Ground photovoltaic power station virtual simulation training system based on real-time operation data

Abstract

The invention discloses a ground photovoltaic power station virtual simulation practical training system based on real-time operation data, relates to the technical field of virtual simulation, and improves the simulation accuracy of a ground photovoltaic power station. According to the method, the associated environment deviation parameters and the associated operation deviation parameters between the operation data and the environment data are set, the virtual simulation practical training network is established according to the equipment distribution diagram of the ground photovoltaic power station, and the real-time simulation trend decision tree is traversed in the virtual simulation practical training network according to the photovoltaic operation and maintenance event to be executed; real-time environment data and real-time operation data of the corresponding photovoltaic operation and maintenance equipment are obtained, the real-time environment data are input into the real-time simulation trend decision tree for analogue simulation, and operation data annotations carried by multiple items of operation data of the photovoltaic operation and maintenance equipment are predicted according to analogue simulation; and comparing the operation data annotations carried by the operation data predictions with the corresponding real-time operation data, and judging whether analogue simulation succeeds or not according to a comparison result.

Description

Technical Field

[0001] The present invention relates to the field of virtual simulation technology, and in particular to a ground photovoltaic power station virtual simulation training system based on real-time operation data. Background Art

[0002] In the operation and maintenance management of modern power systems, ground photovoltaic power stations have received extensive attention due to their environmental protection and sustainability. However, there are many problems in the operation and maintenance management of photovoltaic power stations, such as equipment fault detection, performance optimization and environmental adaptability. Traditional operation and maintenance methods often rely on manual inspections and experience judgment, which are inefficient and costly.

[0003] The existing simulation system has shortcomings in simulating the operation and environmental impact of photovoltaic power stations. It is unable to accurately predict the operating status and potential failures of the equipment, and lacks in-depth analysis and utilization of historical data, making it difficult to achieve intelligent operation and maintenance decision support. For this reason, a ground photovoltaic power station virtual simulation training system based on real-time operation data is provided. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a ground photovoltaic power station virtual simulation training system based on real-time operation data.

[0005] In order to achieve the above object, the present invention provides the following technical solutions: A ground photovoltaic power station virtual simulation training system based on real-time operation data includes a cloud computing platform, wherein the cloud computing platform is communicatively connected with a simulation data acquisition module, a virtual simulation attribute analysis module, and an operation simulation training module; The simulation data acquisition module is used to set multiple sensors for each power equipment in the ground photovoltaic power station, and set a number of photovoltaic operation and maintenance events, and then collect the historical operation records and historical environmental data sets after the ground photovoltaic power station is executed multiple times in a cycle; The virtual simulation attribute analysis module is used to establish a simulation trend decision tree according to the historical operation records of each photovoltaic operation and maintenance event, and to establish a normal change interval and multiple abnormal change intervals according to the historical operation records and historical environmental data sets; According to normal change intervals and multiple abnormal change intervals, each historical data in the historical operation records and historical environment data sets is marked with level abnormal environment data and level abnormal operation data, thereby obtaining the associated environment deviation parameters between each level abnormal operation data mark and each level abnormal environment data mark, as well as the associated operation deviation parameters between each level abnormal operation data; The operation simulation training module is used to obtain the equipment distribution map of the ground photovoltaic power station and the photovoltaic operation and maintenance events to be executed, and establish a virtual simulation training network according to the equipment distribution map of the ground photovoltaic power station, traverse a real-time simulation trend decision tree in the virtual simulation training network according to the photovoltaic operation and maintenance events to be executed, and obtain the real-time environmental data and real-time operation data of the corresponding photovoltaic operation and maintenance equipment; The real-time environmental data is input into the real-time simulation trend decision tree for simulation. According to the associated environmental deviation parameters and the real-time environmental data, multiple operating data of each photovoltaic operation and maintenance equipment are simulated, and the operating data annotations expected to be carried out are compared with the corresponding real-time operating data. The success of the simulation is judged based on the comparison results.

[0006] Furthermore, the collection process of the historical operation records and historical environment data sets includes: The staff uploads the equipment distribution map of the ground photovoltaic power station to the simulation data acquisition module, where the equipment distribution map includes the name, spatial location and interaction direction of each photovoltaic operation and maintenance equipment in the ground photovoltaic power station; Set numbers and multiple sensors for each photovoltaic operation and maintenance equipment in the ground photovoltaic power station, and divide the sensors of each photovoltaic operation and maintenance equipment into environmental sensors and operation sensors; Set up several photovoltaic operation and maintenance events, and then simulate the data acquisition module to collect various photovoltaic operation and maintenance events through sensors, and perform historical operation records and historical environmental data sets after m cycles of execution, and perform the number of executions of each historical operation record and historical environmental data set and the event name of the photovoltaic operation and maintenance event, where m is a natural number greater than 0.

