Data processing system, device and method based on distributed power system

Abstract

A data processing system, device and method based on a distributed power system, wherein the system includes: an upper computer and multiple lower computers for running different simulation programs. The upper computer is used to: obtain a discrete model of the distributed power system, and obtain multiple simulation programs of the distributed power system based on the discrete model, obtain a list of target variables or parameters in the simulation program, generate a cross-index file containing the list and synchronize it between the upper computer and multiple lower computers; determine a target lower computer for running the target simulation program among multiple lower computers according to the cross-index file, and instruct it to load and run the target simulation program to simulate the operation of the distributed power system; configure a corresponding oscilloscope for the target simulation program; and obtain and use the oscilloscope to display the simulation operation data of the distributed power system in real time. The present application can improve the controllability and safety of debugging of power equipment in a distributed power system, and reduce the debugging cost.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data processing technology, and in particular, to a data processing system, device and method based on a distributed power system. Background Art

[0002] A distributed power system refers to a new type of power generation system that is arranged near users in a small-scale (small modular type ranging from several kilowatts to 50MW) and decentralized manner. In recent years, with the global vigorous promotion of clean energy, the wind power generation and photovoltaic power generation industries have developed rapidly, and distributed power systems based on wind power generation and photovoltaic power generation have been widely used. In order to ensure the stable operation of the above-mentioned distributed power system, it is usually necessary to pre-debug the control parameters of the distributed power system. In the prior art, this debugging is generally carried out on-site, but the controllability and safety of on-site debugging are low, and it requires a large cost. Summary of the invention

[0003] The embodiments of the present application aim to provide a data processing system, device and method based on a distributed power system, which can improve the controllability and safety of power equipment debugging in the distributed power system and reduce the debugging cost.

[0004] On the one hand, an embodiment of the present application provides a data processing system based on a distributed power system, including: an upper computer and a plurality of lower computers for running different simulation programs;

[0005] The host computer is used to obtain a discrete model of the distributed power system, and obtain multiple simulation programs of the distributed power system according to the discrete model, obtain a list of target variables or parameters in the simulation program, generate a cross-reference file containing the list, and synchronize the generated cross-reference file between the host computer and the multiple slave computers;

[0006] The upper computer is further used to determine a target lower computer for running a target simulation program among the multiple lower computers according to the cross-reference file, connect to and instruct the target lower computer to load and run the target simulation program to simulate the operation of the distributed power system;

[0007] The host computer is also used to configure a corresponding oscilloscope for the target simulation program;

[0008] The host computer is also used to obtain the simulation operation data of the distributed power system collected by the target lower computer when simulating the operation of the distributed power system, and use the oscilloscope to display the collected simulation operation data in real time.

[0009] In one aspect, an embodiment of the present application further provides a data processing device based on a distributed power system, on which a simulation tool executable by a processor is configured, the simulation tool comprising: a management module and a plurality of simulation control modules;

[0010] The management module includes: a communication module, a data processing module, a visualization module and a user input module, wherein the data processing module is used to:

[0011] Monitoring user input through the user input module, and setting simulation and / or control parameters according to the detected user input;

[0012] Acquire a discrete model of the distributed power system, and obtain multiple simulation programs of the distributed power system according to the discrete model, acquire a list of target variables or parameters in the simulation program, generate a cross-reference file containing the list, and synchronize the generated cross-reference file in the management module and the multiple simulation control modules;

[0013] According to the cross-reference file, determining a target simulation control module for running a target simulation program from among the multiple simulation control modules, and instructing the target simulation control module to load and run the target simulation program through the communication module to simulate the operation of a distributed power system;

[0014] Configuring a corresponding oscilloscope for the target simulation program; and

[0015] The communication module requests the target simulation control module for the simulation operation data of the distributed power system collected by the target simulation control module when simulating the operation of the distributed power system, and the visualization module uses the oscilloscope to display the collected simulation operation data in real time.

[0016] The present application also provides a data processing method based on a distributed power system, including:

[0017] Obtaining a discrete model of the distributed power system through a host computer, and obtaining multiple simulation programs of the distributed power system according to the discrete model, obtaining a list of target variables or parameters in the simulation program, generating a cross-index file containing the list, and synchronizing the generated cross-index file between the host computer and multiple slave computers;

[0018] According to the cross-reference file, determining a target slave computer for running a target simulation program among the multiple slave computers, connecting and instructing the target slave computer to load and run the target simulation program to simulate the operation of a distributed power system;

[0019] Configuring a corresponding oscilloscope for the target simulation program;

[0020] The simulation operation data of the distributed power system collected by the target lower computer when simulating the operation of the distributed power system is obtained, and the collected simulation operation data is displayed in real time using the oscilloscope.

