Method and device for constructing output model of photovoltaic power station
Through multi-source meteorological data fusion and downscale technology, a photovoltaic power station output model is built, which solves the scarcity and complex terrain problems of meteorological data in photovoltaic power generation systems in high-altitude areas, and realizes accurate prediction and efficient utilization of photovoltaic power station output.
Patent Information
- Application Number
- CN202510712218.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-29
- Publication Date
- 2025-09-02
AI Technical Summary
The terrain and climate in high-altitude areas are complex, and ground meteorological observation stations are scarce. Traditional meteorological data acquisition methods are difficult to meet the demand for accurate prediction of photovoltaic output, especially in terms of spatial and temporal correlation between meteorological elements and the coupling of multi-time scale fluctuation characteristics.
By obtaining multi-source meteorological satellite data and ground observation data, data fusion is carried out, time and space reduction methods are adopted, and GWR statistical reduction technology is combined to build a photovoltaic power station output model, and the degree of influence of meteorological elements on photovoltaic power station output model is established.
It has achieved refined reconstruction and accurate prediction of the output of photovoltaic power stations, provided technical support for photovoltaic power generation systems in high-altitude areas, and improved the economical and efficient development and utilization of new energy.
Smart Images
Figure CN120579327A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of new energy output meteorological data processing, and in particular to a method and device for constructing a photovoltaic power station output model. Background Art
[0002] With the global energy transition and the advancement of sustainable development strategies, new energy power generation technologies have garnered widespread attention and application. As a key component of new energy, photovoltaic power generation, due to its clean, renewable, and widespread advantages, has become a key direction in the global energy restructuring. In the future, new wind and solar power generation capacity in my country will gradually shift to higher altitude regions.
[0003] The output characteristics of photovoltaic power generation are significantly affected by meteorological conditions. Therefore, accurate meteorological data is a key foundation for the design, operation, and output forecast of photovoltaic power generation systems. However, the topography and climate environment in high-altitude areas are complex, and the accurate prediction of wind and solar resources still lacks a large amount of basic data support. Due to factors such as the high-altitude cold environment, sparse population, and inconvenient transportation in high-altitude areas, the number of ground-based meteorological observation stations is scarce and their spatial distribution is uneven. At the same time, due to the large terrain fluctuations and complex climatic conditions in high-altitude areas, the spatial distribution of meteorological characteristics is highly heterogeneous. The meteorological information represented by ground-based observation stations is limited in scope and cannot meet the needs of accurate photovoltaic output forecasting. Traditional meteorological data acquisition methods usually rely on a single data source, which does not capture local meteorological characteristics and makes it difficult to fully utilize the complementarity of multi-source data.
[0004] Existing PV output reconstruction technologies primarily target areas with relatively uniform spatial meteorological conditions. However, they struggle to effectively address the dual challenges of strong spatial heterogeneity of meteorological elements in complex terrain and the scarcity of historical data. In particular, conventional methods struggle with the spatiotemporal correlations between meteorological elements in PV output reconstruction modeling, such as single assumptions and insufficient coupling of multi-timescale fluctuation characteristics. Summary of the Invention
[0005] In view of this, the present invention proposes a method and device for constructing a photovoltaic power station output model, aiming to solve one or more of the technical problems mentioned in the above background technology section.
[0006] In a first aspect, an embodiment of the present invention provides a method for constructing a photovoltaic power station output model, the method comprising: obtaining photovoltaic power station output data and meteorological satellite data and ground observation data corresponding to the photovoltaic power station output; fusing the meteorological satellite data and the ground observation data to obtain meteorological fusion data; obtaining meteorological elements based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output; and constructing a photovoltaic power station output model based on the photovoltaic power station output data and the meteorological fusion data, in combination with the meteorological elements.
[0007] Furthermore, the meteorological satellite data corresponding to the output of the photovoltaic power station is obtained in the following manner: multi-source meteorological satellite data corresponding to the output of the photovoltaic power station is obtained; using the ground observation data as a reference, and using the average error and resolution as screening criteria, the meteorological satellite data corresponding to the output of the photovoltaic power station is screened from the multi-source meteorological satellite data.