[0007] Furthermore, the photovoltaic operation and maintenance event includes the event name, the photovoltaic operation and maintenance equipment type corresponding to the event center equipment and the event-related equipment, the event duration, and the energy trend diagram; The historical operation record includes several items of historical operation data corresponding to each event center device and event-related device; The historical environment data set includes several items of historical environment data related to each event center device and event-related device.

[0008] Furthermore, the process of establishing the simulation trend decision tree includes: Establish a number of simulation device nodes according to the number of photovoltaic operation and maintenance equipment in the ground photovoltaic power station, and mark each simulation device node with the corresponding photovoltaic operation and maintenance equipment number and name; According to the energy trend diagram of each photovoltaic operation and maintenance event, the corresponding simulation device nodes are retrieved and connected in sequence to obtain m identical simulation trend decision trees. According to the types of photovoltaic operation and maintenance equipment corresponding to the event center equipment and the event-related equipment, the simulation device nodes in the simulation trend decision tree are classified into simulation center equipment nodes and simulation-related equipment nodes.

[0009] Furthermore, the process of establishing the normal change interval and the multiple abnormal change intervals includes: Establish a multi-dimensional coordinate system and set several time nodes, and divide the entire historical change curve into several historical change curve segments through the time nodes; Normally distribute the historical change fragments corresponding to the same photovoltaic operation and maintenance equipment, the same data type and at the same time node, and obtain the normal operation change interval and multiple abnormal operation change intervals of various operation data of each photovoltaic operation and maintenance equipment under each photovoltaic operation and maintenance event based on the normal distribution results; Input the historical operation records corresponding to each photovoltaic operation and maintenance event and the historical change curves in the historical environmental data set into each simulation device node in the corresponding simulation trend decision tree; According to the normal operation change interval and abnormal operation change interval of various operation data, set the level of abnormal operation data labeling and normal operation data labeling for each historical operation data; Selecting several simulation trend decision trees in which all historical operation data of all simulation device nodes are labeled with normal operation data from the m simulation trend decision trees corresponding to the same photovoltaic operation and maintenance event, and recording the selected simulation trend decision trees as normal simulation trend decision trees; The process of obtaining the normal operating change interval and the level of abnormal operating change interval of various operating data is adopted to obtain the normal operating change interval and the abnormal operating change interval of various environmental data, and then set normal environmental data annotations and level of abnormal environmental data annotations for the historical environmental data carried by each simulation device node.

[0010] Furthermore, the process of setting the associated environment deviation parameter and the associated operation deviation parameter includes: Starting from the simulation center device node, determine whether all historical operation data are labeled with normal operation data. If it is determined that all are labeled with normal operation data, then determine whether all historical operation data of the next simulation-related device node are labeled with normal operation data according to the arrow direction of the directed connection line connected to the simulation center device node; When the historical operation data with graded abnormal operation data annotations appear on the same type of photovoltaic operation and maintenance equipment according to the judgment results, the corresponding historical environmental data with graded abnormal environment data annotations are obtained; The occurrence probability of each historical environmental data with abnormal environmental data annotation is counted, and a probability threshold is set. The historical environmental data with abnormal environmental data annotation of the level whose occurrence probability is greater than or equal to the probability threshold is recorded as the abnormal associated environmental data of the corresponding historical operation data of the corresponding type of photovoltaic operation and maintenance equipment. Otherwise, the corresponding historical environmental data with abnormal environmental data annotation is ignored. Obtaining abnormal operation data annotations of different levels, and the probability of simultaneous occurrence of various abnormal associated environment data in abnormal environment data annotations of different levels, and recording the simultaneous occurrence probability between abnormal operation data annotations of each level and abnormal environment data annotations of each level as associated environment deviation parameters; By adopting the process of obtaining the associated environmental deviation parameters, according to the connection status between each simulation device node in the simulation trend decision tree, the probability of simultaneous occurrence of various historical operation data between adjacent sequential simulation device nodes when various levels of abnormal operation data are marked, and the simultaneous occurrence probability is recorded as the associated operation deviation parameter of the corresponding type of historical operation data when the corresponding level of abnormal operation data is marked.