[0021] The various embodiments provided in the present application, on the one hand, by utilizing a host computer to determine a lower computer for running a target simulation program according to a cross-index file, connecting and instructing the lower computer to load and run the target simulation program to simulate the operation of the power system, thereby realizing the regulation of power equipment in a distributed power system based on offline simulation, thereby improving the controllability and safety of power equipment debugging in the distributed power system and reducing the debugging cost; on the other hand, by configuring a corresponding oscilloscope for the target simulation program, obtaining the simulation operation data of the power system collected by the lower computer when simulating the operation of the power system, and using the oscilloscope to display the collected simulation operation data in real time, it can help users understand the debugging results more intuitively and improve the convenience and efficiency of power equipment debugging in the distributed power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram of the structure of a data processing system based on a distributed power system provided in one embodiment of the present application;

[0023] Figure 2 A schematic diagram of the hardware structure of a data processing device based on a distributed power system provided in one embodiment of the present application;

[0024] Figure 3 for Figure 2 A schematic diagram of the structure of the simulation tool configured in the device shown;

[0025] Figure 4 A flowchart of a data processing method based on a distributed power system provided in an embodiment of the present application;

[0026] Figure 5 A schematic diagram of a simulation run package selection interface in an embodiment of the present application;

[0027] Figure 6 is a schematic diagram of a configuration interface of an oscilloscope in an embodiment of the present application;

[0028] Figure 7 This is a schematic diagram of a curve adjustment function menu in an embodiment of the present application;

[0029] Figure 8 A schematic diagram of calling up a curve adjustment function menu in an embodiment of the present application;

[0030] Fig. 9Schematic diagram of the curve display window, mathematical curve operation window and data analysis window in the embodiment of the present application;

[0031] Fig.10 It is a schematic diagram of a photovoltaic panel simulation real-time operation data curve displayed by an oscilloscope in an embodiment of the present application;

[0032] Fig.11 It is a schematic diagram of a dynamic block diagram in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, 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 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.

[0034] See also Figure 1 , a schematic diagram of the structure of a data processing system based on a distributed power system provided by an embodiment of the present application. Figure 1 As shown, the data processing system 1000 based on the distributed power system includes: an upper computer 1010 and a plurality of lower computers 1020 for running different simulation programs.

[0035] Among them, the upper computer 1010 is used to: obtain a discrete model of the distributed power system, and obtain multiple simulation programs of the distributed power system based on the discrete model, obtain a list of target variables or parameters in the simulation program, generate a cross-index file containing the list, and synchronize the generated cross-index file between the upper computer 1010 and multiple lower computers 1020; according to the cross-index file, determine a target lower computer for running a target simulation program among the multiple lower computers, connect and instruct the target lower computer to load and run the target simulation program to simulate the operation of the distributed power system; configure a corresponding oscilloscope for the target simulation program; and obtain the simulation operation data of the distributed power system collected by the target lower computer when simulating the operation of the distributed power system, and use the oscilloscope to display the collected simulation operation data in real time.

[0036] Furthermore, the upper computer 1010 is also used to: generate multiple cross-reference files or cross-reference file sets using simulation and / or control source files, so as to be used for the upper computer 1010 to exchange data with the underlying lower computer 1020 .

[0037] Furthermore, the host computer 1010 is also used to: use the oscilloscope to generate a real-time change curve corresponding to the simulation operation data, and display the generated real-time change curve in the curve display window; and perform corresponding operations on the real-time change curve based on the user's operation of the curve adjustment function menu in the curve display window.

[0038] Furthermore, the upper computer 1010 is also used to: display a mathematical curve operation window based on the user's operation on the mathematical curve calculation menu; perform corresponding operations on the curve displayed in the curve display window according to the operation parameters input by the user in the mathematical curve operation window; and construct a third curve based on the operation results, and display the constructed third curve in the curve display window.

[0039] Furthermore, the host computer 1010 is also used to: when the user clicks the operation of the data analysis menu in the curve display window, obtain the data between the two cursors pointed to by the user when performing a preset selection operation, perform calculation and analysis on the obtained data, and output the analysis results in the data analysis window.

[0040] Furthermore, the host computer 1010 is also used to: obtain actual operation data of the power system collected by an external acquisition device, and use the oscilloscope to display the obtained actual operation data in real time; and compare and analyze the simulated operation data with the actual operation data and output the analysis results.

[0041] Furthermore, the host computer 1010 is also used to: in response to the user's operation in the simulation learning interactive interface, obtain the data of the target courseware pointed to by the operation from a preset simulation learning courseware resource database, wherein the simulation learning courseware resource database is configured on the host computer or the cloud server; and display the content of the target courseware based on the obtained data.

[0042] Furthermore, the upper computer 1010 is also used to construct a blockchain network using multiple lower computers 1020, and store simulation data and remote test data through the blockchain network. The upper computer 1010 is also used to send the operating conditions to the target lower computer while instructing the target lower computer to load and run the target simulation program; the lower computer 1020 is used to search for a candidate lower computer in the blockchain network when the target lower computer does not meet the operating conditions, and send the target simulation program to the candidate lower computer, so as to simulate the operation of the distributed power system through the candidate lower computer and obtain the simulation operation data.

[0043] For the incomplete details of the functions of the above-mentioned upper computer 1010 and the lower computer 1020, please refer to the relevant descriptions in the following embodiments.