[0008] Furthermore, the meteorological satellite data and the ground observation data are fused to obtain meteorological fused data, including: first performing temporal downscaling on the meteorological satellite data and the ground observation data, and then performing spatial downscaling on the meteorological satellite data and the ground observation data, to obtain meteorological fused data; or first performing spatial downscaling on the meteorological satellite data and the ground observation data, and then performing temporal downscaling on the meteorological satellite data and the ground observation data, to obtain meteorological fused data.
[0009] Furthermore, the following method is used for time downscaling:
[0010]
[0011] Among them, y i represents the meteorological satellite data after time downscaling at point i; if time downscaling is performed first, then x it represents the high-precision remote sensing data at point i at time t, including meteorological satellite data and ground observation data; if spatial downscaling is performed first, then x it represents the meteorological satellite data after spatial downscaling at point i at time t; (v i ,u i ) represents the geographic location information, ε(v i ,u i ) represents the error function, β0(v i ,u i ) represents the constant term in the time-scale data fusion equation at point i, β t represents the downscaling coefficient at time t, and t represents the data sampling time.
[0012] Furthermore, the following method is used for spatial downscaling: if temporal downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data after temporal downscaling; if spatial downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data and the ground observation data.
[0013] Furthermore, based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output, meteorological elements are obtained, including: based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output, meteorological elements are obtained according to the degree of impact on the photovoltaic power station output.
[0014] Furthermore, based on the photovoltaic power station output data and the meteorological fusion data, combined with the meteorological elements, a photovoltaic power station output model is constructed, including: constructing the photovoltaic power station output model as follows:
[0015] P p =η p AI p (u i ,v i ,λ p )f i (y i );
[0016] Among them, P p is the output power of the photovoltaic power station, η p , A are the photovoltaic system conversion efficiency and photovoltaic array area, respectively, p is the tilt angle of the photovoltaic array, (u i ,v i ) is a parameter containing geographic location information, f i (y i ) is the parameter after considering the impact of meteorological factors on photovoltaic output, I p is the light intensity, y i It is meteorological fusion data.
[0017] In the second aspect, an embodiment of the present invention also provides a device for constructing a photovoltaic power station output model, the device including: an acquisition unit for acquiring photovoltaic power station output data and meteorological satellite data and ground observation data corresponding to the photovoltaic power station output; a fusion unit for fusing the meteorological satellite data and the ground observation data to obtain meteorological fusion data; a processing unit for obtaining meteorological elements based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output; and a construction unit for constructing a photovoltaic power station output model based on the photovoltaic power station output data and the meteorological fusion data in combination with the meteorological elements.
[0018] Furthermore, the meteorological satellite data corresponding to the output of the photovoltaic power station is obtained in the following manner: multi-source meteorological satellite data corresponding to the output of the photovoltaic power station is obtained; using the ground observation data as a reference, and using the average error and resolution as screening criteria, the meteorological satellite data corresponding to the output of the photovoltaic power station is screened from the multi-source meteorological satellite data.
[0019] Furthermore, the fusion unit is also used to: first perform temporal downscaling on the meteorological satellite data and the ground observation data, and then perform spatial downscaling on them to obtain meteorological fusion data; or first perform spatial downscaling on the meteorological satellite data and the ground observation data, and then perform temporal downscaling on them to obtain meteorological fusion data.
[0020] Furthermore, the following method is used for time downscaling:
[0021]
[0022] Among them, y i represents the meteorological satellite data after time downscaling at point i; if time downscaling is performed first, then x it represents the high-precision remote sensing data at point i at time t, including meteorological satellite data and ground observation data; if spatial downscaling is performed first, then x it represents the meteorological satellite data after spatial downscaling at point i at time t; (v i ,u i ) represents the geographic location information, ε(v i ,u i ) represents the error function, β0(v i ,u i ) represents the constant term in the time-scale data fusion equation at point i, β t represents the downscaling coefficient at time t, and t represents the data sampling time.
[0023] Furthermore, the following method is used for spatial downscaling: if temporal downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data after temporal downscaling; if spatial downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data and the ground observation data.