[0011] Furthermore, the virtual simulation training network is composed of a number of simulation device nodes, a corresponding real-time simulation trend decision tree is traversed in the virtual simulation training network, a number of real-time environmental data of each photovoltaic operation and maintenance equipment in the ground photovoltaic power station is obtained from the simulation data acquisition module, and each real-time environmental data is input into the corresponding simulation device node; Determine the numerical range of each item of real-time environmental data, and set a normal environmental data label or a grade abnormal environmental data label for each item of real-time environmental data according to the determination result, and obtain the associated environmental deviation parameters of each grade of abnormal operating data label corresponding to the operating data with the type of real-time environmental data as the abnormal associated environmental data according to the determination result; A normal parameter interval and multiple abnormal parameter intervals are set for each type of operating data, the sum of the associated environmental deviation parameters of each type of operating data is counted, and according to the parameter interval in which the sum of the associated environmental deviation parameters is located, a graded abnormal operating data label or a normal operating data label is set for the corresponding operating data.

[0012] Furthermore, the simulation process of the photovoltaic operation and maintenance event includes: According to the real-time environmental data of the photovoltaic operation and maintenance equipment corresponding to the device nodes of the simulation center, the abnormal operation data labeling or normal operation data labeling expected to be carried by each operation data of the device nodes of the simulation center is simulated, and then according to the trend between the simulation device nodes in the real-time simulation trend decision tree, the abnormal operation data labeling or normal operation data labeling expected to be carried by each operation data of the device nodes associated with the next event is simulated; According to the trend between the simulation device nodes in the real-time simulation trend decision tree, set the abnormal operation data label or normal operation data label for each event-related device node or event center device node in turn, until all the simulation device nodes in the real-time simulation trend decision tree are marked with data, it is judged that the corresponding photovoltaic operation and maintenance event simulation is completed.

[0013] Furthermore, the process of determining whether the simulation is successful includes: Set a total deviation number threshold to determine whether several real-time operation data of each photovoltaic operation and maintenance equipment are within the numerical range corresponding to the abnormal level operation data label or normal operation data label obtained from the photovoltaic operation and maintenance event simulation results, and count the number of real-time operation data that are not within the corresponding numerical range, which is recorded as the total simulation deviation number; If the total simulation deviation number is less than the total deviation number threshold, it is determined that the photovoltaic operation and maintenance event simulation is successful, otherwise it is determined that the photovoltaic operation and maintenance event simulation is unsuccessful.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention sets level abnormal environment data annotations and level abnormal operation data annotations for each historical data in the historical operation records and historical environmental data sets according to normal change intervals and multiple abnormal change intervals, and then obtains the associated environmental deviation parameters between each level abnormal operation data annotation and each level abnormal environment data annotation, as well as the associated operation deviation parameters between each level abnormal operation data, thereby improving the in-depth analysis and utilization of historical data and providing a data basis for subsequent simulation of photovoltaic operation and maintenance equipment.

[0015] 2. The present invention performs simulation by inputting real-time environmental data into a real-time simulation trend decision tree, and simulates multiple operating data of each photovoltaic operation and maintenance equipment according to the simulation, and estimates the operating data annotations, and compares the operating data annotations expected to be carried by each operating data with the corresponding real-time operating data, and determines whether the simulation is successful based on the comparison results, thereby improving the accuracy of the simulated operation results of the photovoltaic power station. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0018] like Figure 1As shown, a ground photovoltaic power station virtual simulation training system based on real-time operation data includes a cloud computing platform, and the cloud computing platform is communicatively connected with a simulation data acquisition module, a virtual simulation attribute analysis module, and an operation simulation training module; The simulation data acquisition module is used to set multiple sensors for each power equipment in the ground photovoltaic power station, and set a number of photovoltaic operation and maintenance events, and then collect the historical operation records and historical environmental data sets after the ground photovoltaic power station is executed multiple times in a cycle; The virtual simulation attribute analysis module is used to establish a simulation trend decision tree according to the historical operation records of each photovoltaic operation and maintenance event, and to establish a normal change interval and multiple abnormal change intervals according to the historical operation records and historical environmental data sets; According to normal change intervals and multiple abnormal change intervals, each historical data in the historical operation records and historical environment data sets is marked with level abnormal environment data and level abnormal operation data, thereby obtaining the associated environment deviation parameters between each level abnormal operation data mark and each level abnormal environment data mark, as well as the associated operation deviation parameters between each level abnormal operation data; The operation simulation training module is used to obtain the equipment distribution map of the ground photovoltaic power station and the photovoltaic operation and maintenance events to be executed, and establish a virtual simulation training network according to the equipment distribution map of the ground photovoltaic power station, traverse a real-time simulation trend decision tree in the virtual simulation training network according to the photovoltaic operation and maintenance events to be executed, and obtain the real-time environmental data and real-time operation data of the corresponding photovoltaic operation and maintenance equipment; The real-time environmental data is input into the real-time simulation trend decision tree for simulation. According to the associated environmental deviation parameters and the real-time environmental data, multiple operating data of each photovoltaic operation and maintenance equipment are simulated, and the operating data annotations expected to be carried out are compared with the corresponding real-time operating data. The success of the simulation is judged based on the comparison results.