[0044] See also Figure 2, a hardware structure diagram of a data processing device based on a distributed power system provided by an embodiment of the present application. Exemplarily, the data processing device can be any of various types of computer system devices that are non-removable or removable or portable and perform wireless or wired communication. Specifically, the electronic device can be a desktop computer, a server, a mobile phone or a smart phone (for example, a phone based on iPhone TM, a phone based on Android TM), a portable game device (for example, Nintendo DS TM, PlayStation Portable TM, Gameboy Advance TM, iPhone TM), a laptop, a PDA, a portable Internet device, a music player, and a data storage device, other handheld devices, and such as watches, headphones, pendants, headphones, etc. The electronic device can also be other wearable devices. In some cases, the electronic device can perform multiple functions (for example, playing music, displaying videos, storing pictures, and receiving and sending phone calls).

[0045] The data processing device is equipped with a simulation tool that can be executed by the processor. Figure 2 As shown, the data processing device 100 may include a control circuit, which may include a storage and processing circuit 300. The storage and processing circuit 300 may include a memory 301, such as a hard disk drive memory, a non-temporary or non-volatile memory (such as a flash memory or other electronically programmable memory with limited deletion for forming a solid-state drive, etc.), a volatile memory (such as a static or dynamic random access memory, etc.), etc., which is not limited by the embodiment of the present application. The processing circuit 302 in the storage and processing circuit 300 can be used to control the operation of the data processing device 100. The processing circuit can be implemented based on one or more microprocessors, microcontrollers, digital signal processors, baseband processors, power management units, audio codec chips, application-specific integrated circuits, display driver integrated circuits, etc. The processor can be electrically coupled to multiple temperature acquisition devices (such as micro temperature sensors).

[0046] The memory 301 stores the executable program code of the above-mentioned simulation tool, and the processor 302 coupled to the memory 301 calls the executable program code stored in the memory 301 to execute the data processing method based on the distributed power system described in the following embodiment. The executable program code may include: a management module 10 and multiple simulation control modules 20.

[0047] The management module 10 is used to generate and determine a target simulation control module for running a target simulation program based on a cross-index file, connect and instruct the target simulation control module to load and run the target simulation program to simulate the operation of the power system; configure a corresponding oscilloscope for the target simulation program; and obtain the simulation operation data of the power system collected by the target simulation control module when simulating the operation of the power system, and use the oscilloscope to display the collected simulation operation data in real time.

[0048] Optionally, the storage and processing circuit 300 can also be used to run software in the data processing device 100, such as an Internet browsing application, a Voice over Internet Protocol (VOIP) phone call application, an email application, a media playback application, an operating system function, etc. These software can be used to perform some control operations, such as image acquisition based on a camera, ambient light measurement based on an ambient light sensor, proximity sensor measurement based on a proximity sensor, information display functions based on status indicators such as status indicators of light-emitting diodes, touch event detection based on a touch sensor, functions associated with displaying information on multiple (e.g., layered) displays, operations associated with performing wireless communication functions, operations associated with collecting and generating audio signals, control operations associated with collecting and processing button press event data, and other functions in the data processing device 100, etc., which are not limited by the embodiments of the present application.

[0049] Optionally, the electronic device 100 may further include an input / output circuit 420. The input / output circuit 420 may be used to enable the electronic device 100 to input and output data, that is, to allow the electronic device 100 to receive data from an external device and also to allow the electronic device 100 to output data from the electronic device 100 to an external device. The input / output circuit 420 may further include a sensor 320. The sensor 320 may include an ambient light sensor, a proximity sensor based on light and capacitance, a touch sensor (for example, based on a light touch sensor and / or a capacitive touch sensor, wherein the touch sensor may be part of a touch display screen or may be used independently as a touch sensor structure), an acceleration sensor, and other sensors.

[0050] The input / output circuit 420 may also include one or more displays, such as the display 140. The display 140 may include a liquid crystal display, an organic light emitting diode display, an electronic ink display, a plasma display, a display using other display technologies, or a combination of several of them. The display 140 may include a touch sensor array (i.e., the display 140 may be a touch display screen). The touch sensor may be a capacitive touch sensor formed by an array of transparent touch sensor electrodes (e.g., indium tin oxide (ITO) electrodes), or may be a touch sensor formed using other touch technologies, such as sonic touch, pressure-sensitive touch, resistive touch, optical touch, etc., which is not limited in the embodiments of the present application.

[0051] Optionally, the electronic device 100 may further include an audio component 360. The audio component 360 may be used to provide audio input and output functions for the electronic device 100. The audio component 360 in the electronic device 100 may include a speaker, a microphone, a buzzer, a tone generator, and other components for generating and detecting sound.