[0024] Furthermore, the processing unit is further configured to obtain meteorological elements according to the degree of influence on the output of the photovoltaic power station based on the output data of the photovoltaic power station and the meteorological fusion data corresponding to the output of the photovoltaic power station.
[0025] Furthermore, the construction unit is further used to: construct a photovoltaic power station output model as follows:
[0026] P p =η p AI p (u i ,v i ,λ p )f i (y i );
[0027] Among them, P p is the output power of the photovoltaic power station, η p , A are the photovoltaic system conversion efficiency and photovoltaic array area, respectively, p is the tilt angle of the photovoltaic array, (u i ,v i ) is a parameter containing geographic location information, fi (y i ) is the parameter after considering the impact of meteorological factors on photovoltaic output, I p is the light intensity, y i It is meteorological fusion data.
[0028] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the methods provided in the above embodiments are implemented.
[0029] In a fourth aspect, an embodiment of the present invention further provides an electronic device comprising: a processor; a memory for storing instructions executable by the processor; and the processor for reading the executable instructions from the memory and executing the instructions to implement the methods provided in the above embodiments.
[0030] The method and device for constructing a photovoltaic power station output model provided by the embodiment of the present invention obtain meteorological fusion data by fusing meteorological satellite data and ground observation data, obtain meteorological elements based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output, and construct a photovoltaic power station output model based on the photovoltaic power station output data and the meteorological fusion data in combination with meteorological elements. This can realize the output reconstruction of the photovoltaic power station in a refined manner, can more accurately simulate and predict the actual output of the photovoltaic power generation system, and provide technical support for the economic and efficient development and utilization of new energy. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] Figure 1 An exemplary flow chart of a method for constructing a photovoltaic power station output model according to an embodiment of the present invention is shown;
[0032] Figure 2a 、 2b A schematic diagram showing data of solar radiation and temperature, among meteorological factors, affecting the output of a photovoltaic power station according to an embodiment of the present invention;
[0033] Figure 3 A schematic structural diagram of an apparatus for constructing a photovoltaic power station output model according to an embodiment of the present invention is shown. DETAILED DESCRIPTION
[0034] Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to provide a thorough and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments shown in the accompanying drawings is not intended to limit the present invention. In the accompanying drawings, identical elements are denoted by the same reference numerals.
[0035] Unless otherwise specified, the terms used herein (including technical terms) have the meanings commonly understood by those skilled in the art. In addition, it is understood that terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.
[0036] Figure 1 An exemplary flow chart of a method for constructing a photovoltaic power station output model according to an embodiment of the present invention is shown.
[0037] like Figure 1 As shown, the method includes:
[0038] Step S101: obtaining photovoltaic power station output data and meteorological satellite data and ground observation data corresponding to the photovoltaic power station output.
[0039] Furthermore, the meteorological satellite data corresponding to the output of the photovoltaic power station is obtained in the following way:
[0040] Obtain multi-source meteorological satellite data corresponding to the output of photovoltaic power stations;
[0041] Using ground observation data as a reference and average error and resolution as screening criteria, meteorological satellite data corresponding to the output of photovoltaic power stations are screened from multi-source meteorological satellite data.
[0042] Specifically, for multi-source meteorological satellite data, that is, meteorological satellite data from different sources, ground observation data (that is, site observation data) is used as a reference to screen out high-resolution meteorological remote sensing data that best matches the target area.
[0043] Preferably, the average error of solar radiation is used as the screening criterion, and the expression of the average error is:
[0044]
[0045] E me is the average deviation, i is the i-th geographical location, n is the sample size, P pi is the meteorological satellite data, P pi Ground observation data.
[0046] Step S102: Fusing meteorological satellite data and ground observation data to obtain meteorological fusion data.
[0047] Furthermore, step S102 includes:
[0048] Meteorological satellite data and ground observation data are first temporally downscaled and then spatially downscaled to obtain meteorological fusion data; or
[0049] Meteorological satellite data and ground observation data are first spatially downscaled and then temporally downscaled to obtain meteorological fusion data.