[0019] Further, the working principle of the present invention is described below by way of examples: The staff uploads the equipment distribution map of the ground photovoltaic power station to the simulation data acquisition module, where the equipment distribution map includes the name, spatial location and interaction direction of each photovoltaic operation and maintenance equipment in the ground photovoltaic power station; The photovoltaic operation and maintenance equipment includes photovoltaic modules, transformers, inverters, etc.; The simulation data acquisition module sets a number and multiple sensors for each photovoltaic operation and maintenance equipment in the ground photovoltaic power station according to the equipment distribution map, and divides the sensors of each photovoltaic operation and maintenance equipment into environmental sensors and operation sensors. The environmental sensors are used to collect the surrounding environment data of each photovoltaic operation and maintenance equipment, such as external temperature, external humidity, etc.; The operation sensor is used to collect various data under the operation status of photovoltaic operation and maintenance equipment, such as voltage, power, internal temperature value, etc.; The number can be a1, a2, a3, ..., a n , the types of sensors include temperature sensors, voltage sensors, power sensors, etc., n is a natural number greater than 0; It should be noted that the types of sensors carried by various photovoltaic operation and maintenance equipment are not exactly the same. For example, photovoltaic modules are equipped with temperature sensors, current sensors, etc., while transformers are equipped with temperature sensors, voltage sensors, etc.; Set up several photovoltaic operation and maintenance events, and then the simulation data acquisition module collects each photovoltaic operation and maintenance event through sensors, and respectively performs historical operation records and historical environmental data sets after m cycles of execution, and performs the number of executions of each historical operation record and historical environmental data set and the event name of the photovoltaic operation and maintenance event, where m is a natural number greater than 0; The photovoltaic operation and maintenance event includes the event name, the photovoltaic operation and maintenance equipment type corresponding to the event center equipment and the event-related equipment, the event duration, and the energy trend diagram; The historical operation record includes several items of historical operation data corresponding to each event center device and event-related device, such as historical voltage change curve, historical power change curve, etc.; The historical environment data set includes several items of historical environment data related to each event center device and event-related device, such as historical external temperature change curve, historical external humidity change curve, etc.; It should be noted that the various change curves in the historical operation records and historical environmental data sets are marked with the numbers of the corresponding photovoltaic operation and maintenance equipment, and each cycle execution is completed when the photovoltaic operation and maintenance equipment has no hardware defects.

