A method for analyzing and evaluating the carrying capacity of photovoltaic power generation

Abstract

The invention discloses a method for analyzing and evaluating the carrying capacity of photovoltaic power generation, which comprises the following steps: obtaining basic data of a photovoltaic power generation system, obtaining available access points from the basic data; calculating the theoretical capacity of the available access points, screening the available access points based on the distributed photovoltaic capacity to be connected, and obtaining a first access point; constructing a DIKW model of a power generation system based on the basic data of the photovoltaic power generation system; obtaining several application scenarios of the first access point; the DIKW model of the power generation system evaluates the actual capacity of distributed photovoltaic access to the first access point based on different application scenarios; after preliminary screening of the available access points, the number of access points that need to be calculated can be reduced, and the efficiency of analysis and evaluation can be improved; and then the DIKW model of the power generation system constructed in combination with the DIKW knowledge graph can obtain the actual capacity of the photovoltaic power generation system after the distributed photovoltaic access in different application scenarios, evaluate the carrying capacity, and thus select a suitable access point for the access of the distributed photovoltaic.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and in particular to a method for analyzing and evaluating the bearing capacity of photovoltaic power generation. Background Art

[0002] With the continuous increase in population, the pressure on electricity consumption is also increasing. Traditional thermal power generation and hydropower generation can no longer meet people's normal electricity needs, and traditional power generation methods are also prone to cause environmental pollution. Therefore, people have explored more clean energy. Among them, photovoltaic power generation refers to the power generation method of converting solar energy into electrical energy. After absorbing and converting solar energy through large-area photovoltaic panels, the electrical energy can be used after voltage stabilization and processing. Compared with thermal power generation, photovoltaic power generation does not produce gases that pollute the environment, and the source is easy and reliable, so it has been widely promoted.

[0003] In photovoltaic power generation systems, they generally operate according to a preset topological structure. According to different policies and plans in different regions, some distributed photovoltaics need to be connected to the photovoltaic system. Distributed photovoltaics cannot be used simply by being incorporated into the system. When connecting to the photovoltaic power generation system, it is necessary to consider whether the capacity of the photovoltaic power generation system can allow the access of distributed photovoltaics. At the same time, voltage fluctuations, harmonic pollution, and grid planning and scheduling must also be considered. In other words, the carrying capacity of the photovoltaic power generation system needs to be analyzed. However, the current carrying capacity analysis mostly only stays in the access of distributed photovoltaics, and does not select and confirm the application scenarios at the time of access, resulting in grid fluctuations in actual applications, affecting normal power generation, transmission and distribution. Summary of the invention

[0004] In view of this, the present invention proposes a carrying capacity analysis and evaluation method for photovoltaic power generation, which can analyze and evaluate the carrying capacity based on different application scenarios to ensure the reliability of distributed photovoltaic access to the photovoltaic power generation system.

[0005] The technical solution of the present invention is achieved in this way:

[0006] A method for analyzing and evaluating the carrying capacity of photovoltaic power generation comprises the following steps:

[0007] Step S1, obtaining basic data of a photovoltaic power generation system, and obtaining available access points from the basic data;

[0008] Step S2: Calculate the theoretical capacity of available access points, screen the available access points based on the distributed photovoltaic capacity to be connected, and obtain a first access point;

[0009] Step S3, constructing a DIKW model of the power generation system based on basic data of the photovoltaic power generation system;

[0010] Step S4, obtaining several application scenarios of the first access point;

[0011] Step S5: the power generation system DIKW model evaluates the actual capacity of the distributed photovoltaic access to the first access point based on different application scenarios.

[0012] Preferably, the specific steps of step S1 are:

[0013] Step S11, obtaining daily usage data, topology, line parameters, transformer capacity, and load distribution of the photovoltaic power generation system;

[0014] Step S12: obtaining a theoretical access point according to the topological structure;

[0015] Step S13: searching for available access points in use from theoretical access points according to daily usage data of the photovoltaic power generation system.