[0052] Optionally, the communication circuit 380 can be used to provide the electronic device 100 with the ability to communicate with external devices. The communication circuit 380 may include analog and digital input / output interface circuits, and wireless communication circuits based on radio frequency signals and / or optical signals. The wireless communication circuit in the communication circuit 380 may include a radio frequency transceiver circuit, a power amplifier circuit, a low noise amplifier, a switch, a filter, and an antenna. For example, the wireless communication circuit in the communication circuit 380 may include a circuit for supporting near field communication (NFC) by transmitting and receiving near field coupled electromagnetic signals. For example, the communication circuit 380 may include a near field communication antenna and a near field communication transceiver. The communication circuit 380 may also include a cellular phone transceiver and antenna, a wireless local area network transceiver circuit and antenna, etc.

[0053] Optionally, the electronic device 100 may further include a battery, a power management circuit and other input / output units 400. The input / output units 400 may include buttons, joysticks, click wheels, scroll wheels, touch pads, keypads, keyboards, cameras, light emitting diodes and other status indicators.

[0054] A user may input commands through input / output circuit 420 to control the operation of data processing apparatus 100 , and may use output data of input / output circuit 420 to receive status information and other outputs from data processing apparatus 100 .

[0055] Combination Figure 2 and Figure 3The simulation tool adopts a modular structure, combining the simulation demonstration function with the actual control platform, and there are standard communication interfaces between the modules. The simulation tool can be an application running on a PC (personal computer) platform, such as Figure 3 As shown, it may specifically include: a management module 10 and multiple simulation control modules 20A-20N. Among them, the management module 10 and the multiple simulation control modules 20 can communicate based on standard TCP / UDP (Transmission Control Protocol / User Datagram Protocol). Such standard network communication connection between different modules can facilitate on-site deployment and team collaborative development, thereby improving the convenience and openness of equipment debugging.

[0056] Optionally, the management module 10 and multiple simulation control modules 20 can be run on the same computer platform, or they can also be run on different computer platforms. For example, when the complexity of the simulation is high or when the computer platform where the management module is located does not meet the computer performance (software and hardware) conditions required for the simulation, the simulation control module is run on other high-performance computers, or the simulation control module can also be run on a real-time control platform according to the actual control situation. Wherein the real-time control platform refers to a computer device for real-time control of the simulation object, such as a real-time control platform of a distributed power system such as a distributed wind power generation system or a distributed photovoltaic power generation system, and the real-time control platform is used to control each device in the distributed power system. In one embodiment, the management module 10 and the simulation control module 20 can be integrated on the real-time control platform of the distributed power system. When it is necessary to adjust the parameters of some or all devices in the distributed power system, the simulation control module 20 can be used to simulate the operation of the power system based on the parameters to be adjusted input by the user, and the simulation operation data of the power system collected when simulating the operation of the power system can be obtained. The management module 10 compares the simulation operation data with the preset data. If the difference between the simulation operation data and the preset data is less than the preset value, the communication module of the real-time control platform instructs the corresponding device to perform the parameter adjustment operation according to the parameter to be adjusted, so that the corresponding device operates according to the parameter to be adjusted. If the difference between the simulation operation data and the preset data is not less than the preset value, the management module 10 adjusts the parameter to be adjusted, and performs the simulation operation again through the simulation control module 20 based on the adjusted parameter, until the difference between the obtained simulation operation data and the preset data is less than the preset value. In this way, the management module 10 and the simulation control module 20 are integrated on the real-time control platform of the distributed power system. By using the real-time control platform and the internal network of the distributed power system, the simulation operation and parameter configuration of the distributed power system are performed, which can reduce hardware costs and improve data transmission security and configuration efficiency.

[0057] In this application, the management module or the computer platform running the management module can be regarded as the upper computer, and the simulation control module or the computer platform running the simulation control module can be regarded as the lower computer. The upper computer and the lower computer run independently and exchange data efficiently with a custom communication protocol. The simulation and actual control of the distributed power system can be realized through the upper computer, that is, the simulation and actual control applications share a management platform. Specifically, the above-mentioned simulation tool can be developed using QT and can run across platforms (for example: Windows or Linux). Among them, the management module 10 is mainly used for loading, operation control, simulation data acquisition, parameter setting and online analysis of basic data of the simulation control module, such as Figure 3As shown, it may specifically include: a communication module 111 , a data processing module 112 , a visualization module 113 and a user input module 114 .

[0058] The communication module 111 is used to send control instructions to the lower-layer simulation control module 20 (ie, the lower-layer application), request data, and receive data from the lower-layer application.

[0059] The data processing module 112 is used to parse the received data into usable data based on the interactive reference data, and perform basic processing such as normalization, square difference, accumulation, etc. on the data. The interactive reference data includes the data interacted between the management module 10 and the simulation control module 20 and other devices, which may include but is not limited to: the simulation model operation result data collected by the simulation control module 20, the actual operation data of each device in the power system reported by the power system, etc.

[0060] The visualization module 113 is used for real-time display of global data (table display) and real-time drawing of trend data (graphic display).

[0061] The user input module 114 is used to monitor the user's input, which is used to set simulation and / or control parameters.

