Photovoltaic station intelligent inspection method and system based on object model
By constructing a full-site object model in the photovoltaic station and collecting operating parameters in real-time, the problem of insufficient definition of equipment object model in the operation and maintenance of the photovoltaic station is solved, and efficient and intelligent inspection and operation safety guarantee are achieved.
Patent Information
- Application Number
- CN202411442475.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-16
- Publication Date
- 2025-02-25
AI Technical Summary
The lack of definition of equipment object models in the operation and maintenance of photovoltaic stations results in the fact that similar equipment collects more preprocessing steps and poor versatility due to different specifications, and the collection cost of key data required for equipment monitoring is too high.
The intelligent inspection method of photovoltaic stations based on object model is adopted to construct the object model of the entire site and complete the parameter configuration of object model, collect the operating parameters of key equipment in real time, implement the faulty equipment locking strategy, and obtain the intelligent inspection results in combination with the object model.
By building a full-site station object model for photovoltaic sites, data preprocessing steps are reduced, data universality and collection efficiency are improved, equipment monitoring costs are reduced, efficient and intelligent inspection is achieved, and the operational safety of photovoltaic sites is ensured.
Smart Images
Figure CN119519592A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of intelligent inspection of photovoltaic stations, and specifically to an intelligent inspection method and system for photovoltaic stations based on a physical model. Background Art
[0002] In the daily operation and maintenance process of photovoltaic stations, SCADA (Supervisory Control And Data Acquisition) systems are usually used to collect various key data in real time. Such systems can continuously monitor many equipment and operating parameters in the station to ensure the real-time update and accuracy of information. However, in actual applications, due to the huge amount of data involved and the lack of effective linkage and intelligent analysis between various data points, this often leads to a large number of invalid alarms. Although these alarms remind operation and maintenance personnel to pay attention to potential problems, in fact, they may cause a waste of operation and maintenance resources due to lack of accuracy, forcing operation and maintenance personnel to frequently go to the site for uninterrupted inspections and maintenance work to ensure the normal operation of the equipment and the safety and stability of the station.
[0003] The function realization of photovoltaic SCADA (supervisory control and data acquisition) system has certain limitations. Currently, it can only realize the alarm and statistics functions. However, due to the randomness and strong volatility of the output of photovoltaic arrays, the false alarm rate is high, which further leads to unsatisfactory site operation and maintenance efficiency. In addition, due to the lack of definition of equipment object model, the data collected by similar equipment has more pre-processing steps due to different specifications and poor versatility, which undoubtedly increases the cost of key data collection.
[0004] For general fault alarm analysis algorithms, they are usually trained on a general algorithm model using historical data. The service performance of this algorithm mainly depends on the amount and scope of data, but for newly built sites, these algorithm services are often difficult to apply directly, which results in the inability to improve operation and maintenance efficiency through algorithms within 2-3 years after commissioning. These problems have limited the performance and application effect of the photovoltaic SCADA system to a certain extent, and solutions are urgently needed to improve its operating efficiency and accuracy.
[0005] With the continuous advancement and popularization of IoT technology, a more efficient data collection and intelligent management method has become feasible. Using IoT devices, not only can the remote monitoring of various components and key facilities in photovoltaic stations be achieved, but also the collected data can be analyzed and processed in real time through advanced data processing algorithms. This intelligent data processing method enables station operation and maintenance personnel to obtain more accurate and useful information in a timely manner, thereby effectively reducing the number of invalid alarms and improving operation and maintenance efficiency.
[0006] The combination of IoT technology and advanced algorithms not only improves the data collection and processing capabilities of new energy stations, but also greatly expands its application scope. In the operation and maintenance management of photovoltaic stations, this technology is widely used in equipment failure prediction and prevention, energy efficiency improvement, operating cost reduction, and station safety monitoring. In this way, the management and operation of photovoltaic stations become more intelligent and efficient, which helps to promote the sustainable development and technological progress of the new energy industry. Summary of the invention
[0007] The present application provides a photovoltaic station intelligent inspection method based on physical models, which can solve the technical problems in the prior art that the operation and maintenance of photovoltaic stations lack the definition of equipment physical models, resulting in more pre-processing steps for the collected data of similar devices due to different specifications, poor versatility, and excessively high costs for collecting key data required for equipment monitoring.