[0016] Preferably, the specific steps of step S2 are:

[0017] Step S21, dividing the photovoltaic power generation system into regions and determining the regions to which the available access points belong;

[0018] Step S22, obtaining line parameters, transformer capacity and current load conditions in the area;

[0019] Step S23, evaluating the maximum power limit and remaining power capacity of the area according to the line parameters, transformer capacity and current load conditions;

[0020] Step S24: outputting the available access point whose maximum power limit and remaining power capacity meet the distributed photovoltaic capacity to be connected as the first access point.

[0021] Preferably, the specific steps of step S3 are:

[0022] Step S31: Map the basic data into typed data, where the typed data includes data resources, information resources, and knowledge resources;

[0023] Step S32: construct a DIKW model of the power generation system according to the typed data.

[0024] Preferably, the data resources, information resources and knowledge resources can be transformed and combined with each other.

[0025] Preferably, the specific steps of step S4 are:

[0026] Step S41, obtaining the specific geographical location of the first access point;

[0027] Step S42: acquiring an objective scene of the first access point based on the specific geographical location, wherein the objective scene includes different weather and disasters;

[0028] Step S43: acquiring a subjective scenario of the first access point based on the specific geographical location, wherein the subjective scenario includes economic evaluation, policies and regulations, market scheduling, and strategic planning;

[0029] Step S44: randomly select an objective scene and at least one subjective scene to form an application scene.

[0030] Preferably, the specific steps of step S42 are: determining the local climate type according to the specific geographical location of the first access point, obtaining the weather that occurs at the first access point on an annual basis according to the climate type, and obtaining historical disaster information according to the specific geographical location, and determining the disasters that may occur at the location of the first access point according to the historical disaster information.

[0031] Preferably, after step S43, the following steps are further included:

[0032] Step S43a: determine the subjective needs of the distributed photovoltaic system to be connected, and screen the subjective scenarios from the subjective needs.

[0033] Preferably, the specific steps of step S5 are:

[0034] Step S51, the power generation system DIKW model randomly connects the distributed photovoltaic to a first access point;

[0035] Step S52: The DIKW model of the power generation system is introduced into an application scenario, and voltage fluctuation data and harmonic change data of the distributed photovoltaic connected to the first access point in the application scenario are obtained;

[0036] Step S53: Evaluate the actual capacity of the first access point for distributed photovoltaic access based on the voltage fluctuation data and the harmonic change data.

[0037] Preferably, the step S5 further comprises:

[0038] Step S54: display the actual capacity of distributed photovoltaics by the first access point in different scenarios.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] ① After obtaining the basic data of the photovoltaic power generation system, the available access points can be found from the basic data, and the theoretical capacity of the available access points and the capacity of the distributed photovoltaics to be connected can be used for preliminary screening to obtain the first access point that can actually be used, and then the first access point can be evaluated, which can reduce the amount of data for evaluation and improve data processing efficiency;

[0041] ② After obtaining the first access point, the DIKW model of the power generation system is constructed in combination with the DIKW knowledge graph. After obtaining several application scenarios of the first access point, the actual capacity of distributed photovoltaics after access can be evaluated according to different application scenarios through the DIKW model of the power generation system. This can determine the carrying capacity of the photovoltaic power generation system under different application scenarios to ensure that the access of distributed photovoltaics will not affect the normal operation of the photovoltaic power generation system in any application scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0043] Figure 1 It is a flow chart of a method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to the present invention;

[0044] Figure 2 It is a flow chart of step S1 of a method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to the present invention;

[0045] Figure 3 It is a flow chart of step S2 of a method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to the present invention;

[0046] Figure 4 It is a flow chart of step S3 of a method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to the present invention;

[0047] Figure 5 It is a flow chart of step S4 of a method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to the present invention;

[0048] Figure 6 This is a flow chart of step S5 of a method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to the present invention. DETAILED DESCRIPTION

[0049] In order to better understand the technical content of the present invention, a specific embodiment is provided below, and the present invention is further described in conjunction with the accompanying drawings.

