Wind power station intelligent optimization method and system based on cloud edge collaboration

Abstract

The invention provides a wind power plant station intelligent optimization method and system based on cloud edge collaboration, and the method comprises the steps: analyzing the current information of each subsystem in a to-be-optimized wind power plant station, and carrying out the reconstruction of each subsystem through combining the current information with a to-be-constructed function; constructing an edge all-in-one machine according to an optimization upgrading strategy of the wind power station, and integrating each intelligent subsystem to the edge all-in-one machine to realize data sharing of each subsystem; based on a cloud-side collaborative platform technology architecture, an edge all-in-one machine is adaptively connected with an intelligent station integrated management platform, the integrated management platform is in communication connection with a group industry data middle station, and intelligent management is performed on an intelligent wind power station through the industry data middle station. According to the method, a plurality of subsystems in a station are deeply integrated on the basis of a cloud-side collaborative platform technology architecture, an existing wind power station is transformed into an intelligent station through a digital intelligent means, and the safety level and the management level of the station are improved.

Description

Technical Field

[0001] The present application relates to the technical field of wind farm transformation, and in particular to a method and system for intelligent optimization of wind farms based on cloud-edge collaboration. Background Art

[0002] Against the backdrop of energy transformation and the accelerated integration of various emerging technologies, the application of smart and digital technologies in the new energy industry is becoming increasingly in-depth. In order to promote the high-quality development of wind power stations, it is necessary to focus on building smart stations and promote the intelligent transformation and digital transformation of existing wind power stations.

[0003] However, wind farms contain a large number of systems and equipment, and these systems and equipment are relatively scattered and messy, and cannot be connected and linked with each other, which restricts the digital development of wind farms. Due to the above limitations, the smart wind farms constructed in related technologies have a low degree of intelligence and digitization and cannot meet the actual needs of smart farms.

[0004] Therefore, how to integrate scattered system equipment to carry out in-depth intelligent and digital upgrades of wind farms has become an urgent problem that needs to be solved. Summary of the invention

[0005] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0006] To this end, the first purpose of this application is to propose an intelligent optimization method for wind farms based on cloud-edge collaboration. This method deeply integrates multiple subsystems within the farm based on the platform technology architecture of cloud-edge collaboration and a variety of key technologies. On this basis, the existing wind farms are optimized and transformed into smart farms through digital and intelligent means, which can realize the intelligent management of wind farms and significantly improve the inherent safety level and production management level of the farms.

[0007] The second object of this application is to propose a wind farm intelligent optimization system based on cloud-edge collaboration;

[0008] A third object of the present application is to provide a non-transitory computer-readable storage medium.

[0009] To achieve the above objectives, the first aspect of the present application is to propose a wind farm intelligent optimization method based on cloud-edge collaboration, the method comprising the following steps:

[0010] Analyze the status information of each existing subsystem in the wind farm to be optimized, and transform each subsystem in combination with the status information and the functions to be constructed of each subsystem, and deploy the transformed intelligent subsystems on the farm side;

[0011] According to the optimization and upgrading strategy of the wind farm, an edge integrated machine is constructed in the wind farm, and each intelligent subsystem is integrated into the edge integrated machine to realize data sharing of each intelligent subsystem;

[0012] Based on the platform technology architecture of cloud-edge collaboration, the edge all-in-one machine is adapted and connected with the integrated management platform of the smart station, and the integrated management platform of the smart station is communicatively connected with the industrial data middle platform of the group to which the station belongs, and the optimized wind farm is intelligently managed through the industrial data middle platform.

[0013] Optionally, in one embodiment of the present application, the transformed intelligent subsystems include: an intelligent access control system, an automatic fire protection system, a perimeter protection system, an intelligent lock control system, a video inspection system, an environmental monitoring system, an intelligent equipment inspection system and a fault monitoring system, and the edge integrated machine is constructed in the wind farm according to the optimization and upgrade strategy of the wind farm, including: detecting the servers and data transmission status already equipped in the wind farm, and determining whether to add an edge integrated machine according to the status of the equipped servers and the data transmission status; if an edge integrated machine needs to be added, the software and hardware configuration of the edge integrated machine is determined based on the requirements of the cloud-edge collaborative platform technology architecture for multi-faceted collaboration.

[0014] Optionally, in one embodiment of the present application, the intelligent management of the optimized wind farm station through the industrial data middle platform includes: uploading the real-time data detected by the various intelligent subsystems to the smart station integrated management platform, and the smart station integrated management platform uploads the real-time data to the industrial data middle platform for display; generating business data for controlling the intelligent subsystems to perform corresponding functions through the industrial data middle platform and sending the business data to the smart station integrated management platform, and generating control instructions according to the business data through the smart station integrated management platform and sending the control instructions to the edge integrated machine.