[0008] In a first aspect, the present application provides a photovoltaic station intelligent inspection method based on a physical model, comprising the following steps:
[0009] Construct the physical model of the entire photovoltaic station and complete the physical model parameter configuration;
[0010] Real-time acquisition of operating parameters of key equipment in photovoltaic stations, including booster stations and transformer substations;
[0011] According to the operating parameters of key equipment, different fault equipment locking strategies for the entire station are executed, and the intelligent inspection results of the photovoltaic station are obtained by combining the constructed physical model of the entire station.
[0012] In combination with the first aspect, in one implementation, constructing a photovoltaic station full-station physical model and completing physical model parameter configuration specifically includes the following steps:
[0013] Select key equipment for photovoltaic stations;
[0014] Build corresponding physical models according to the equipment types of key equipment;
[0015] Model parameter configuration is performed for all physical models, wherein the model parameters include parameter type, parameter threshold and parameter acquisition strategy.
[0016] In conjunction with the first aspect, in one implementation, the real-time acquisition of operating parameters of key equipment in a photovoltaic station specifically includes the following steps:
[0017] Regularly collect and obtain the operating parameters of key equipment in photovoltaic stations; or,
[0018] The sensing parameters of key equipment are collected and acquired. When the sensing parameters exceed the parameter sensing threshold, the acquisition of the operating parameters of the key equipment of the photovoltaic station is triggered.
[0019] In combination with the first aspect, in one implementation, executing different fault equipment locking strategies for the entire station according to the operating parameters of the key equipment, and obtaining the intelligent inspection results of the photovoltaic station in combination with the constructed physical model of the entire station specifically includes the following steps:
[0020] When the operating parameters of key equipment exceed the parameter threshold, the equipment exceeding the parameter threshold and the area where the equipment is located are locked;
[0021] Conduct further parameter monitoring on the locked device and locked area and obtain parameter monitoring results;
[0022] According to the monitoring results of the locked parameters, the associated devices are obtained;
[0023] The faulty equipment for locking the entire station is the locking equipment and associated equipment.
[0024] In combination with the first aspect, in one implementation, further monitoring parameters of the locking device and the locking area to obtain parameter monitoring results specifically includes the following steps:
[0025] Continuously monitor the parameters of the locking device and obtain the parameter monitoring results of the locking device;
[0026] Conduct continuous parameter monitoring of other key equipment within the locked area and obtain parameter monitoring results within the locked area.
[0027] In combination with the first aspect, in one implementation, obtaining the associated device according to the locking parameter monitoring result specifically includes the following steps:
[0028] According to the parameter monitoring results of the locked device, the key devices with the same data pattern as the parameter monitoring results of the locked device are locked, and the key devices associated with the device are obtained;
[0029] According to the parameter monitoring results of the locked area, the key equipment associated with the parameter monitoring results of the locked area is locked, and the key equipment associated with the area is obtained;
[0030] Mark the key devices associated with the device and the key devices associated with the region.
[0031] In combination with the first aspect, in one implementation, after the step of marking the key devices associated with the device and the key devices associated with the region for the first time, the following steps are further included:
[0032] Construct fault warning algorithm based on the physical model of the whole station;
[0033] A fault alarm algorithm is used to analyze and integrate related equipment, infer the faulty equipment and faulty components, and perform a second marking on the associated equipment that has been marked once.
[0034] In combination with the first aspect, in one implementation, obtaining the intelligent inspection result of the photovoltaic station specifically includes the following steps:
[0035] Combine the marking information of the primary marking and the secondary marking to obtain the faulty equipment and faulty components of the entire photovoltaic station.