[0050] See also Figures 1 to 6 The present invention provides a method for analyzing and evaluating the carrying capacity of photovoltaic power generation, comprising the following steps:

[0051] Step S1, obtaining basic data of a photovoltaic power generation system, and obtaining available access points from the basic data;

[0052] Step S2: Calculate the theoretical capacity of available access points, screen the available access points based on the distributed photovoltaic capacity to be connected, and obtain a first access point;

[0053] Step S3, constructing a DIKW model of the power generation system based on basic data of the photovoltaic power generation system;

[0054] Step S4, obtaining several application scenarios of the first access point;

[0055] Step S5: the power generation system DIKW model evaluates the actual capacity of the distributed photovoltaic access to the first access point based on different application scenarios.

[0056] The invention discloses a method for analyzing and evaluating the carrying capacity of photovoltaic power generation, which is used to analyze and evaluate the carrying capacity of distributed photovoltaic when connected to a photovoltaic power generation system. The method first obtains basic data of the photovoltaic power generation system, and then obtains the available access points in use from the basic data. The available access points are the entrances for distributed photovoltaic to be connected to the photovoltaic power generation system, but not all available access points can be used for distributed photovoltaic access. First, the theoretical capacity of the available access points needs to be calculated, and the theoretical capacity is compared with the capacity of the distributed photovoltaic to be connected. After the available access points that do not meet the requirements are screened out, the remaining available access points are the available access points that can be used for distributed photovoltaic access in theory, so that the available access points are output as the first access points. By screening the access points, the number of access points for subsequent calculation can be reduced, and the efficiency of the carrying capacity analysis and evaluation can be improved.

[0057] After obtaining the basic data of the photovoltaic power generation system, a DIKW model of the power generation system is constructed based on the basic data. The DIKW knowledge graph is combined with the photovoltaic power generation system to improve the data processing efficiency, and the data have the ability to convert each other, reducing the source of data acquisition. After constructing the DIKW model of the power generation system, several application scenarios of the first access point are obtained. The application scenario refers to the various scenarios that may exist when distributed photovoltaics are connected to the first access point. In different scenarios, the access of distributed photovoltaics may have different degrees of impact on the photovoltaic power generation system. Therefore, after obtaining multiple application scenarios, the virtual scene is simulated through the DIKW model of the power generation system, in which distributed photovoltaics will be connected to different first access points. After changing the application scenario, the actual capacity can be determined according to the data changes of the photovoltaic power generation system when the distributed photovoltaics are connected. Based on the actual capacity, the carrying capacity of the photovoltaic power generation system can be evaluated, and then a number of first access points that meet the evaluation results can be determined. Finally, the first access point can be selected according to actual needs for the access of distributed photovoltaics.

[0058] Preferably, the specific steps of step S1 are:

[0059] Step S11, obtaining daily usage data, topology, line parameters, transformer capacity, and load distribution of the photovoltaic power generation system;

[0060] Step S12: obtaining a theoretical access point according to the topological structure;

[0061] Step S13: searching for available access points in use from theoretical access points according to daily usage data of the photovoltaic power generation system.

[0062] After obtaining the topological data of the photovoltaic power generation system, the planned theoretical access points can be obtained from the topological data. The theoretical access points may change during long-term use. Therefore, based on the daily use data of the photovoltaic power generation system, it can be determined whether the theoretical access points are in use, and then the theoretical access points in use can be output as available access points.

[0063] Preferably, the specific steps of step S2 are:

[0064] Step S21, dividing the photovoltaic power generation system into regions and determining the regions to which the available access points belong;

[0065] Step S22, obtaining line parameters, transformer capacity and current load conditions in the area;

[0066] Step S23, evaluating the maximum power limit and remaining power capacity of the area according to the line parameters, transformer capacity and current load conditions;

[0067] Step S24: outputting the available access point whose maximum power limit and remaining power capacity meet the distributed photovoltaic capacity to be connected as the first access point.

[0068] After obtaining the available access points, the photovoltaic power generation system is divided into regions, where each available access point has its own region. The regions have structural differences depending on the buildings and population. Therefore, after obtaining the line parameters, transformer capacity and current load conditions of the region, the maximum power limit and remaining power capacity of the region can be evaluated. The maximum power limit and remaining power capacity can be used to determine whether the distributed photovoltaic to be connected can be connected. The capacity of the distributed photovoltaic is compared with the maximum power limit and the remaining power capacity, and then the available access points that do not meet the requirements are eliminated, and the remaining available access points can be output as the first access points.