[0062] Among them, the data processing module 112 is specifically used to: monitor the user's input through the user input module 114, and set simulation and / or control parameters according to the detected user's input; obtain the discrete model of the distributed power system, and obtain multiple simulation programs of the distributed power system according to the discrete model, obtain a list of target variables or parameters in the simulation program, generate a cross-index file containing the list, and synchronize the generated cross-index file in the management module and the multiple simulation control modules; according to the cross-index file, determine the target simulation control module for running the target simulation program in the multiple simulation control modules, and instruct the target simulation control module to load and run the target simulation program through the communication module 111 to simulate the operation of the distributed power system; configure a corresponding oscilloscope for the target simulation program; and request the simulation operation data of the distributed power system collected by the target simulation control module when simulating the operation of the distributed power system from the target simulation control module through the communication module 111, and use the oscilloscope to display the collected simulation operation data in real time through the visualization module 113.

[0063] The simulation control module 20 has a standard framework, which is mainly used to control the application simulation tool (or simulation tool framework or simulation program) using standard C++. The standard framework is used to establish a set of code libraries to assist the operation of simulation / control application programs, such as Figure 3As shown, it may specifically include: a task management module 121 , a data acquisition module 122 , a control command interface module 123 , a data communication module 124 , and a diagnosis module 125 .

[0064] The task management module 121 is used to schedule the running of the simulation program.

[0065] The data acquisition module 122 is used to run and manage different buffers and collect data at different rates, such as real-time update data (1-2 Hz) under normal background, low-speed curve data (2-200 Hz), and high-speed sampling data (200-20 kHz).

[0066] The control command interface module 123 is used to receive and process control instructions issued by the management module 10 .

[0067] The data communication module 124 is used to upload the collected data to the management module 10 or the server.

[0068] The diagnostic module 125 is used to upload error information of the simulation program and other control application programs.

[0069] Furthermore, the above-mentioned simulation tool may also include an analysis module. The analysis module may be a control and / or simulation tool code analysis and information extraction tool based on Python, which may be specifically used to generate multiple cross-index files or cross-index file sets using simulation and / or control source files, so as to exchange data between the management module 10 and the underlying simulation control module 20. Among them, the cross-index file may specifically store: variable information for display, parameter information for user operation, one or more information in the configuration information for management configuration, the mutual dependence between the cross-index file and the simulation control module and the lower computer, and the storage location of the source code of the simulation control module that depends on the cross-index file. In actual applications, the management module 10 connects different simulation control modules 20 by loading different cross-index files or cross-index file sets to realize the function of a general management platform.

[0070] Optionally, a serial communication interface (such as RS-232, RS-485), a CAN (Controller Area Network) interface and an Ethernet communication interface are integrated in the above-mentioned simulation tool to be applied to different data transmission requirements.

[0071] In a practical application example, the above-mentioned simulation tool can be applied to the operation monitoring training of distributed photovoltaic power systems. By using the above-mentioned simulation tool, a discrete model of photovoltaic power generation is established, a simulation program of photovoltaic power generation is obtained based on the model, and a simulation demonstration is performed based on the simulation program. Furthermore, the above-mentioned simulation tool can also be used to establish a photovoltaic power generation simulation mathematical curve operation window. By using the tools provided by the simulation tool, the photovoltaic system operation curve is operated, such as addition, subtraction, etc., to construct a third curve, and by comparing the difference between the simulation model operation results and the actual operation data of the power system, the rationality of the simulation data or the actual operation data is analyzed, etc., to judge the various operation states of the power system and discover the fault state in time.

[0072] In another practical application example, the above simulation tool can be applied to the operation monitoring training of distributed wind power generation system. By using the above simulation tool, a general wind turbine model (wherein the wind turbine parameters can be customized by the user) is established and a simulation demonstration is performed.

[0073] Optionally, the above-mentioned simulation tool may also provide a "dynamic block diagram" function, which displays the operating status of the simulation / control system in the form of a "dynamic block diagram", thereby improving the intuitiveness of the display.

[0074] Optionally, the above-mentioned simulation tool may also include a training module. The training module is used to obtain the data of the target courseware pointed to by the user in the simulation learning interactive interface from the simulation learning courseware resource database, and display the content of the target courseware according to the obtained data. The simulation learning courseware may include, but is not limited to: simulation learning courseware related to photovoltaic power generation and simulation learning courseware related to wind power generation. The main interface for displaying the above-mentioned courseware data may include, but is not limited to: an overview of new energy grid-connected technology, typical schemes of new energy grid-connected systems such as solar energy, typical schemes of wind power grid-connected systems, typical schemes of new energy grid-connected systems, secondary parts of grid-connected systems, intermittent new energy power generation access technologies, and intermittent new energy power generation power prediction technologies, etc., to trigger the display of the above-mentioned courseware content. The above-mentioned courseware may include, but is not limited to, the content of various aspects such as new energy system subsystems, grid connection, power prediction, etc., and may use engineering cases, technical specifications, application examples, etc. to vividly display the content related to wind power and photovoltaic grid connection in the power system, so as to deepen the understanding of relevant theoretical knowledge and practical operations and improve the effectiveness of simulation training. The resource database may be configured in the same computer device as the above-mentioned simulation tool, or may also be configured in a cloud server.