[0015] Optionally, in one embodiment of the present application, the business data generated by the industrial data middle platform to control the intelligent subsystem to perform corresponding functions includes: integrating and analyzing the real-time data detected by each intelligent subsystem through the industrial data middle platform, and determining the operating decisions for each intelligent subsystem in combination with the stored historical experience data; and generating the business data for the corresponding intelligent subsystem based on the operating decisions.

[0016] Optionally, in one embodiment of the present application, after the various intelligent subsystems are integrated into the edge all-in-one machine, it also includes: performing visual modeling on the intelligent management of the wind farm station in the edge all-in-one machine, and constructing an analysis model for the detection data of the various intelligent subsystems based on the modeling results; and using the detection data analysis results output by the analysis model as the data basis for the artificial intelligence service of the industrial data middle platform.

[0017] Optionally, in one embodiment of the present application, the intelligent management function in the industrial data center includes site security, and the transformed intelligent subsystems are deployed on the site side, including: arranging the automatic fire extinguishing system, the intelligent access control system and the perimeter protection system in the booster station area of ​​the wind farm; arranging the intelligent lock control system and the automatic fire extinguishing system in the wind turbine area of ​​the wind farm.

[0018] Optionally, in one embodiment of the present application, the intelligent management function in the industrial data center includes daily inspections, and the deployment of the transformed intelligent subsystems on the station side also includes: arranging the video inspection system, the environmental monitoring system and the digital meter in the booster station area of ​​the wind farm; arranging the intelligent equipment inspection system in the collection line area of ​​the wind farm; arranging the video inspection system, the intelligent equipment inspection system and the fault monitoring system in the wind turbine area of ​​the wind farm.

[0019] Optionally, in one embodiment of the present application, the intelligent management function in the industrial data middle platform includes operation monitoring, and the intelligent management of the optimized wind farm station through the industrial data middle platform also includes: performing multi-dimensional early warning according to the real-time data detected by each intelligent subsystem to generate early warning information; and arranging operation and maintenance work of the wind farm station based on the monitoring results of the real-time data and the early warning information.

[0020] To achieve the above objectives, the second aspect of the present application further proposes a wind farm intelligent optimization system based on cloud-edge collaboration, comprising the following modules:

[0021] A transformation module is used to analyze the status information of each existing subsystem in the wind farm to be optimized, and transform each subsystem in combination with the status information and the functions to be constructed of each subsystem, and deploy the transformed intelligent subsystems on the farm side;

[0022] An integration module, used to construct an edge integrated machine in the wind farm station according to the optimization and upgrade strategy of the wind farm station, and integrate the various intelligent subsystems into the edge integrated machine to realize data sharing of the various intelligent subsystems;

[0023] The management module is used to adapt and connect the edge all-in-one machine with the integrated management platform of the smart station based on the platform technology architecture of cloud-edge collaboration, and to communicate and connect the integrated management platform of the smart station with the industrial data middle platform of the group to which the station belongs, so as to intelligently manage the optimized wind farm through the industrial data middle platform.

[0024] In order to implement the above-mentioned embodiments, the third aspect embodiment of the present application also proposes a non-temporary computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, the wind farm intelligent optimization method based on cloud-edge collaboration in the above-mentioned first aspect embodiment is implemented.

[0025] The technical solution provided by the embodiment of the present application brings at least the following beneficial effects: the present application first determines the deployment mode of each intelligent application subsystem in the station according to the actual situation of the wind farm to be transformed; then constructs the edge all-in-one machine of the smart station to realize the deep integration of all intelligent application subsystems and the interconnection of system data; then the edge all-in-one machine is model-adapted with the integrated management platform of the smart station to realize the display of real-time data of the smart station on the industrial data platform, transforms and innovates the station model, and also realizes the multi-level integration from bottom perception to top decision-making based on the platform technology architecture of cloud-edge collaboration. Through the fusion analysis of a large amount of data in the industrial data platform, a high degree of integration and sharing of resources and experience is achieved, and through data fusion innovation, the coordination ability of new energy business is improved. Therefore, the present application constructs a smart wind power station, and realizes intelligent management of security, inspection and monitoring of wind farms through intelligent means, so as to ensure the safety of equipment, improve the utilization efficiency of wind energy, reduce the operation and maintenance costs and improve the operation and maintenance efficiency, reduce the pressure of staff, and significantly improve the inherent safety level and production management level of the station.

[0026] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0028] Figure 1 A flow chart of a wind farm intelligent optimization method based on cloud-edge collaboration proposed in an embodiment of the present application;

[0029] Figure 2 A flow chart of an intelligent management method for a wind farm proposed in an embodiment of the present application;

[0030] Figure 3A schematic diagram of the structure of a wind farm intelligent optimization system based on cloud-edge collaboration proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0031] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0032] A wind farm intelligent optimization method and system based on cloud-edge collaboration proposed in an embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0033] Figure 1 A flow chart of a wind farm intelligent optimization method based on cloud-edge collaboration proposed in an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0034] Step S101, analyzing the status information of each existing subsystem in the wind farm to be optimized, and transforming each subsystem respectively based on the status information and the functions to be constructed of each subsystem, and deploying the transformed intelligent subsystems at the farm side.