[0069] Preferably, the specific steps of step S3 are:

[0070] Step S31: Map the basic data into typed data, wherein the typed data includes data resources, information resources and knowledge resources, and the data resources, information resources and knowledge resources can be transformed and combined with each other;

[0071] Step S32: construct a DIKW model of the power generation system according to the typed data.

[0072] The present invention creatively combines the DIKW knowledge graph into the photovoltaic power generation system, wherein the data resources, information resources and knowledge resources can be converted and combined with each other, thereby generating deeper resources. At the same time, the acquired resources will be continuously updated to enrich the database of the DIKW model of the power generation system. The DIKW model of the power generation system constructed according to the typed data can be used to simulate the state of distributed photovoltaics when connected to the system, so that an evaluation can be performed before the distributed photovoltaics are connected to avoid the impact of the distributed photovoltaics on the photovoltaic power generation system after the connection.

[0073] Preferably, the specific steps of step S4 are:

[0074] Step S41, obtaining the specific geographical location of the first access point;

[0075] Step S42: acquiring an objective scene of the first access point based on the specific geographical location, wherein the objective scene includes different weather and disasters;

[0076] Step S43: acquiring a subjective scenario of the first access point based on the specific geographical location, wherein the subjective scenario includes economic evaluation, policies and regulations, market scheduling, and strategic planning;

[0077] Step S43a, determining the subjective needs of the distributed photovoltaics to be connected, and screening the subjective scenarios from the subjective needs;

[0078] Step S44: randomly select an objective scene and at least one subjective scene to form an application scene.

[0079] There are many photovoltaic power generation systems, covering a wide range. Photovoltaic power generation systems in different regions face different problems. Therefore, it is necessary to obtain the specific geographical location of the first access point, and then obtain the objective scenario and subjective scenario respectively according to the specific geographical location. The objective scenario is the weather and disasters that may occur at the location of the first access point, such as heavy rain, snow, long-term exposure to the sun, typhoons and earthquakes, while the subjective scenario is the direction of human consideration, including economic evaluation, local policies and regulations, market scheduling and strategic planning, etc. Under different objective scenarios and different subjective scenarios, the impact of distributed photovoltaic access to the photovoltaic power generation system is different. Therefore, it is necessary to focus on multiple application scenarios. After obtaining the subjective scenario, it is also necessary to judge the subjective needs of the distributed photovoltaic to be connected, including whether to focus on economic construction issues, local regulations and future planning issues. After the subjective scenario is screened, the subjective scenario and the objective scenario are combined to form an application scenario. The application scenario can only include one objective scenario, and the subjective scenario is at least one, so it can be combined to form a plurality of application scenarios.

[0080] Preferably, the specific steps of step S42 are: determining the local climate type according to the specific geographical location of the first access point, obtaining the weather that occurs at the first access point on an annual basis according to the climate type, and obtaining historical disaster information according to the specific geographical location, and determining the disasters that may occur at the location of the first access point according to the historical disaster information.

[0081] When obtaining the objective scenario, the determination is made based on the local climate type of the first access point and the disasters that have occurred in the past, so that the access status of the distributed photovoltaic under the objective scenario can be specifically simulated.

[0082] Preferably, the specific steps of step S5 are:

[0083] Step S51, the power generation system DIKW model randomly connects the distributed photovoltaic to a first access point;

[0084] Step S52: The DIKW model of the power generation system is introduced into an application scenario, and voltage fluctuation data and harmonic change data of the distributed photovoltaic connected to the first access point in the application scenario are obtained;

[0085] Step S53: Evaluate the actual capacity of the first access point for distributed photovoltaic access based on the voltage fluctuation data and the harmonic change data.

[0086] Step S54: display the actual capacity of distributed photovoltaics by the first access point in different scenarios.