[0036] In a second aspect, the present application provides a photovoltaic station intelligent inspection system based on a physical model, comprising:
[0037] Physical model building module, used to build the physical model of the entire photovoltaic station and complete the physical model parameter configuration;
[0038] The equipment operation parameter acquisition module is used to acquire the operation parameters of the key equipment of the photovoltaic station in real time, and the key equipment includes the booster station and the transformer substation;
[0039] The inspection result acquisition module is communicated with the physical model construction module and the equipment operation parameter acquisition module, and is used to execute different fault equipment locking strategies for the entire station according to the operating parameters of key equipment, and obtain the intelligent inspection results of the photovoltaic station in combination with the constructed physical model of the entire station.
[0040] In conjunction with the second aspect, in one implementation, the object model building module includes:
[0041] Key equipment selection unit, used to select key equipment for photovoltaic stations;
[0042] A physical model building unit, which is in communication with the key equipment selection unit and is used to build corresponding physical models according to equipment types of key equipment;
[0043] The physical model parameter configuration unit is in communication with the physical model construction unit and is used to configure model parameters for all physical models. The model parameters include parameter type, parameter threshold and parameter acquisition strategy.
[0044] The beneficial effects brought by the technical solution provided by the embodiment of the present application include at least:
[0045] By constructing a physical model of the entire photovoltaic station, there is no need to pre-process the data collected by similar equipment due to different specifications. It is more versatile, and the operating parameters of the collected equipment are faster and more convenient, thus achieving efficient and intelligent inspection of photovoltaic stations and effectively ensuring the operational safety of photovoltaic stations. BRIEF DESCRIPTION OF THE DRAWINGS
[0046] Figure 1 A method flow chart of a photovoltaic station intelligent inspection method based on a physical model provided in an embodiment of the present application;
[0047] Figure 2 A functional module block diagram of a photovoltaic station intelligent inspection system based on a physical model provided in an embodiment of the present application. DETAILED DESCRIPTION
[0048] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0049] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.
[0050] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.
[0051] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.
[0052] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.
[0053] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.
[0054] First, please refer to Figure 1 The present application provides a photovoltaic station intelligent inspection method based on a physical model, comprising the following steps:
[0055] Step S1: construct a physical model of the entire photovoltaic station and complete the physical model parameter configuration;
[0056] Step S2: real-time acquisition of operating parameters of key equipment of the photovoltaic station, wherein the key equipment includes a booster station, photovoltaic modules, a transformer substation, an inverter, etc.;
[0057] Step S3: According to the operating parameters of key equipment, different fault equipment locking strategies for the entire station are executed, and the intelligent inspection results of the photovoltaic station are obtained in combination with the constructed physical model of the entire station.
[0058] This application constructs a physical model of the entire photovoltaic station, and there is no need to pre-process the data collected by similar equipment due to different specifications. It is more versatile, and the operating parameters of the collection equipment are realized more quickly and conveniently, thereby achieving efficient and intelligent inspections of photovoltaic stations and effectively ensuring the operational safety of photovoltaic stations.
[0059] In one embodiment, the step S1: constructing a physical model of the entire photovoltaic station and completing the physical model parameter configuration specifically includes the following steps:
[0060] Step S11: Select key equipment of the photovoltaic station;
[0061] Step S12: construct corresponding physical models according to the equipment types of key equipment;
[0062] Step S13: Pay attention to key information such as equipment specification parameterization, operating status parameters, measurement units, and critical values of parameters, and configure model parameters for all object models. The model parameters include parameter type, parameter threshold, and parameter acquisition strategy; more specifically, different parameter thresholds are set for different types of equipment; different parameter thresholds are set for the same type of equipment with different specifications;
[0063] Based on steps S11 to S13, object models are constructed for the same type of equipment, and different parameter thresholds are set for different types of equipment, and different parameter thresholds are set for equipment of the same type but with different specifications. There is no need to perform data preprocessing on the operating parameters after collecting the equipment operating parameters, so the fault alarm inspection function of the entire station can be quickly realized.
[0064] In one embodiment, the step S2: real-time acquisition of operating parameters of key equipment in a photovoltaic station specifically includes the following steps:
[0065] Regularly collect and obtain the operating parameters of key equipment in photovoltaic stations; or,
[0066] The sensing parameters of key equipment are collected and acquired. When the sensing parameters exceed the parameter sensing threshold, the acquisition of the operating parameters of key equipment of the photovoltaic station is triggered.