[0035] It should be noted that this application aims to build a smart station for wind farms, and to achieve intelligent management of security, inspection, monitoring and other aspects of wind farms through intelligent means, so as to ensure equipment safety, improve wind energy utilization efficiency, reduce operation and maintenance costs, and ultimately achieve a comprehensive improvement in the economic benefits and management level of wind farms. Among them, on the one hand, it is necessary to use digital systems to realize unmanned station inspections, remote operation of station equipment, optimization of station maintenance plan arrangements, systematization of station maintenance work, and regional coordinated maintenance and inspection. On the other hand, it is necessary to deeply integrate all subsystems of the station to realize the connection of business scenarios. Unified integration of system applications such as automatic fire protection, intelligent access control, perimeter protection and daily inspections to achieve data interconnection and interoperability of all subsystems.

[0036] To this end, this application first transforms the existing wind farms to be optimized to meet the hardware foundation for achieving the above goals. In the transformation process, specific transformation strategies are formulated for different wind farms to implement precise wind farm smart station transformation, thereby avoiding unnecessary waste of resources and ensuring a balance between input and output.

[0037] Specifically, for the wind farm transformation project to be optimized, the typical design of the transformation of the existing wind farm smart station can be referred to to analyze the status information of each existing subsystem in the wind farm. The status information includes information such as the equipment installed in the current subsystem and the functions that can be realized. Then, combining the obtained status information with the expected target functions of each subsystem for the construction of the wind farm smart station, each subsystem is transformed separately, including adding new equipment or upgrading existing equipment.

[0038] Furthermore, based on the actual situation of the wind farm, the specific construction content is studied, and according to the construction function of each subsystem, the on-site deployment method is studied, and the transformed intelligent subsystems are deployed at the corresponding positions in the wind farm.

[0039] In one embodiment of the present application, the various intelligent subsystems after transformation include: intelligent access control system, automatic fire protection system, perimeter protection system, intelligent lock control system, video inspection system, environmental monitoring system, intelligent equipment inspection system and fault monitoring system. Among them, the intelligent equipment inspection system includes drone inspection and inspection robot, etc. The fault monitoring system includes line fault monitoring and wind turbine online status monitoring, etc.

[0040] In this embodiment, existing front-end intelligent fire-fighting devices, cameras, intelligent access control, rail robots and other equipment are utilized, and artificial intelligence Internet of Things, big data and other technologies are applied to build the above-mentioned subsystems, gradually realize the unmanned management mode of the station, and improve the inherent safety of the station and the production management level of the enterprise.

[0041] In order to more clearly illustrate the specific implementation process of transforming each subsystem in combination with the current status information and the functions to be constructed of each subsystem, the above-mentioned subsystems are used as examples for explanation below.

[0042] As the first example, for the automatic fire fighting system, the current status information analyzed includes: the wind farm booster station has a fire fighting system, but it is currently limited to fire alarm, and the on-site portable or cart-type dry powder fire extinguishers are equipped without automatic fire fighting function; the wind turbine cabin has an automatic fire fighting system; the main transformer is not equipped with an automatic fire fighting system. The functions to be built include: the central control room, as the control center of the station-level fire fighting, can timely know the dynamics of each defense zone in the station. When the fire fighting in any defense zone is activated, the sound and light alarm in the main control room will be activated to remind the on-site duty personnel to pay attention to the fire. The gas extinguishing host of all defense zones will aggregate the signal to the detection alarm host in the central control room, and the information will be uploaded to the smart platform in real time through the detection alarm host.

[0043] Therefore, the transformation measures for the automatic fire-fighting subsystem include: installing a fire linkage module in the control room, equipping the main control room, battery room, and hazardous waste temporary storage room with heptafluoropropane automatic fire extinguishing devices, equipping each cabinet in the primary room, relay room, AC / DC room, SVG room, and pump room with aerosol automatic fire extinguishing devices, which have the function of automatically sensing the fire source and triggering fire extinguishing, and are used to replace portable dry powder fire extinguishers; equipping the main transformer with an automatic fire extinguishing system.

[0044] As a second example, for the access control system, the current status information analyzed includes: the access control system in the wind farm station uses induction card access control, with a total of 14 points, and currently only 3 cards are available, and the card making function has failed; the current gate of the booster station uses a remote control key switch, people and vehicles are separated, people enter and exit passwords, and there is no background record. The functions to be built include: the intelligent access control system mainly provides access control authority management, event management, access control status viewing, access control remote control, real-time display of personnel entry and exit records, and remote call intercom applications; it can be linked with the two-ticket management, and after the personnel have regular inspections, maintenance, pre-tests and other tasks, the access control authority is authorized to the work shift members according to the two-ticket work location.