[0087] After confirming the application scenario, the DIKW model of the power generation system is used to evaluate the carrying capacity. Since there are multiple first access points and application scenarios, it is necessary to evaluate the combination of each first access point and application scenario. After selecting a first access point, the application scenarios are introduced in the DIKW model of the power generation system in turn, and the voltage fluctuation data and harmonic change data of the distributed photovoltaic access to the first access point under the application scenario are obtained. The actual capacity can be evaluated through the voltage fluctuation data and the harmonic change data. The actual capacity is the performance of the carrying capacity of the photovoltaic power generation system. Finally, after displaying the actual capacity of all first access points in all application scenarios, the staff can select the first access point for distributed photovoltaic access as needed.

[0088] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for analyzing and evaluating the carrying capacity of photovoltaic power generation, characterized in that: The following steps are involved: Step S1, obtaining basic data of a photovoltaic power generation system, and obtaining available access points from the basic data; Step S2: Calculate the theoretical capacity of available access points, screen the available access points based on the distributed photovoltaic capacity to be connected, and obtain a first access point; Step S3, constructing a DIKW model of the power generation system based on basic data of the photovoltaic power generation system; Step S4, obtaining several application scenarios of the first access point; Step S5, the power generation system DIKW model evaluates the actual capacity of distributed photovoltaic access to the first access point based on different application scenarios; The specific steps of step S4 are: Step S41, obtaining the specific geographical location of the first access point; Step S42: acquiring an objective scene of the first access point based on the specific geographical location, wherein the objective scene includes different weather and disasters; Step S43: acquiring a subjective scenario of the first access point based on the specific geographical location, wherein the subjective scenario includes economic evaluation, policies and regulations, market scheduling, and strategic planning; Step S44, randomly selecting an objective scene and at least one subjective scene to form an application scene; The specific steps of step S5 are: Step S51, the power generation system DIKW model randomly connects the distributed photovoltaic to a first access point; Step S52: The DIKW model of the power generation system is introduced into an application scenario, and voltage fluctuation data and harmonic change data of the distributed photovoltaic connected to the first access point in the application scenario are obtained; Step S53: Evaluate the actual capacity of the first access point for distributed photovoltaic access based on the voltage fluctuation data and the harmonic change data.

2. A method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to claim 1, characterized in that: The specific steps of step S1 are: Step S11, obtaining daily usage data, topology, line parameters, transformer capacity, and load distribution of the photovoltaic power generation system; Step S12: obtaining a theoretical access point according to the topological structure; Step S13: searching for available access points in use from theoretical access points according to daily usage data of the photovoltaic power generation system.

3. A method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to claim 1, characterized in that: The specific steps of step S2 are: Step S21, dividing the photovoltaic power generation system into regions and determining the regions to which the available access points belong; Step S22, obtaining line parameters, transformer capacity and current load conditions in the area; Step S23, evaluating the maximum power limit and remaining power capacity of the area according to the line parameters, transformer capacity and current load conditions; Step S24: outputting the available access point whose maximum power limit and remaining power capacity meet the distributed photovoltaic capacity to be connected as the first access point.

4. A method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to claim 1, characterized in that: The specific steps of step S3 are: Step S31: Map the basic data into typed data, where the typed data includes data resources, information resources, and knowledge resources; Step S32: construct a DIKW model of the power generation system according to the typed data.

5. A method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to claim 4, characterized in that: The data resources, information resources and knowledge resources can be transformed and combined with each other.

6. A method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to claim 1, characterized in that: The specific steps of step S42 are: determining the local climate type according to the specific geographical location of the first access point, obtaining the weather that occurs at the first access point in an annual cycle according to the climate type, obtaining historical disaster information according to the specific geographical location, and determining the disasters that may occur at the location of the first access point according to the historical disaster information.

7. A method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to claim 1, characterized in that: After step S43, the following steps are further included: Step S43a: determine the subjective needs of the distributed photovoltaic system to be connected, and screen the subjective scenarios from the subjective needs.

8. A method for analyzing and evaluating the carrying capacity of photovoltaic power generation according to claim 1, characterized in that: The step S5 further comprises: Step S54: display the actual capacity of distributed photovoltaics by the first access point in different scenarios.

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