[0020] Further, the simulation data acquisition module sends all historical operation records and historical environment data sets to the virtual simulation attribute analysis module; The virtual simulation attribute parsing module establishes n simulation device nodes according to the number of photovoltaic operation and maintenance equipment in the ground photovoltaic power station, and marks the corresponding photovoltaic operation and maintenance equipment number and name for each simulation device node; According to the energy trend diagram of each photovoltaic operation and maintenance event, the corresponding simulation device nodes are retrieved and connected in sequence to obtain m identical simulation trend decision trees, and according to the types of photovoltaic operation and maintenance equipment corresponding to the event center device and the event-related device, the simulation device nodes in the simulation trend decision tree are classified into simulation center device nodes and simulation-related device nodes. It should be noted that each simulation center device node and simulation-related device node in the simulation trend decision tree is provided with a directed connection line, and the arrow of the directed connection line indicates the direction of energy flow; Establish a multi-dimensional coordinate system, and map various historical change curves in the historical operation records with the event name of the same photovoltaic operation and maintenance event into the same multi-dimensional coordinate system; Since the collection time of each historical change curve is the same, each historical change curve has a common time dimension, and then a coordinate axis is set on the multidimensional coordinate system as a common time axis, and several time nodes are set on the common time axis, and all historical change curves are divided into several historical change curve segments through the time nodes; The historical change segments corresponding to the same photovoltaic operation and maintenance equipment, the same data type and at the same time node are normally distributed, and multiple value intervals are divided on the normal distribution graph. The historical change segments in each value interval are counted, and then the value interval with the largest number of historical change segments is selected as the normal change interval segment, and the remaining value intervals are recorded as abnormal change interval segments; Connect each normal change interval segment and abnormal change interval segment in chronological order, and then obtain the normal operation change interval and multiple abnormal operation change intervals of various operation data of each photovoltaic operation and maintenance equipment under each photovoltaic operation and maintenance event. It should be noted that, according to the interval order between each numerical interval and the numerical interval corresponding to the normal change interval segment, the numerical interval on the right side of the numerical interval corresponding to the normal change interval segment is respectively divided into a first-level abnormal change interval segment, a second-level abnormal change interval segment, etc., among which the first-level abnormal change interval segment has the lightest abnormality, and the subsequent abnormalities are superimposed in sequence; Input the historical operation records corresponding to each photovoltaic operation and maintenance event and the historical change curves in the historical environmental data set into each simulation device node in the corresponding simulation trend decision tree; According to the normal operation change interval and abnormal operation change interval of various operation data, the level abnormal operation data annotation and the normal operation data annotation are set for each historical operation data, wherein the level abnormal operation data annotation is divided into the first level abnormal operation data annotation, the second level abnormal operation data annotation, etc.; Selecting several simulation trend decision trees in which all historical operation data of all simulation device nodes are labeled with normal operation data from the m simulation trend decision trees corresponding to the same photovoltaic operation and maintenance event, and recording the selected simulation trend decision trees as normal simulation trend decision trees; By adopting the process of obtaining the normal operation variation interval and the graded abnormal operation variation interval of various operation data, the historical environmental data of each simulation device node in each normal simulation trend decision tree is mapped to a multi-dimensional coordinate system, thereby obtaining the normal operation variation interval and the abnormal operation variation interval of various environmental data; According to the normal operation variation range and abnormal operation variation range of various historical environmental data, normal environmental data annotation and graded abnormal environmental data annotation are set for the historical environmental data carried by each simulation device node.

[0021] Furthermore, for each simulation trend decision tree of any photovoltaic operation and maintenance event, starting from the simulation center device node, it is determined whether all historical operation data are labeled with normal operation data. If it is determined that all are labeled with normal operation data, then according to the arrow direction of the directed connection line connected to the simulation center device node, it is determined whether all historical operation data of the next simulation associated device node are labeled with normal operation data; When any item of historical operation data is annotated with abnormal operation data of a certain level, the historical operation data corresponding to all photovoltaic operation and maintenance events and the historical environmental data set are used to obtain the historical environmental data corresponding to the abnormal environment data of a certain level when the same type of photovoltaic operation and maintenance equipment has historical operation data annotated with abnormal operation data of a certain level; The occurrence probability of each historical environmental data with abnormal environmental data annotation is counted, and a probability threshold is set. The historical environmental data with abnormal environmental data annotation of the level whose occurrence probability is greater than or equal to the probability threshold is recorded as the abnormal associated environmental data of the corresponding historical operation data of the corresponding type of photovoltaic operation and maintenance equipment. Otherwise, the corresponding historical environmental data with abnormal environmental data annotation is ignored. For any historical operation data of a photovoltaic operation and maintenance equipment, obtain the probability of simultaneous occurrence of the data under different levels of abnormal operation data annotation and each abnormal associated environment data under different levels of abnormal environment data annotation, and record the simultaneous occurrence probability between each level of abnormal operation data annotation and each level of abnormal environment data annotation as the associated environment deviation parameter; By adopting the process of obtaining the associated environment deviation parameter, according to the connection status between each simulation device node in the simulation trend decision tree, the simultaneous occurrence probability of various historical operation data between adjacent sequential simulation device nodes when various levels of abnormal operation data are marked, and the simultaneous occurrence probability is recorded as the associated operation deviation parameter of the corresponding type of historical operation data when the corresponding level of abnormal operation data is marked; For example, for adjacent simulation device nodes α and β, for historical operation data A in simulation device node α, and historical operation data B in simulation device node β, the probability of simultaneous occurrence of historical operation data A and historical operation data B when annotating abnormal operation data of any level is θ, and the associated operation deviation parameter of historical operation data A and historical operation data B when annotating abnormal operation data of the corresponding level is θ; Each associated operation deviation parameter is annotated in the normal simulation trend decision tree of the corresponding photovoltaic operation and maintenance event, and then the virtual simulation attribute analysis module sends all the normal simulation trend decision trees to the operation simulation training module.