[0045] Therefore, the renovation measures for the access control system include: First, the original visual induction card access control network structure is reused, and 10 sets of face recognition access control are added at the booster station gate, the entrance of the comprehensive building, the relay protection room door, the battery room door, the AC / DC integrated room door, the switch room 2 doors, the GIS room 1 door, the SVG room 1 door, and the pump room door. The original access control host is reused to realize card making management, staff management, visitor management, vehicle access management, channel management, anti-passback and anti-re-swipe, time period conversion, local and remote alarm, information recording and reporting, query, fire alarm linkage and graphic display, biometric information verification and other functions. The access control host transmits the access control data to the edge integrated machine and sends it to the operation center via the operator's dedicated line. Second, the original booster station gate is reused, the gate controller is modified, and the vehicle identification equipment is added to link the gate, so that it has the remote opening and closing function, and the gate opening and closing status is sent to the access control host, which has the same management function as the access control system. Third, the access control system requires UPS power supply, which is shared with the booster station UPS system, and the continuous working time is greater than 2 hours. Fourth, the access control system should have lightning protection measures, making full use of the existing lightning protection facilities in the booster station / switch station. Cables drawn from the outdoors should be equipped with surge protectors. The equipment grounding should be connected to the main grounding grid of the booster station / switch station or the building grounding grid nearby, and the wire-threading steel pipe should be reliably grounded.

[0046] It should be noted that the modification method for each intelligent subsystem can be determined according to the actual situation, and this application does not impose any restrictions on this. The modification of the remaining intelligent subsystems mentioned above will not be repeated.

[0047] Furthermore, in this embodiment, when the transformed intelligent subsystems are deployed on the station side, the deployment location can be determined based on the need for intelligent management of the optimized wind farm by the industrial data center and the actual situation of the wind farm.

[0048] For example, in this embodiment, in order to achieve station security, the various intelligent subsystems after transformation are deployed on the station side, including: arranging an automatic fire protection system, an intelligent access control system and a perimeter protection system in the booster station area of ​​the wind farm station; arranging an intelligent lock control system and an automatic fire protection system in the wind turbine area of ​​the wind farm station. In order to achieve daily inspections, the various intelligent subsystems after transformation are deployed on the station side, including: arranging a video inspection system, an environmental monitoring system and a digital meter in the booster station area of ​​the wind farm station; arranging an intelligent equipment inspection system in the collector line area of ​​the wind farm station; arranging a video inspection system, an intelligent equipment inspection system and a fault monitoring system in the wind turbine area of ​​the wind farm station.

[0049] Step S102: construct an edge integrated machine in the wind farm according to the optimization and upgrade strategy of the wind farm, and integrate various intelligent subsystems into the edge integrated machine to realize data sharing of various intelligent subsystems.

[0050] Specifically, the optimization and upgrade strategies for wind farms include strategies for unified integration of various subsystems, strategies for connecting edge all-in-one machines with integrated management platforms based on cloud-edge collaboration, and strategies for implementing specific precision transformations as mentioned above. This application develops an integrated edge platform for smart farms to integrate all subsystem applications of the above-mentioned farms. First, the edge all-in-one machine for smart farms is configured according to the above-mentioned strategies, which supports the integration and data aggregation of all smart tool sub-application systems at the farm end, so as to facilitate the formation of a collaborative operation mechanism for the subsequent integrated management and control platform of smart farms.

[0051] Among them, the edge all-in-one machine is a device that integrates computing, storage and network functions. It processes data close to the data source of the wind farm subsystem to reduce latency, improve response speed, and reduce the burden on the data center. This application considers the above strategy when configuring the edge all-in-one machine, which not only meets the needs of coordinated operation with the integrated management platform, but also avoids resource waste.

[0052] In one embodiment of the present application, an edge machine is constructed in a wind farm according to the optimization and upgrade strategy of the wind farm, including: detecting the servers and data transmission status already equipped in the wind farm, and determining whether to add an edge machine according to the status of the equipped servers and the data transmission status; when it is necessary to add an edge machine, determining the software and hardware configuration of the edge machine based on the requirements of the cloud-edge collaborative platform technology architecture for multi-faceted collaboration.

[0053] For example, in this embodiment, the status of the servers already equipped in the wind farm and the data transmission status are first detected to make judgments, including: determining that the wind farm has been equipped with two acquisition servers and one server in different areas to integrate data from different areas of the farm and upload it to the centralized control center, but the existing server does not have the function of one acquisition and two transmissions. The newly added system data of the smart farm construction needs to be integrated on-site. According to typical design requirements, it is determined that the wind farm must be equipped with a new smart farm edge all-in-one machine.