[0050] Specifically, for the data fusion of meteorological satellite data and ground observation data, there is no order of priority between temporal downscaling and spatial downscaling.
[0051] Furthermore, the following method is used for time downscaling:
[0052]
[0053] Among them, y i represents the meteorological satellite data after time downscaling at point i; if time downscaling is performed first, then x it represents the high-precision remote sensing data at point i at time t, including meteorological satellite data and ground observation data; if spatial downscaling is performed first, then x it represents the meteorological satellite data after spatial downscaling at point i at time t; (v i ,u i ) represents the geographic location information, ε(v i ,u i ) represents the error function, β0(v i ,u i ) represents the constant term in the time-scale data fusion equation at point i, β t represents the downscaling coefficient at time t, and t represents the data sampling time.
[0054] Specifically, a data fusion algorithm based on temporal resolution downscaling is used to process high-resolution meteorological remote sensing data. This algorithm combines meteorological laws and regional characteristics experience to assimilate multi-source data to ensure data consistency and reliability, thereby obtaining low-resolution ground meteorological data.
[0055] The above embodiment solves the problem of information loss in spatial detail reconstruction of low-resolution data and improves the consistency and computational efficiency of ground observation data in downscaling results.
[0056] Furthermore, the following method is used for spatial downscaling:
[0057] If temporal downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data after temporal downscaling;
[0058] If spatial downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data and ground observation data.
[0059] Specifically, applying the concept of local regression and adhering to the first law of geography, the attenuation function is calculated by introducing the geographic location of the data. This attenuation function is then used to calculate the weight of the data in the local regression equation. Taking into account the spatial weights of adjacent points, a regression model is established by estimating the parameters of the dependent and independent variables at each location. The GWR statistical downscaling method is then used to fuse satellite meteorological data from the target area with interpolated data from ground observation stations. The resulting downscaled, high-resolution meteorological fusion data resolves the problem of spatial and temporal resolution mismatch.
[0060] A mathematical model was established to characterize the spatial correlations between meteorological elements at different geographic locations. A Kriging spatial interpolation algorithm was used to perform reverse back-substitution on remotely sensed meteorological data, thereby obtaining a dataset of meteorological parameters for areas with low spatial resolution. Meteorological observation data from a typical high-altitude area was selected as an example. The deviations between the reconstructed meteorological data and the measured data were compared and analyzed, and residual compensation and overlay processing were implemented.
[0061] The above embodiment solves the problems of low meteorological data resolution and insufficient fusion of multi-source data. Through downscaling and assimilation technology, the spatiotemporal resolution of meteorological elements is improved, providing meteorological data support for the subsequent reconstruction of photovoltaic output in high-altitude weak exploration areas.
[0062] Step S103: obtaining meteorological elements based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output.
[0063] Furthermore, step S103 includes:
[0064] Based on the output data of photovoltaic power stations and the meteorological fusion data corresponding to the output of photovoltaic power stations, meteorological factors are obtained according to the degree of impact on the output of photovoltaic power stations.
[0065] Specifically, the meteorological factors that affect photovoltaic output in high-altitude areas are identified, and the degree of influence of meteorological factors on the output of photovoltaic power stations is qualitatively analyzed theoretically. The results of the judgment include: solar irradiance, ambient temperature, wind speed, and relative humidity are the main modeling input parameters for the reconstruction of photovoltaic power station output.
[0066] Figure 2a 、 2b The data schematic diagrams showing the effects of solar radiation and temperature, two meteorological elements, on the output of a photovoltaic power station according to an embodiment of the present invention are shown respectively. Figure 2a 、 2b As shown in the figure, meteorological data from different sources and with different spatiotemporal resolutions are assimilated, and meteorological factors related to photovoltaic output in high-altitude areas, such as solar radiation, temperature, and wind speed, are selected in combination with meteorological laws and regional characteristics to improve the applicability and pertinence of the data.
[0067] Step S104: Based on the photovoltaic power station output data and the meteorological fusion data, combined with meteorological elements, a photovoltaic power station output model is constructed.