[0022] Furthermore, the operation simulation training module establishes a virtual simulation training network according to the equipment distribution diagram of the ground photovoltaic power station; The virtual simulation training network is composed of n simulation device nodes, and the spatial position distribution of each simulation device node in the virtual simulation training network is the same as the spatial position distribution of actual photovoltaic operation and maintenance equipment in a ground photovoltaic power station; The staff uploads the photovoltaic operation and maintenance events to be executed to the operation simulation training module. Then, whenever the operation simulation training module receives a photovoltaic operation and maintenance event, it traverses the corresponding real-time simulation trend decision tree in the virtual simulation training network according to the photovoltaic operation and maintenance equipment types and energy trend diagram corresponding to the event center equipment and event-related equipment in the photovoltaic operation and maintenance event, and matches the corresponding normal simulation trend decision tree according to the photovoltaic operation and maintenance event; Acquire several items of real-time environmental data of each photovoltaic operation and maintenance equipment in the ground photovoltaic power station from the simulation data acquisition module, and input each item of real-time environmental data into the corresponding simulation device node; Determine the numerical range of each real-time environmental data, and set a normal environmental data label or a graded abnormal environmental data label for each real-time environmental data according to the determination result; If the real-time environment data contains normal environment data, no operation is performed; If the real-time environment data is annotated with graded abnormal environment data, then according to the grade of the graded abnormal environment data annotated, the associated environment deviation parameters corresponding to the graded abnormal operation data annotated corresponding to the operation data with the real-time environment data of this type as the abnormal associated environment data are obtained; A normal parameter interval and multiple abnormal parameter intervals are set for each type of operating data, where the abnormal parameter interval is divided into a first-level abnormal parameter interval, a second-level abnormal parameter interval, etc. The extreme values ​​of adjacent levels of abnormal parameter intervals are closed to each other. For example, the normal parameter interval is [0, a], the first-level abnormal parameter interval is (a, b], and the second-level abnormal parameter interval is [b, c), and so on; The sum of the associated environmental deviation parameters of various types of operating data is counted, and according to the parameter range in which the sum of the associated environmental deviation parameters is located, the corresponding operating data is marked with abnormal operating data or normal operating data.

[0023] Furthermore, firstly, according to the real-time environmental data of the photovoltaic operation and maintenance equipment corresponding to the simulation center equipment node, the abnormal operation data labeling or normal operation data labeling expected to be carried by each operation data of the simulation center equipment node is simulated, and then according to the trend between the simulation equipment nodes in the real-time simulation trend decision tree, the abnormal operation data labeling or normal operation data labeling expected to be carried by each operation data of the next event-related equipment node is simulated; The simulation process of data annotation of the event-related device node includes: First, according to the real-time environmental data of the photovoltaic operation and maintenance equipment corresponding to the event-related device node, the sum of the associated environmental deviation parameters of each type of operation data is obtained, and then it is determined according to the real-time simulation trend decision tree whether the previous event-related device node or the event center device node has operation data with level abnormal operation data annotation; If it does not exist, no operation is performed; if it does exist, the associated operation deviation parameters between the corresponding levels of abnormal operation data annotations between the corresponding simulation device nodes are obtained, the associated operation deviation parameters are added to the sum of the associated environment deviation parameters, and the parameter interval in which the sum of the associated environment deviation parameters is located is determined, and the level of abnormal operation data annotation or normal operation data annotation is set for the event-associated device node according to the judgment result; According to the trend between the simulated device nodes in the real-time simulation trend decision tree, set the level of abnormal operation data labeling or normal operation data labeling for each event-related device node or event center device node in turn, until all the simulated device nodes in the real-time simulation trend decision tree are marked with data, it is judged that the corresponding photovoltaic operation and maintenance event simulation is completed; Execute the photovoltaic operation and maintenance events uploaded by the staff at the ground photovoltaic power station, obtain several real-time operation data corresponding to each photovoltaic operation and maintenance equipment, and set the total deviation quantity threshold; Determine whether several items of real-time operation data of each photovoltaic operation and maintenance equipment are within the numerical range corresponding to the abnormal level operation data label or the normal level operation data label obtained by the photovoltaic operation and maintenance event simulation result, and count the number of real-time operation data that are not within the corresponding numerical range, which is recorded as the total simulation deviation number; If the total number of simulation deviations is less than the total deviation number threshold, the simulation of the photovoltaic operation and maintenance event is judged to be successful, otherwise the simulation of the photovoltaic operation and maintenance event is judged to be unsuccessful, and then according to the real-time operation data and real-time environmental data of each photovoltaic operation and maintenance equipment during the execution of the corresponding photovoltaic operation and maintenance event, the corresponding historical operation records and historical environmental data sets are generated, and the historical operation records and historical environmental data sets are sent to the virtual simulation attribute parsing module, and then the various associated environmental deviation parameters and associated operation deviation parameters are corrected.