[0054] Furthermore, the platform technology architecture of cloud-edge collaboration requires multi-faceted collaboration, including the following: First, data collaboration: In scenarios such as the Internet of Things, edge computing nodes are responsible for collecting field / terminal data, and preliminarily process and analyze the data according to rules or data models, and then upload the processing results and related data to the cloud. Second, resource collaboration: Edge nodes provide infrastructure resources such as computing, storage, networking, and virtualization, while the cloud provides resource scheduling management strategies, including device management, resource management, and network connection management of edge nodes, so that edge nodes can better support a wide range of terminal access. Third, intelligent collaboration: Edge nodes provide data input for AI model training, are responsible for edge AI reasoning execution, execute AI models sent from the cloud, and feed back execution results to the cloud. Fourth, application management collaboration: Edge nodes provide edge application deployment and operating environment and lifecycle management APIs, while the cloud implements full lifecycle management of edge applications.

[0055] Based on the above-mentioned coordination requirements and the current requirements for building intelligent wind farms, determine the software and hardware configurations required for the edge all-in-one machine to meet the above requirements.

[0056] For example, the optimization of wind farms requires the functions of the integrated edge machines of smart farms, including the use of a "software and hardware integration" fusion architecture, which can provide computing resources and communication services uniformly according to the needs of different regions, and access the superior center through a unified interface specification. Therefore, in order to meet the above requirements, the transformation measures are determined, and the corresponding software and hardware are equipped to achieve multi-system integration within the station, with functions such as data collection, data governance, data forwarding, and basic applications, and provide remote stations, maintenance assistance, emergency hot standby and other services. The newly added equipment includes a corresponding number of edge integrated machine servers, smart farm industrial computers, isolation gateways, multi-port expansion switches, firewalls, and high-end KVMs.

[0057] Furthermore, after building the edge all-in-one machine, each intelligent subsystem in the previous step is integrated into the edge all-in-one machine through the corresponding Internet of Things protocol, and data sharing can be achieved between each intelligent subsystem.

[0058] Therefore, in this application, the smart station edge all-in-one machine is deployed to the station side, integrating the station-side intelligent equipment and connecting to the smart station application. The smart station edge all-in-one machine provides the basic support capabilities for the upper-level group to build a unified system platform from multiple aspects such as data integration, business integration, artificial intelligence, and data sharing. It supports the unified management and maintenance of centralized organizations and station personnel, and provides a management foundation for the integrated application of various intelligent tools. It provides data integration services such as the collection and storage of various types of data, providing a data foundation for the construction of various intelligent application functions.

[0059] As an example, in this embodiment, after integrating various intelligent subsystems into the edge all-in-one machine, it also includes: visual modeling of the intelligent management of wind farms in the edge all-in-one machine, and building an analysis model for the detection data of each intelligent subsystem based on the modeling results; using the detection data analysis results output by the analysis model as the data basis for the artificial intelligence service of the industrial data middle platform.

[0060] Specifically, in this embodiment, visual modeling is a method of thinking about problems by organizing models around realistic ideas. The constructed model helps to understand the problems that occur in wind farms, processes related to wind farms, design procedures, and databases. Based on the results of visual modeling, a variety of video / image intelligent recognition and analysis models can be preset, and the detection data of various subsystems output by the analysis model are analyzed and processed, including identification data, classification of data, and other processing. The results of the analysis model output are then used as the data basis for the artificial intelligence service of the industrial data center. Therefore, the artificial intelligence service can use the actual detection data as data support to perform fault diagnosis and operation control decisions of related subsystems.

[0061] Therefore, this application integrates various subsystems through an edge all-in-one machine, which can integrate the scattered subsystems in the station and promote the "digital foundation" of the production and operation management of new energy stations to achieve relative centralization and unification, and open sharing with each other.

[0062] Step S103, based on the cloud-edge collaborative platform technology architecture, the edge all-in-one machine is adapted and connected with the smart station integrated management platform, and the smart station integrated management platform is communicated with the industrial data middle platform of the group to which the station belongs, and the optimized wind farm is intelligently managed through the industrial data middle platform.

[0063] Specifically, this application is based on the platform technology architecture of cloud-edge collaboration, and adapts the model of the smart station edge all-in-one machine with the industrial data middle-end smart station integrated management platform, which not only optimizes the operation mode of the wind farm, but also realizes multi-level integration from bottom-level perception to top-level decision-making, and realizes data fusion innovation. The edge platform capability module system of the edge all-in-one machine of this application and the smart station integrated management and control platform form a mechanism for collaborative operation, mainly including IoT perception access, data storage and services, artificial intelligence services, microservice component expansion, and convenient application integration and open capabilities.

