. If the overall cost per kilowatt-hour is not greater than the third threshold range, the output energy type is determined to be the third type.

7. The method for predicting the operation of a multi-energy complementary system according to claim 6, characterized in that, according to Calculate the time and magnitude matching degree between the output power of the multi-energy complementary system and the power demanded by the user, where p 2-t p represents the output power of the multi-energy complementary system at time t. 1-t Let η represent the power demanded by the user at time t, η represent the degree of matching between the output power of the multi-energy complementary system and the power demanded by the user in terms of time and magnitude, and t represent time t. The value of t is an integer from 1 to i, and the time interval between any t = i and t = i-1 is the same. according to Calculate the overall cost per kilowatt-hour, where p 2_t c represents the output power of the multi-energy complementary system at time t. t C represents the cost of the output power of the multi-energy complementary system at time t. wei This represents the overall cost per kilowatt-hour.

8. A device for predicting the operation of a multi-energy complementary system, characterized in that, include: The generation module is used to acquire meteorological statistical data and real-time weather forecast data, and generate meteorological prediction data based on the meteorological statistical data and real-time weather forecast data; The first determining module is used to determine the predicted power generation value of the solar thermal power plant based on the meteorological forecast data of different time types, and to determine the predicted power generation value of other energy points. The second determining module is used to determine the operation strategy based on the predicted power generation value of the solar thermal power plant, the predicted power generation value of the other energy points, and historical operation data; The display module is used to visualize and display the operating strategy.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 7.

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