[0075] Optionally, the simulation tool may further include a parameter acquisition module, which is used to acquire actual operating parameters of the power system for parameter configuration of the model and simulation program, so that the simulation program and the actual running equipment have similar outputs when the same input is used.

[0076] Optionally, the management module 10 or the simulation control module 20 can also be used to remotely configure the control parameters of the power system and control the power system to operate according to the configured control parameters, and obtain on-site environmental data and equipment operation data in real time, thereby expanding the simulation tool platform into a general development and testing platform, realizing remote testing of the power system, and improving the convenience of power system debugging.

[0077] Furthermore, in order to further improve the security and controllability of simulation and remote testing, in other real-time methods of the present application, multiple lower computers can be used to build a blockchain network, and the simulation data and remote test data can be stored through the blockchain network to prevent the simulation data and remote test data from being maliciously tampered with.

[0078] It is understandable that the above training module and parameter acquisition module can also be used as part of the lower computer application (program), and communicate with the management module 10 as the upper computer through a standard network, and the management module 10 is responsible for unified monitoring and calling them.

[0079] See also Figure 4 , a flowchart of a data processing method based on a distributed power system provided in an embodiment of the present application. The method is applied to Figure 1 The system shown, Figure 4 As shown, the method specifically includes:

[0080] Step S301, obtaining a discrete model of a distributed power system through a host computer, and obtaining multiple simulation programs of the distributed power system according to the discrete model, obtaining a list of target variables or parameters in the simulation program, generating a cross-index file containing the list, and synchronizing the generated cross-index file between the host computer and multiple slave computers;

[0081] Step S302, according to the cross-reference file, determining a target slave computer for running a target simulation program from among the multiple slave computers, connecting and instructing the target slave computer to load and run the target simulation program to simulate the operation of the distributed power system;

[0082] The host computer and the multiple slave computers may be different computer devices, or the host computer and the multiple slave computers may be virtual devices running on the same computer device or different computer devices. Optionally, the host computer and the multiple slave computers may communicate based on standard TCP / UDP.

[0083] The distributed power system includes: a distributed wind power generation system and a distributed photovoltaic power generation system.

[0084] Specifically, the host computer can be started based on the user's startup operation, or each host computer can be automatically started after the computer device is started. Figure 5 The preset simulation operation package selection interface shown in the figure selects the target simulation (or control or monitoring) package, and determines the target simulation program to be run and the corresponding cross-reference file according to the target simulation package. Afterwards, the target lower computer for running the target simulation program is determined according to the corresponding cross-reference file, and the target lower computer is instructed to load and run the target simulation program to simulate the operation of the power system. In this embodiment, Figure 5 As shown, different simulation packages can correspond to different types of power equipment, such as wind power generation equipment (wind), solar photovoltaic power generation equipment (solar), etc.

[0085] Optionally, in other embodiments of the present application, a user-defined simulation package can be added or selected based on the user's new operation in the above-mentioned package selection interface. Each package in the present application is independent of each other and has no dependencies. Different versions of the same package can coexist. In this way, it supports users to add customized control / simulation packages, which can expand the use and maximize the functions.

[0086] Optionally, in other embodiments of the present application, the simulation operation package selection interface is also configured with a plug-in for selecting or inputting the operating conditions of each simulation package, and based on the operating conditions of the target simulation package selected or input by the user through the plug-in, the lower computer used to run the corresponding target simulation program can be automatically adjusted. Among them, the operating conditions include software conditions and hardware conditions, which can specifically include but are not limited to: the operating system environment (such as: the type and version of the operating system, the name and version of the software required for operation, etc.), hardware performance (such as: the computing power of the CPU, memory space), etc.

[0087] Specifically, the upper computer sends the operating condition to the target lower computer while instructing the target lower computer to load and run the target simulation program. The target lower computer confirms whether it meets the operating condition based on its own software and hardware conditions. If not, it broadcasts a proxy request in the blockchain network where it is located, and the proxy request includes the operating condition. The proxy request is used to search for a candidate lower computer in the blockchain network that can run the target simulation program; other lower computers in the blockchain network receive the proxy request, and when their own conditions meet the operating condition in the proxy request, they return response information to the target lower computer; the target lower computer determines the candidate lower computer based on the response information, and sends the target simulation program to the candidate lower computer, so as to simulate the operation of the power system through the candidate lower computer and obtain simulation operation data.

[0088] At the same time, the target lower machine can also generate a proxy log and broadcast it in the blockchain network. All nodes in the blockchain network receive the proxy log and back it up locally. The information recorded in the proxy log may include but is not limited to: the identity ID of the target lower machine, the identity ID of the candidate lower machine, the time of the proxy, the running conditions, the ID of the target simulation program, and the ID of the user (such as login account).

[0089] Furthermore, if multiple other lower computers return response information, the target lower computer randomly determines or preferably determines the candidate lower computer based on the historical duration of obtaining simulation operation data through other lower computers in the proxy history records, wherein the candidate lower computer is the lower computer among the other lower computers that has used the shortest time to obtain simulation operation data (i.e., the shortest historical duration).