[0064] Among them, the smart station integrated management platform of this application is the application of the industrial data platform of the group to which the station belongs. The integrated management platform can be connected with the industrial data platform software to realize the communication and interaction between the integrated management platform and the industrial data platform. Furthermore, it can facilitate the industrial data platform to process data, generate control instructions through the industrial data platform, and perform intelligent management of the optimized wind farm.

[0065] As a possible implementation method, when the edge machine and the integrated management platform of the smart station perform cloud-edge collaboration, the following aspects are involved: First, cloud model training and edge deployment: the integrated management platform is responsible for model training and optimization, while the edge machine is responsible for real-time reasoning and execution of the model. Second, containerization and cloud native support: the edge machine supports containerized deployment, so that the applications and models of the integrated management platform can be quickly deployed to the edge machine in the form of containers. Third, data collaboration: the edge machine is responsible for the initial processing of data, while the integrated management platform is responsible for the in-depth analysis and value mining of data. The edge machine can desensitize and preprocess the data, and then upload the processing results to the cloud. Fourth, model adaptation and optimization: the edge machine needs to adapt and optimize the model issued by the integrated management platform to adapt to the hardware and software environment of the edge end. This process involves compression and quantization of the model. Fifth, hardware adaptation and performance optimization. The edge machine needs to optimize specific hardware to adapt to the integrated management platform to achieve model reasoning acceleration.

[0066] Furthermore, the optimized wind farms are managed intelligently by the industrial data middle platform (including the integrated management platform). Among them, the customized functions in the industrial data middle platform of this application include site security, daily inspections and operation monitoring to adapt to the transformation of wind farms. Among them, the site security function includes the control of the above-mentioned automatic fire protection system, intelligent access control system, perimeter protection system and intelligent lock control system, the daily inspection function includes the control of the above-mentioned video inspection system, environmental monitoring system, inspection robot system, fault monitoring system and drone inspection system, and the operation monitoring includes a multi-dimensional early warning function.

[0067] In order to more clearly illustrate the specific process of intelligent management of wind farms in the present application, a management method proposed in an embodiment of the present application is exemplified below.

[0068] Figure 2 A flow chart of an intelligent management method for a wind farm station proposed in an embodiment of the present application, such as Figure 2 As shown, the method comprises the following steps:

[0069] Step S201, upload the real-time data detected by each intelligent subsystem to the smart station integrated management platform, and the smart station integrated management platform uploads the real-time data to the industrial data center for display.

[0070] Specifically, each intelligent subsystem first uploads its own real-time data, including inspection results and perception data, to the edge all-in-one machine. The edge all-in-one machine uploads the IoT data to the integrated management platform, which then uploads the data to the industrial data middle platform for display, thereby realizing the display of real-time data of smart stations on the industrial data middle platform.

[0071] Step S202: Generate business data for controlling the intelligent subsystem to execute corresponding functions through the industrial data middle platform and send the business data to the smart site integrated management platform; generate control instructions based on the business data through the smart site integrated management platform and send the control instructions to the edge integrated machine.

[0072] Specifically, the industrial data center determines the control decision for the corresponding subsystem based on the real-time detection data, and generates the business data of the corresponding subsystem based on the control decision. For example, the business data includes the startup signal of a subsystem, the operating time and other operating parameters. Then, the industrial data center sends the business data to the smart station integrated management platform, which generates control instructions based on the business data and sends the control instructions to the edge all-in-one machine through the smart station integrated management platform. The edge all-in-one machine then issues a strategy to send the control instructions to the corresponding subsystem to execute the instructions. For example, control the equipment in the booster station to implement three autonomous inspections throughout the day, with a coverage rate of more than 95% of the inspection points; control the smart security AI to identify violations, etc.

[0073] In this embodiment, business data for controlling the intelligent subsystems to perform corresponding functions is generated through the industrial data middle platform, including: integrating and analyzing the real-time data detected by each intelligent subsystem through the industrial data middle platform, and determining the operating decisions for each intelligent subsystem in combination with the stored historical experience data; and generating business data for the corresponding intelligent subsystem based on the operating decisions.

[0074] Specifically, this embodiment realizes a high degree of integration and sharing of resources and experience through the fusion analysis of a large amount of data in the industrial data center, and improves the coordination ability of new energy business. The detection data of each subsystem is uniformly analyzed in the industrial data center, and the operation strategy for each subsystem in the current state is determined in combination with the historical operation experience of the station, and then the business data of certain corresponding subsystems is determined according to the operation strategy. For example, the detection data of each related subsystem can be combined to determine whether a certain equipment in a wind farm station has failed, thereby improving the accuracy of fault detection. For another example, according to the numerical size of the detection data of each related subsystem, and referring to the impact of the results of the operation of the station with different parameters in the past, the corresponding operating parameters of each subsystem are determined.