[0068] Furthermore, step S104 includes:
[0069] The photovoltaic power station output model is constructed as follows:
[0070] P p =η A AI p (u i ,v i ,λ p )f i (y i );
[0071] Among them, P p is the output power of the photovoltaic power station, η p , A are the photovoltaic system conversion efficiency and photovoltaic array area, respectively, p is the tilt angle of the photovoltaic array, (u i ,v i ) is a parameter containing geographic location information, f i (y i ) is the parameter after considering the impact of meteorological factors on photovoltaic output, I p is the light intensity, y i It is meteorological fusion data.
[0072] Specifically, since meteorological factors such as solar radiation and temperature are significantly correlated with geographic coordinates (longitude, latitude) and altitude, geographic location information is determined as a parameter for modeling. Geographic location information includes geographic coordinates (longitude, latitude) and altitude.
[0073] Based on the meteorological spatial data with improved resolution after downscaling and historical photovoltaic output data, combined with the probability distribution method, a photovoltaic distribution characteristics simulation method based on density estimation function, namely the photovoltaic power station output model, is established.
[0074] It should be understood that this embodiment is applicable to photovoltaic power stations in different terrains, preferably, to terrains in high-altitude areas.
[0075] In the above embodiment, meteorological fusion data is obtained by fusing meteorological satellite data and ground observation data, meteorological elements are obtained based on the output data of the photovoltaic power station and the meteorological fusion data corresponding to the output of the photovoltaic power station, and a photovoltaic power station output model is constructed based on the output data of the photovoltaic power station and the meteorological fusion data in combination with meteorological elements. This can realize the reconstruction of the output of the photovoltaic power station in a refined manner, and can more accurately simulate and predict the actual output of the photovoltaic power generation system, providing technical support for the economic and efficient development and utilization of new energy.
[0076] Figure 3 A schematic structural diagram of an apparatus for constructing a photovoltaic power station output model according to an embodiment of the present invention is shown.
[0077] like Figure 3 As shown, the device includes:
[0078] An acquisition unit 301 is configured to acquire photovoltaic power station output data and meteorological satellite data and ground observation data corresponding to the photovoltaic power station output;
[0079] A fusion unit 302 is used to fuse meteorological satellite data and ground observation data to obtain meteorological fusion data;
[0080] The processing unit 303 is configured to obtain meteorological elements based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output;
[0081] The construction unit 304 is used to construct a photovoltaic power station output model based on the photovoltaic power station output data and the meteorological fusion data in combination with meteorological factors.
[0082] Furthermore, the meteorological satellite data corresponding to the output of the photovoltaic power station is obtained in the following way:
[0083] Obtain multi-source meteorological satellite data corresponding to the output of photovoltaic power stations;
[0084] Using ground observation data as a reference and average error and resolution as screening criteria, meteorological satellite data corresponding to the output of photovoltaic power stations are screened from multi-source meteorological satellite data.
[0085] Furthermore, the fusion unit 302 is further configured to:
[0086] Meteorological satellite data and ground observation data are first temporally downscaled and then spatially downscaled to obtain meteorological fusion data; or
[0087] Meteorological satellite data and ground observation data are first spatially downscaled and then temporally downscaled to obtain meteorological fusion data.
[0088] Furthermore, the following method is used for time downscaling:
[0089]
[0090] Among them, y i represents the meteorological satellite data after time downscaling at point i; if time downscaling is performed first, then x it represents the high-precision remote sensing data at point i at time t, including meteorological satellite data and ground observation data; if spatial downscaling is performed first, then x itrepresents the meteorological satellite data after spatial downscaling at point i at time t; (v i ,u i ) represents the geographic location information, ε(v i ,u i ) represents the error function, β0(v i ,u i ) represents the constant term in the time-scale data fusion equation at point i, β t represents the downscaling coefficient at time t, and t represents the data sampling time.
[0091] Furthermore, the following method is used for spatial downscaling:
[0092] If temporal downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data after temporal downscaling;
[0093] If spatial downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data and ground observation data.
[0094] Furthermore, the processing unit 303 is further configured to:
[0095] Based on the output data of photovoltaic power stations and the meteorological fusion data corresponding to the output of photovoltaic power stations, meteorological factors are obtained according to the degree of impact on the output of photovoltaic power stations.