[0067] In one embodiment, the step S2: real-time acquisition of operating parameters of key equipment in the photovoltaic station is specifically implemented as follows:
[0068] Networks and intelligent equipment inspection data collection devices are deployed in photovoltaic stations. The intelligent equipment inspection data timing collection device collects the operating parameters of each key equipment, or triggers the automatic inspection function by receiving the data collected by the sensor to obtain the operating parameters of the key equipment, and forwards them to the physical model processing system through the network. At the same time, it detects the link without data transmission to ensure smooth data transmission.
[0069] In a more specific embodiment, the photovoltaic field station deployment network is implemented as follows:
[0070] A network connection is established between the intelligent equipment inspection data collection device and the physical model processing system, wherein the physical model processing system stores the entire photovoltaic station model and implements parameter configuration of all physical models; more specifically, the physical model processing system is a computer with data storage and data processing functions.
[0071] In one embodiment, step S3: executing different fault equipment locking strategies for the entire station according to the operating parameters of the key equipment, combining the constructed physical model of the entire station, and obtaining the intelligent inspection results of the photovoltaic station, specifically includes the following steps:
[0072] Step S31: When the operating parameters of the key equipment exceed the parameter threshold, the equipment exceeding the parameter threshold and the area where the equipment is located are locked;
[0073] Step S32: further monitoring parameters of the locked device and the locked area to obtain parameter monitoring results;
[0074] Step S33: acquiring associated devices according to the monitoring results of the locking parameters;
[0075] Step S34: Lock the faulty equipment in the entire station into locked equipment and associated equipment.
[0076] Based on steps S31 to S34, when faulty equipment and faulty areas are detected, fault deduction is performed to obtain more comprehensive and accurate fault monitoring results.
[0077] In one embodiment, the step S32: further monitoring the parameters of the locking device and the locking area to obtain the parameter monitoring results, specifically includes the following steps:
[0078] Step S321: continuously monitoring the parameters of the locking device and obtaining the parameter monitoring results of the locking device;
[0079] Step S322: Continuously monitor the parameters of other key equipment in the locked area to obtain parameter monitoring results in the locked area.
[0080] The duration of the above-mentioned continuous parameter monitoring is a preset time, specifically, the duration is 5 minutes. In the modified embodiment of the present application, it can be adjusted according to the operating cycle and operating stability of the equipment and the ambient temperature.
[0081] In one embodiment, the step S33: obtaining the associated device according to the locking parameter monitoring result, specifically includes the following steps:
[0082] According to the parameter monitoring results of the locked device, the key devices with the same data pattern as the parameter monitoring results of the locked device are locked, and the key devices associated with the device are obtained;
[0083] According to the parameter monitoring results of the locked area, the key equipment associated with the parameter monitoring results of the locked area is locked, and the key equipment associated with the area is obtained;
[0084] Mark the key devices associated with the device and the key devices associated with the region.
[0085] By further deducing the faults of the locked devices and locked areas according to the device type association and area association respectively, the key devices with device type association and area association are obtained to capture the key devices with a wider range of fault possibilities.
[0086] In one embodiment, after the step of marking the key devices associated with the device and the key devices associated with the region for the first time, the following steps are also included:
[0087] Construct fault warning algorithm based on the physical model of the whole station;
[0088] A fault alarm algorithm is used to analyze and integrate related equipment, infer the faulty equipment and faulty components, and perform a second marking on the associated equipment that has been marked once.
[0089] By marking the faulty equipment for the second time, we can obtain more comprehensive faulty equipment and detailed faulty components, and obtain more detailed and comprehensive fault inspection results.
[0090] In one embodiment, obtaining the intelligent inspection result of the photovoltaic station in step S3 specifically includes the following steps:
[0091] Combined with the marking information of the primary and secondary markings, the faulty equipment and faulty components of the entire photovoltaic station are obtained, and the inferred equipment fault location and historical fault document information of similar faults are pushed to the client user, and a fault alarm is initiated. Maintenance personnel can perform equipment maintenance according to the pushed fault information and determine the preparedness of the current fault, and optimize and adjust the model parameters of the object model accordingly, such as raising or lowering the parameter threshold.