[0075] Step S203, perform multi-dimensional warning according to the real-time data detected by each intelligent subsystem, generate warning information, and arrange the operation and maintenance of the wind farm station based on the monitoring results of the real-time data and the warning information.

[0076] Specifically, the multi-dimensional warnings performed in this embodiment include warnings in various aspects such as large component warnings, sensor warnings, and capacity reduction warnings. The operation monitoring function of the industrial data center can make judgments based on real-time monitoring data to determine whether to execute the corresponding warning. Through the online monitoring and early warning functions of the industrial data center, through the online monitoring, equipment early warning, fault diagnosis, output prediction, and in-depth mining of industrial big data in the production operation center, professional support is provided for the operation and maintenance of the station. For example, the cause of the fault and maintenance measures are determined based on the fault diagnosis results to guide the maintenance operations of the operation and maintenance personnel. For example, according to the overall equipment degradation status of each component in the station, operation and maintenance arrangements for different subsystems are formulated.

[0077] Therefore, this application uses a digital system built on a platform technology architecture based on cloud-edge collaboration to collaboratively control the corresponding subsystems, thereby realizing unmanned station inspections, remote operation of station equipment, optimization of station maintenance plan arrangements, systematization of station maintenance work, and regional coordinated maintenance and inspection.

[0078] In summary, the intelligent optimization method for wind farms based on cloud-edge collaboration in the embodiment of the present application first determines the deployment mode of each intelligent application subsystem in the wind farm to be transformed according to the actual situation of the wind farm to be transformed; then builds the edge all-in-one machine of the smart farm to achieve deep integration of all intelligent application subsystems and interconnection of system data; then the edge all-in-one machine is model-adapted with the integrated management platform of the smart farm to realize the display of real-time data of the smart farm on the industrial data platform, transforming and innovating the farm model, and also based on the platform technology architecture of cloud-edge collaboration, realizing multi-level integration from bottom-level perception to top-level decision-making. Through the fusion analysis of a large amount of data in the industrial data platform, a high degree of integration and sharing of resources and experience is achieved, and through data fusion innovation, the coordination ability of new energy business is improved. Therefore, the method constructs a smart wind power station, and realizes intelligent management of security, inspection and monitoring of wind farms through intelligent means, so as to ensure equipment safety, improve wind energy utilization efficiency, reduce operation and maintenance costs and improve operation and maintenance efficiency, reduce the pressure of staff, and significantly improve the inherent safety level and production management level of the farm.

[0079] In order to implement the above embodiments, the present application also proposes a wind farm intelligent optimization system based on cloud-edge collaboration. Figure 3 A schematic diagram of the structure of a wind farm intelligent optimization system based on cloud-edge collaboration proposed in an embodiment of the present application is shown in FIG. Figure 3 As shown, the system includes a transformation module 100 , an integration module 200 and a management module 300 .

[0080] Among them, the transformation module 100 is used to analyze the status information of each existing subsystem in the wind farm to be optimized, and transform each subsystem separately based on the status information and the functions to be constructed of each subsystem, and deploy the transformed intelligent subsystems on the farm side.

[0081] The integration module 200 is used to build an edge integrated machine in the wind farm station according to the optimization and upgrade strategy of the wind farm station, and integrate various intelligent subsystems into the edge integrated machine to realize data sharing of various intelligent subsystems.

[0082] The management module 300 is used for adapting and connecting the edge all-in-one machine with the integrated management platform of the smart station based on the platform technology architecture of cloud-edge collaboration, and for communicating and connecting the integrated management platform of the smart station with the industrial data middle platform of the group to which the station belongs, so as to perform intelligent management of the optimized wind farm through the industrial data middle platform.

[0083] It should be noted that the above explanation of the embodiment of the wind farm intelligent optimization method based on cloud-edge collaboration is also applicable to the system of this embodiment. The specific implementation process and beneficial effects of the system are the same as the corresponding contents recorded in the above method embodiment, and will not be repeated here.

[0084] To sum up, the wind farm intelligent optimization system based on cloud-edge collaboration in the embodiment of the present application builds a smart wind power generation station, and realizes intelligent management of various aspects of the wind farm such as security, inspection and monitoring through intelligent means, thereby ensuring equipment safety, improving wind energy utilization efficiency, reducing operation and maintenance costs and improving operation and maintenance efficiency, reducing the pressure on staff, and significantly improving the inherent safety level and production management level of the station.

[0085] In order to implement the above embodiments, the present application also proposes a non-temporary computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the wind farm intelligent optimization method based on cloud-edge collaboration as described in any of the above embodiments.