[0024] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A ground photovoltaic power station virtual simulation training system based on real-time operation data, including a cloud computing platform, characterized in that: The cloud computing platform is communicatively connected with a simulation data acquisition module, a virtual simulation attribute analysis module and an operation simulation training module; The simulation data acquisition module is used to set multiple sensors for each power equipment in the ground photovoltaic power station, and set a number of photovoltaic operation and maintenance events, and then collect the historical operation records and historical environmental data sets after the ground photovoltaic power station is executed multiple times in a cycle; The virtual simulation attribute analysis module is used to establish a simulation trend decision tree according to the historical operation records of each photovoltaic operation and maintenance event, and to establish a normal change interval and multiple abnormal change intervals according to the historical operation records and historical environmental data sets; According to normal change intervals and multiple abnormal change intervals, each historical data in the historical operation records and historical environment data sets is marked with level abnormal environment data and level abnormal operation data, thereby obtaining the associated environment deviation parameters between each level abnormal operation data mark and each level abnormal environment data mark, as well as the associated operation deviation parameters between each level abnormal operation data; The operation simulation training module is used to obtain the equipment distribution map of the ground photovoltaic power station and the photovoltaic operation and maintenance events to be executed, and establish a virtual simulation training network according to the equipment distribution map of the ground photovoltaic power station, traverse a real-time simulation trend decision tree in the virtual simulation training network according to the photovoltaic operation and maintenance events to be executed, and obtain the real-time environmental data and real-time operation data of the corresponding photovoltaic operation and maintenance equipment; The real-time environmental data is input into the real-time simulation trend decision tree for simulation. According to the associated environmental deviation parameters and the real-time environmental data, multiple operating data of each photovoltaic operation and maintenance equipment are simulated, and the operating data annotations expected to be carried out are compared with the corresponding real-time operating data. The success of the simulation is judged based on the comparison results.

2. The ground photovoltaic power station virtual simulation training system based on real-time operation data according to claim 1 is characterized in that: The collection process of the historical operation records and historical environment data sets includes: The equipment distribution map of the ground photovoltaic power station is uploaded to the simulation data acquisition module. The equipment distribution map includes the name, spatial location and interaction direction of each photovoltaic operation and maintenance equipment in the ground photovoltaic power station. Several photovoltaic operation and maintenance events are set, and the historical operation records and historical environmental data sets of each photovoltaic operation and maintenance event after m cycles are executed are collected through sensors, where m is a natural number greater than 0.

3. The ground photovoltaic power station virtual simulation training system based on real-time operation data according to claim 2 is characterized in that: The photovoltaic operation and maintenance event includes the event name, the photovoltaic operation and maintenance equipment type corresponding to the event center equipment and the event-related equipment, the event duration, and the energy trend diagram; The historical operation record includes several items of historical operation data corresponding to each event center device and event-related device, and the historical environment data set includes several items of historical environment data related to each event center device and event-related device.

4. The ground photovoltaic power station virtual simulation training system based on real-time operation data according to claim 3 is characterized in that: The establishment process of the simulation trend decision tree includes: According to the number of photovoltaic operation and maintenance equipment in the ground photovoltaic power station, several simulation device nodes are established. According to the energy trend diagram of each photovoltaic operation and maintenance event, the simulation device nodes are retrieved and connected in sequence to obtain m identical simulation trend decision trees. According to the types of photovoltaic operation and maintenance equipment corresponding to the event center equipment and the event associated equipment, the simulation device nodes in the simulation trend decision tree are classified into simulation center equipment nodes and simulation associated equipment nodes.