[0096] Furthermore, the construction unit 304 is further configured to:
[0097] The photovoltaic power station output model is constructed as follows:
[0098] P p =η p AI p (u i ,v i ,λ p )f i (y i );
[0099] Among them, P p is the output power of the photovoltaic power station, η p , A are the photovoltaic system conversion efficiency and photovoltaic array area, respectively, p is the tilt angle of the photovoltaic array, (u i ,v i ) is a parameter containing geographic location information, f i (y i ) is the parameter after considering the impact of meteorological factors on photovoltaic output, I p is the light intensity, y i It is meteorological fusion data.
[0100] In the above embodiment, meteorological fusion data is obtained by fusing meteorological satellite data and ground observation data, meteorological elements are obtained based on the output data of the photovoltaic power station and the meteorological fusion data corresponding to the output of the photovoltaic power station, and a photovoltaic power station output model is constructed based on the output data of the photovoltaic power station and the meteorological fusion data in combination with meteorological elements. This can realize the reconstruction of the output of the photovoltaic power station in a refined manner, and can more accurately simulate and predict the actual output of the photovoltaic power generation system, providing technical support for the economic and efficient development and utilization of new energy.
[0101] It should be noted that the apparatus provided in the above embodiments is merely illustrated by the division of the above functional modules when implementing its functions. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.
[0102] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for constructing a photovoltaic power station output model provided in the above embodiments is implemented.
[0103] An embodiment of the present invention also provides an electronic device, comprising: a processor; a memory for storing processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method for constructing a photovoltaic power station output model provided in the above-mentioned embodiments.
[0104] The invention has been described above with reference to a few embodiments. However, it is readily apparent to a person skilled in the art that other embodiments than the ones disclosed above are equally within the scope of the invention, as defined by the appended patent claims.
[0105] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a / the [means, component, etc.]" are to be interpreted openly as referring to at least one instance of the means, component, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not necessarily need to be performed in the exact order disclosed, unless explicitly stated otherwise.
[0106] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0107] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0108] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.
[0109] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.
[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.
Claims
1. A method for constructing a photovoltaic power station output model, characterized in that: The method comprises: Obtaining photovoltaic power station output data and meteorological satellite data and ground observation data corresponding to the photovoltaic power station output; fusing the meteorological satellite data with the ground observation data to obtain meteorological fusion data; Obtaining meteorological elements based on the photovoltaic power station output data and meteorological fusion data corresponding to the photovoltaic power station output; Based on the photovoltaic power station output data and the meteorological fusion data, combined with the meteorological elements, a photovoltaic power station output model is constructed.
2. The method according to claim 1, characterized in that The meteorological satellite data corresponding to the output of the photovoltaic power station is obtained in the following manner: Obtain multi-source meteorological satellite data corresponding to the output of photovoltaic power stations; Taking the ground observation data as a reference and the average error and resolution as screening criteria, the meteorological satellite data corresponding to the output of the photovoltaic power station is screened from the multi-source meteorological satellite data.
3. The method according to claim 1, characterized in that Fusing the meteorological satellite data and the ground observation data to obtain meteorological fusion data includes: downscaling the meteorological satellite data and the ground observation data first in time and then in space to obtain meteorological fusion data; or The meteorological satellite data and the ground observation data are first spatially downscaled and then temporally downscaled to obtain meteorological fusion data.
4. The method according to claim 3, characterized in that The time downscaling is performed using the following method: Among them, y i represents the meteorological satellite data after time downscaling at point i; if time downscaling is performed first, then x it represents the high-precision remote sensing data at point i at time t, including meteorological satellite data and ground observation data; if spatial downscaling is performed first, then x it represents the meteorological satellite data after spatial downscaling at point i at time t; (v i ,u i ) represents geographic location information, e(v i ,u i ) represents the error function, b0(v i ,u i ) represents the constant term in the time-scale data fusion equation at point i, b t represents the downscaling coefficient at time t, and t represents the data sampling time.