[0086] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0087] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0088] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0089] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0090] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0091] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0092] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0093] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A wind farm intelligent optimization method based on cloud-edge collaboration, characterized in that: The following steps are involved: Analyze the status information of each existing subsystem in the wind farm to be optimized, and transform each subsystem in combination with the status information and the functions to be constructed of each subsystem, and deploy the transformed intelligent subsystems on the farm side; According to the optimization and upgrading strategy of the wind farm, an edge integrated machine is constructed in the wind farm, and each intelligent subsystem is integrated into the edge integrated machine to realize data sharing of each intelligent subsystem; Based on the platform technology architecture of cloud-edge collaboration, the edge all-in-one machine is adapted and connected with the integrated management platform of the smart station, and the integrated management platform of the smart station is communicatively connected with the industrial data middle platform of the group to which the station belongs, and the optimized wind farm is intelligently managed through the industrial data middle platform.

2. The method according to claim 1, characterized in that The transformed intelligent subsystems include: intelligent access control system, automatic fire protection system, perimeter protection system, intelligent lock control system, video inspection system, environmental monitoring system, intelligent equipment inspection system and fault monitoring system. The edge integrated machine is constructed in the wind farm according to the optimization and upgrade strategy of the wind farm, including: Detecting the servers and data transmission status of the wind farm station, and determining whether to add an edge integrated machine according to the status of the servers and the data transmission status; When it is necessary to add an edge integrated machine, the software and hardware configuration of the edge integrated machine is determined based on the requirements of the cloud-edge collaborative platform technology architecture for multi-faceted collaboration.

3. The method according to claim 1, characterized in that The intelligent management of the optimized wind farm station through the industrial data center includes: Upload the real-time data detected by each intelligent subsystem to the smart station integrated management platform, and the smart station integrated management platform uploads the real-time data to the industrial data center for display; The industrial data middle platform generates business data for controlling the intelligent subsystem to execute corresponding functions and sends the business data to the smart site integrated management platform. The smart site integrated management platform generates control instructions based on the business data and sends the control instructions to the edge integrated machine.

4. The method according to claim 3, characterized in that The business data generated by the industrial data middle platform to control the intelligent subsystem to perform corresponding functions includes: The real-time data detected by each intelligent subsystem is integrated and analyzed by the industrial data center, and the operation decision of each intelligent subsystem is determined in combination with the stored historical experience data; The business data for the corresponding intelligent subsystem is generated according to the operation decision.

5. The method according to claim 1, characterized in that After the intelligent subsystems are integrated into the edge integrated machine, the method further includes: Performing visual modeling on the intelligent management of the wind farm in the edge integrated machine, and constructing an analysis model for the detection data of each intelligent subsystem based on the modeling result; The detection data analysis results output by the analysis model are used as the data basis for the artificial intelligence service of the industrial data center.

6. The method according to claim 2, characterized in that The intelligent management functions of the industrial data center include site security, and the various intelligent subsystems after transformation are deployed on the site side, including: Arrange the automatic fire fighting system, the intelligent access control system and the perimeter protection system in the booster station area of ​​the wind farm station; The intelligent lock control system and the automatic fire fighting system are arranged in the wind turbine group area of ​​the wind farm station.

7. The method according to claim 2, characterized in that The intelligent management function of the industrial data center includes daily inspections, and the deployment of the transformed intelligent subsystems on the station side also includes: Arrange the video inspection system, the environmental monitoring system and the digital meter in the booster station area of ​​the wind farm station; Arrange the intelligent equipment inspection system in the collector line area of ​​the wind farm station; The video inspection system, the intelligent equipment inspection system and the fault monitoring system are arranged in the wind turbine group area of ​​the wind farm station.

8. The method according to claim 3, characterized in that The intelligent management function in the industrial data center includes operation monitoring, and the intelligent management of the optimized wind farm station through the industrial data center also includes: Perform multi-dimensional warnings based on the real-time data detected by each intelligent subsystem and generate warning information; Based on the monitoring results of the real-time data and the early warning information, the operation and maintenance work of the wind farm is arranged.

9. A wind farm intelligent optimization system based on cloud-edge collaboration, characterized in that: Includes the following modules: A transformation module is used to analyze the status information of each existing subsystem in the wind farm to be optimized, and transform each subsystem in combination with the status information and the functions to be constructed of each subsystem, and deploy the transformed intelligent subsystems on the farm side; An integration module, used to construct an edge integrated machine in the wind farm station according to the optimization and upgrade strategy of the wind farm station, and integrate the various intelligent subsystems into the edge integrated machine to realize data sharing of the various intelligent subsystems; The management module is used to adapt and connect the edge all-in-one machine with the integrated management platform of the smart station based on the platform technology architecture of cloud-edge collaboration, and to communicate and connect the integrated management platform of the smart station with the industrial data middle platform of the group to which the station belongs, so as to intelligently manage the optimized wind farm through the industrial data middle platform.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements a wind farm intelligent optimization method based on cloud-edge collaboration as described in any one of claims 1-8.

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