5. The ground photovoltaic power station virtual simulation training system based on real-time operation data according to claim 4 is characterized in that: The process of establishing the normal change interval and the multiple abnormal change intervals includes: Establish a multi-dimensional coordinate system and set several time nodes, divide all historical change curves into several historical change curve segments through time nodes, and normally distribute the historical change segments of the same photovoltaic operation and maintenance equipment, the same data type and at the same time node. According to the normal distribution results, obtain the normal operation change interval and multiple abnormal operation change intervals of various operation data of each photovoltaic operation and maintenance equipment under each photovoltaic operation and maintenance event; According to the normal operation change interval and abnormal operation change interval of various operation data, set the level of abnormal operation data labeling and normal operation data labeling for each historical operation data; The process of obtaining the normal operation change interval and the graded abnormal operation change interval of various operation data is adopted to obtain the normal operation change interval and the abnormal operation change interval of various environmental data, and then set normal environmental data labels and graded abnormal environmental data labels for each historical environmental data.

6. The ground photovoltaic power station virtual simulation training system based on real-time operation data according to claim 5 is characterized in that: The process of setting the associated environment deviation parameter and the associated operation deviation parameter includes: Starting from the simulation center device node, determine whether each historical operation data is labeled with normal operation data. If it is determined that each historical operation data is labeled with normal operation data, determine whether each historical operation data of the next simulation associated device node is labeled with normal operation data. Otherwise, when the historical operation data with abnormal level operation data annotations of the same type of photovoltaic operation and maintenance equipment is obtained, the corresponding historical environmental data with abnormal level environment data annotations are obtained; The occurrence probability of each historical environmental data with abnormal environmental data annotation is counted, and a probability threshold is set. The historical environmental data with abnormal environmental data annotation of level with an occurrence probability greater than or equal to the probability threshold is recorded as abnormal associated environmental data of the corresponding historical operation data of the corresponding type of photovoltaic operation and maintenance equipment, otherwise the corresponding historical environmental data is ignored; For any historical operation data of a photovoltaic operation and maintenance equipment, obtain the probability of simultaneous occurrence of the data under different levels of abnormal operation data annotation and each abnormal associated environmental data under different levels of abnormal environmental data annotation, and record the simultaneous occurrence probability as the associated environmental deviation parameter; By adopting the process of obtaining the associated environmental deviation parameters, according to the connection status between each simulation device node in the simulation trend decision tree, the probability of simultaneous occurrence of various historical operation data between adjacent sequential simulation device nodes when abnormal operation data of each level is marked, and the simultaneous occurrence probability is recorded as the associated operation deviation parameter of the corresponding type of historical operation data when abnormal operation data of the corresponding level is marked.

7. The ground photovoltaic power station virtual simulation training system based on real-time operation data according to claim 6 is characterized in that: The simulation process of the photovoltaic operation and maintenance event includes: The virtual simulation training network is composed of a number of simulation device nodes, which obtains a number of real-time environmental data of each photovoltaic operation and maintenance equipment in the ground photovoltaic power station; Determine the environmental change interval of each real-time environmental data, and set a normal environmental data label or a grade abnormal environmental data label for each real-time environmental data according to the determination result, and then obtain the associated environmental deviation parameters corresponding to each grade abnormal operating data label of the operating data with each real-time environmental data as the abnormal associated environmental data; A normal parameter interval and multiple abnormal parameter intervals are set for each type of operating data, the sum of the associated environmental deviation parameters of each type of operating data is counted, and according to the parameter interval in which the sum of the associated environmental deviation parameters is located, a graded abnormal operating data label or a normal operating data label is set for each operating data.

8. The ground photovoltaic power station virtual simulation training system based on real-time operation data according to claim 7 is characterized in that: The simulation process of the photovoltaic operation and maintenance event also includes: According to the real-time environmental data of the photovoltaic operation and maintenance equipment corresponding to the simulation center device node, the abnormal operation data labeling or normal operation data labeling expected to be carried by each operation data in the simulation center device node is simulated, and the abnormal operation data labeling or normal operation data labeling expected to be carried by each operation data of the next event-related device node is simulated in turn, until all the simulation device nodes in the real-time simulation trend decision tree are marked with data, it is judged that the simulation of the corresponding photovoltaic operation and maintenance event is completed.

9. The ground photovoltaic power station virtual simulation training system based on real-time operation data according to claim 8 is characterized in that: The process of judging whether the simulation is successful includes: A total deviation number threshold is set to determine whether several real-time operating data of each photovoltaic operation and maintenance equipment are within the numerical range corresponding to the abnormal level operation data label or the normal operation data label obtained in the photovoltaic operation and maintenance event simulation results, and the number of real-time operation data that are not within the corresponding numerical range is counted and recorded as the total simulation deviation number. If the total simulation deviation number is less than the total deviation number threshold, the photovoltaic operation and maintenance event simulation is judged to be successful, otherwise the photovoltaic operation and maintenance event simulation is judged to be unsuccessful.

Images