5. The method according to claim 3, characterized in that The following method is used for spatial downscaling: If temporal downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data after temporal downscaling; If spatial downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data and the ground observation data.
6. The method according to claim 1, wherein Based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output, meteorological elements are obtained, including: Based on the photovoltaic power station output data and the meteorological fusion data corresponding to the photovoltaic power station output, meteorological factors are obtained according to the degree of influence on the photovoltaic power station output.
7. The method according to claim 1, characterized in that Based on the photovoltaic power station output data and the meteorological fusion data, combined with the meteorological elements, a photovoltaic power station output model is constructed, including: The photovoltaic power station output model is constructed as follows: P p =h p AI p (u i ,v i ,L p )f i (y i ); Among them, P p is the output power of the photovoltaic power station, h p , A are the photovoltaic system conversion efficiency and photovoltaic array area respectively, l p is the tilt angle of the photovoltaic array, (u i ,v i ) is a parameter containing geographic location information, f i (y i ) is the parameter after considering the impact of meteorological factors on photovoltaic output, I p is the light intensity, y i It is meteorological fusion data.
8. A device for constructing a photovoltaic power station output model, characterized in that: The device comprises: An acquisition unit, used to acquire photovoltaic power station output data and meteorological satellite data and ground observation data corresponding to the photovoltaic power station output; a fusion unit, configured to fuse the meteorological satellite data and the ground observation data to obtain meteorological fusion data; a processing unit, configured to obtain meteorological elements based on the photovoltaic power station output data and meteorological fusion data corresponding to the photovoltaic power station output; A construction unit is used to construct a photovoltaic power station output model based on the photovoltaic power station output data and the meteorological fusion data in combination with the meteorological elements.
9. The device according to claim 8, characterized in that The meteorological satellite data corresponding to the output of the photovoltaic power station is obtained in the following manner: Obtain multi-source meteorological satellite data corresponding to the output of photovoltaic power stations; Taking the ground observation data as a reference and the average error and resolution as screening criteria, the meteorological satellite data corresponding to the output of the photovoltaic power station is screened from the multi-source meteorological satellite data.
10. The device according to claim 8, characterized in that The fusion unit is further used for: downscaling the meteorological satellite data and the ground observation data first in time and then in space to obtain meteorological fusion data; or The meteorological satellite data and the ground observation data are first spatially downscaled and then temporally downscaled to obtain meteorological fusion data.
11. The device according to claim 10, characterized in that The time downscaling is performed using the following method: Among them, y i represents the meteorological satellite data after time downscaling at point i; if time downscaling is performed first, then x it represents the high-precision remote sensing data at point i at time t, including meteorological satellite data and ground observation data; if spatial downscaling is performed first, then x it represents the meteorological satellite data after spatial downscaling at point i at time t; (v i ,u i ) represents geographic location information, e(v i ,u i ) represents the error function, b0(v i ,u i ) represents the constant term in the time-scale data fusion equation at point i, b t represents the downscaling coefficient at time t, and t represents the data sampling time.
12. The device according to claim 10, characterized in that The following method is used for spatial downscaling: If temporal downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data after temporal downscaling; If spatial downscaling is performed first, the GWR statistical downscaling method is used to spatially downscale the meteorological satellite data and the ground observation data.
13. The device according to claim 8, characterized in that The processing unit is further configured to obtain meteorological elements according to the degree of influence on the output of the photovoltaic power station based on the output data of the photovoltaic power station and the meteorological fusion data corresponding to the output of the photovoltaic power station.
14. The device according to claim 8, characterized in that The construction unit is further used to construct a photovoltaic power station output model as follows: P p =h p AI p (u i ,v i ,L p )f i (y i ); Among them, P p is the output power of the photovoltaic power station, h p , A are the photovoltaic system conversion efficiency and photovoltaic array area respectively, l p is the tilt angle of the photovoltaic array, (u i ,v i ) is a parameter containing geographic location information, f i (y i ) is the parameter after considering the impact of meteorological factors on photovoltaic output, I p is the light intensity, y i It is meteorological fusion data.
15. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.
16. An electronic device comprising: processor; a memory for storing instructions executable by the processor; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of claims 1 to 7.