[0090] Optionally, the blockchain network may be other types of networks, such as a common local area network, in which case the operations of generating proxy logs and backing them up in the blockchain network may not be performed.

[0091] Like this, when the target lower machine determined by the cross-index file does not meet the operating conditions, automatically transferring the proxy to the target lower machine and using the blockchain to save the transfer proxy log can simplify the simulation program and improve the intelligence and operating efficiency of the simulation.

[0092] Furthermore, in an actual application, the specific implementation process of generating a cross-reference file in step S301 may include: first, obtaining the field data and object model of the distributed power system, and obtaining a mathematical expression that can describe the state of the power system based on the obtained field data and object model; then, discretizing the mathematical expression to obtain a discrete model of the power system; then, converting the discrete model into a standard C or C++ code to obtain the source code of the simulation program that can be run in the lower computer; finally, scanning the source code to obtain a list of target variables or parameters in the source code, and generating the cross-reference file based on the list. It can be understood that the cross-reference file is the basis for the upper and lower levels to exchange data and communicate. Finally, the source code is compiled using a preset compiler to generate an executable simulation program.

[0093] Among them, the field data of the power system can include but is not limited to: measurement data such as power, voltage, current, etc. of power equipment, event data generated by operations such as opening and closing, overcurrent, quick disconnection, and accidents, as well as various application and environmental data used for analysis and prediction.

[0094] The object model of the power system includes various components of each power equipment in the power system. Taking wind power generation equipment as an example, the object model of wind power generation equipment mainly includes components such as wind rotor, generator, rectifier, tower, speed limit safety mechanism and energy storage device. These components together constitute the basic structure and working principle of the wind turbine.

[0095] The target variables or parameters in the source code may include, but are not limited to: variables or parameters of power equipment related to display, user operation, and management configuration in the source code. Specifically, in practical applications, they can be customized by users.

[0096] The discrete model of the power system may include, but is not limited to, a state transition model based on time series data, such as a Hidden Markov Model (HMM) and a Kalman Filter. In this model, there is a clear association between the state variables and events of the power system. For example, in a power system, the state of the generator can be defined as running or stopped, and the events of the generator start and stop are triggered by the decision of the system operator. By modeling these states and events as discrete events, the behavior of the power system under different operational decisions is simulated to test different control strategies and operating methods, and the stability and reliability of the power system are evaluated based on the simulation results, and possible future events and failures are predicted.

[0097] Step S303, configuring a corresponding oscilloscope for the target simulation program;

[0098] An oscilloscope, also known as a curve viewer, is used to display the collected simulation operation data of the power system in real time in the form of a curve.

[0099] Specifically, a preset configuration file can be called to configure one or more different types of oscilloscopes corresponding to the target simulation program. Alternatively, a preset tool interface can also be used to configure one or more different types of oscilloscopes corresponding to the target simulation program. The tool interface is integrated with the entrance of the function window of each common tool in the host computer, wherein the function window can include, for example but not limited to: a configuration window of the oscilloscope, a curve display window, and a display window of the system status (such as: CPU (Central Processing Unit, central processing unit) load, firmware version, etc.) of the corresponding lower computer (such as, the target lower computer).

[0100] Combination Figure 6 , the configuration of the oscilloscope may include but is not limited to: adding or deleting different types of oscilloscopes, and configuring the display parameters of the oscilloscope. The display parameters may include but are not limited to: variables that need to be observed in real time, such as the time of real-time sampling. Taking the addition of an oscilloscope as an example, when it is detected that the user clicks the "+ Add Trend Oscilloscope" button, the host computer will create a new oscilloscope window and enable its corresponding "Wake Up" button. Figure 6 As shown, a simulation program can support multiple types of oscilloscopes. For the same simulation program, the number of supported oscilloscopes of various types may be different. In actual applications, the configuration can be based on the user's operation in the configuration window of the oscilloscope or a preset configuration file. The preset configuration file can also be generated based on the user's configuration operation in the configuration window of the above oscilloscope and pre-stored in the local computer device or cloud server.

[0101] Step S304, obtaining the simulation operation data of the distributed power system collected by the target lower computer when simulating the operation of the distributed power system, and using the oscilloscope to display the collected simulation operation data in real time.

[0102] Optionally, the oscilloscope may be used to generate a corresponding real-time change curve for the collected simulation operation data, and the generated real-time change curve may be displayed in a curve display window.

[0103] Furthermore, the curve display window is also configured with a curve adjustment function menu, such as Figure 7 As shown, the curve adjustment function menu can be configured above the curve display window in the form of a graphic control, or can also be configured as shown in Figure 8As shown, the display is called by right clicking on the curve display area of ​​the curve display window. The method also includes: performing corresponding operations on the real-time changing curve based on the user's operation on the curve adjustment function menu in the curve display window.