[0092] Second, please refer to Figure 2 The present application provides a photovoltaic station intelligent inspection system based on a physical model, including a physical model construction module 100, an equipment operation parameter collection module 200 and an inspection result acquisition module 300. The physical model construction module 100 is used to construct a physical model of the entire photovoltaic station and complete the physical model parameter configuration; the equipment operation parameter collection module 200 is used to collect and obtain the operating parameters of key equipment of the photovoltaic station in real time, and the key equipment includes a booster station and a substation; the inspection result acquisition module 300 is communicated with the physical model construction module 100 and the equipment operation parameter collection module 200, and is used to execute different fault equipment locking strategies for the entire station according to the operating parameters of the key equipment, and obtain the intelligent inspection results of the photovoltaic station in combination with the constructed physical model of the entire station.
[0093] In one embodiment, the physical model building module includes:
[0094] Key equipment selection unit, used to select key equipment for photovoltaic stations;
[0095] A physical model building unit, which is in communication with the key equipment selection unit and is used to build corresponding physical models according to equipment types of key equipment;
[0096] The physical model parameter configuration unit is in communication with the physical model construction unit and is used to configure model parameters for all physical models. The model parameters include parameter type, parameter threshold and parameter acquisition strategy.
[0097] Among them, the functional implementation of each module in the above-mentioned photovoltaic station intelligent inspection system based on physical model corresponds to the various steps in the above-mentioned photovoltaic station intelligent inspection method embodiment based on physical model, and its functions and implementation process will not be repeated here one by one.
[0098] In a third aspect, an embodiment of the present application provides a photovoltaic station intelligent inspection device based on a physical model. The photovoltaic station intelligent inspection device based on a physical model can be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.
[0099] The communication interface includes input / output (I / O) interface, physical interface and logical interface, etc., which are used to realize the interconnection of devices inside the photovoltaic station intelligent inspection equipment based on the physical model, and the interface used to realize the interconnection between the photovoltaic station intelligent inspection equipment based on the physical model and other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display, a keyboard, etc.
[0100] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.
[0101] The processor may be a general-purpose processor, which may call the photovoltaic station intelligent inspection program based on the physical model stored in the memory, and execute the photovoltaic station intelligent inspection method based on the physical model provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the photovoltaic station intelligent inspection program based on the physical model is called may refer to the various embodiments of the photovoltaic station intelligent inspection method based on the physical model of the present application, which will not be repeated here.
[0102] In a fourth aspect, an embodiment of the present application also provides a readable storage medium.
[0103] The readable storage medium of the present application stores a photovoltaic station intelligent inspection program based on a physical model, wherein when the photovoltaic station intelligent inspection program based on a physical model is executed by a processor, the steps of the photovoltaic station intelligent inspection method based on a physical model as described above are implemented.
[0104] Among them, the method implemented when the photovoltaic station intelligent inspection program based on the physical model is executed can refer to the various embodiments of the photovoltaic station intelligent inspection method based on the physical model of the present application, and will not be repeated here.
[0105] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.
[0106] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.
[0107] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.
Claims
1. A photovoltaic station intelligent inspection method based on physical model, characterized in that: The following steps are involved: Construct the physical model of the entire photovoltaic station and complete the physical model parameter configuration; Real-time acquisition of operating parameters of key equipment in photovoltaic stations, including booster stations and transformer substations; According to the operating parameters of key equipment, different fault equipment locking strategies for the entire station are executed, and the intelligent inspection results of the photovoltaic station are obtained by combining the constructed physical model of the entire station.
2. The photovoltaic station intelligent inspection method based on physical model according to claim 1, characterized in that: The construction of the photovoltaic station full-station physical model and completion of physical model parameter configuration specifically includes the following steps: Select key equipment for photovoltaic stations; Build corresponding physical models according to the equipment types of key equipment; Model parameter configuration is performed for all physical models, wherein the model parameters include parameter type, parameter threshold and parameter acquisition strategy.
3. The photovoltaic station intelligent inspection method based on physical model according to claim 1, characterized in that: The real-time acquisition of operating parameters of key equipment in the photovoltaic station specifically includes the following steps: Regularly collect and obtain the operating parameters of key equipment in photovoltaic stations; or, The sensing parameters of key equipment are collected and acquired. When the sensing parameters exceed the parameter sensing threshold, the collection of operating parameters of key equipment of the photovoltaic station is triggered.
4. The photovoltaic station intelligent inspection method based on physical model according to claim 1, characterized in that: According to the operating parameters of key equipment, different fault equipment locking strategies for the entire station are executed, and the intelligent inspection results of the photovoltaic station are obtained in combination with the constructed physical model of the entire station, which specifically includes the following steps: When the operating parameters of key equipment exceed the parameter threshold, the equipment exceeding the parameter threshold and the area where the equipment is located are locked; Conduct further parameter monitoring on the locked device and locked area and obtain parameter monitoring results; According to the monitoring results of the locked parameters, the associated devices are obtained; The faulty equipment for locking the entire station is the locking equipment and associated equipment.
5. The photovoltaic station intelligent inspection method based on physical model according to claim 4, characterized in that: The further parameter monitoring of the locking device and the locking area to obtain the parameter monitoring results specifically includes the following steps: Continuously monitor the parameters of the locking device and obtain the parameter monitoring results of the locking device; Conduct continuous parameter monitoring of other key equipment within the locked area and obtain parameter monitoring results within the locked area.
6. The photovoltaic station intelligent inspection method based on physical model according to claim 1, characterized in that: The step of obtaining the associated device according to the locking parameter monitoring result specifically includes the following steps: According to the parameter monitoring results of the locked device, the key devices with the same data pattern as the parameter monitoring results of the locked device are locked, and the key devices associated with the device are obtained; According to the parameter monitoring results of the locked area, the key equipment associated with the parameter monitoring results of the locked area is locked, and the key equipment associated with the area is obtained; The key devices associated with the device and the key devices associated with the region are marked once, and the associated devices include the key devices associated with the device and the key devices associated with the region.
7. The photovoltaic station intelligent inspection method based on physical model according to claim 6, characterized in that: After the step of marking the key devices associated with the device and the key devices associated with the region for the first time, the following steps are also included: Construct fault warning algorithm based on the physical model of the whole station; A fault alarm algorithm is used to analyze and integrate related equipment, infer the faulty equipment and faulty components, and perform a second marking on the associated equipment that has been marked once.
8. The photovoltaic station intelligent inspection method based on physical model according to claim 1, characterized in that: The obtaining of the intelligent inspection results of the photovoltaic station specifically includes the following steps: Combine the marking information of the primary marking and the secondary marking to obtain the faulty equipment and faulty components of the entire photovoltaic station.
9. A photovoltaic station intelligent inspection system based on physical model, characterized in that: include: Physical model building module, used to build the physical model of the entire photovoltaic station and complete the physical model parameter configuration; The equipment operation parameter acquisition module is used to acquire the operation parameters of the key equipment of the photovoltaic station in real time, and the key equipment includes the booster station and the transformer substation; The inspection result acquisition module is communicated with the physical model construction module and the equipment operation parameter acquisition module, and is used to execute different fault equipment locking strategies for the entire station according to the operating parameters of key equipment, and obtain the intelligent inspection results of the photovoltaic station in combination with the constructed physical model of the entire station.
10. The photovoltaic station intelligent inspection system based on physical model according to claim 9, characterized in that: The physical model building module includes: Key equipment selection unit, used to select key equipment for photovoltaic stations; A physical model building unit, which is in communication with the key equipment selection unit and is used to build corresponding physical models according to equipment types of key equipment; The physical model parameter configuration unit is in communication connection with the physical model construction unit and is used to configure model parameters for all physical models. The model parameters include parameter type, parameter threshold and parameter acquisition strategy.