[0104] The above corresponding operations may include but are not limited to: temporary data acquisition, moving the cursor, displaying the time currently pointed to by the cursor at the bottom of the cursor, displaying the current time and the value of the curve in data form at the intersection of the cursor and the curve, moving the cursor, displaying the time difference between the two cursors and the corresponding frequency value at the top of the curve window, scaling the curve, locking the time difference between the cursors, and comparing and viewing curves of different sections and the same time difference, etc.

[0105] Specifically, Fig. 9 As shown, based on the user's operation on the mathematical curve calculation menu, the mathematical curve operation window is superimposed on the curve display window, and according to the operation parameters input by the user in the mathematical curve operation window, the curve displayed in the curve display window is subjected to corresponding operation (such as addition or subtraction, etc.), and a third curve is constructed according to the operation result, and the constructed third curve is displayed in the curve display window. By constructing multiple curves and superimposing them, the user can intuitively understand the curve changes before and after the adjustment.

[0106] like Fig. 9 As shown, the mathematical curve operation window includes: a configuration part for curve source 1 for calculation, an operator configuration part, a configuration part for curve source 2 for calculation, and a part for specifying the name of the newly generated curve.

[0107] Furthermore, the rationality of the collected simulation operation data can be analyzed and the analysis results can be output. Fig. 9 When the user clicks the operation of the data analysis menu in the curve display window, the data between the two cursors pointed to by the user performing the preset selection operation is obtained, the obtained data is calculated and analyzed, and the data is displayed in the data analysis window (such as Fig. 9 The analysis results are output in the "Variables and Measurements" window below. The calculation analysis may include, but is not limited to: calculating the difference, mean, and root mean square of the data between the two cursors, and comparing the size of the data between the two cursors. The above calculation analysis can improve the data processing efficiency.

[0108] The preset selection operation may be, for example, a click, a cursor move, a click again, or other user-defined operations. The calculation analysis uses the data between the two cursors as a sample to perform various preset calculations in real time, which may include, but are not limited to: calculating the maximum value, the minimum value, the root mean square, the cursor difference, the mean value, etc. Furthermore, the calculation result may be compared with the preset threshold, and the value greater than or less than the preset threshold may be marked in the data analysis window to prompt the user that the data is unreasonable, thereby providing parameter configuration guidance to the user during device debugging.

[0109] Furthermore, based on the user's check operation on the check box of the name column in the data analysis window, the curve pointed to by the check operation can be displayed in the curve display area, and the curve can be all or part of the curve.

[0110] Furthermore, the actual operation data of the power system collected by the external collection device can be obtained through Ethernet, and the actual operation data obtained can be displayed in real time using the above oscilloscope, and the simulation operation data collected when running the simulation program can be compared with the actual operation data and the analysis results can be output. The real-time change curve corresponding to the simulation operation data can be compared with the real-time change curve corresponding to the actual operation data, and when the offset between the two is greater than the preset offset, the fault prompt information is output.

[0111] Optionally, the operating status of the simulated power system can be more intuitively displayed by means of a "dynamic block diagram" to help users intuitively understand the impact of different operating parameters on the operating variables of the simulated power system. Specifically, the method also includes: loading the operating schematic diagram of the power system from a specified directory and displaying it in a preset dynamic block diagram display window; when the user performs a parameter modification operation in the dynamic block diagram display window, obtaining the parameter value input by the user, calculating the value of the corresponding output variable according to the parameter value, and updating the calculated value in the dynamic block diagram display window.

[0112] The operation schematic diagram is drawn by the user in a specified format, and may include, but is not limited to, an operation flow chart of the power system, a system operation status diagram, and a structural block diagram.

[0113] Furthermore, in order to improve the security and controllability of simulation and remote testing, in other embodiments of the present application, multiple lower computers can be used to build a blockchain network, and the simulation data and remote test data can be stored through the blockchain network to prevent the simulation data and remote test data from being maliciously tampered with.

[0114] Specifically, each slave computer can be distributed in different local area networks or Ethernet networks, but at the same time can serve as a node in the blockchain network, and has a unique identity identification ID in the blockchain network. The ID can be but is not limited to: the MAC address (Media Access Control Address) of the slave computer, or the device serial number, or a random number generated by the upper computer using a hash function and assigned to each slave computer.

[0115] After sending the simulation operation data to the upper computer, the lower computer generates a simulation log at the same time and backs up the simulation log in multiple nodes of the blockchain network by broadcasting. The multiple nodes meet the backup conditions contained in the broadcast.

[0116] The simulation log may include but is not limited to: the identity ID of the lower computer, the identity ID of the running target simulation program, the identity ID of the user associated with the target simulation program, the running time, the system login location of the user, and the obtained simulation running data.

[0117] The associated user, that is, the user who triggers this simulation task, is Figure 5 The user who performs the selection operation in the preset simulation run package selection interface shown. It can be understood that before each simulation task is executed, the user needs to log in to the system on the host computer using a pre-registered account. The host computer generates a login log including relevant information of the login behavior based on the user's login behavior, and backs up the login log on all nodes in the blockchain network in the form of broadcast to ensure that each user's login information is authentic and reliable. In order to further improve the controllability and security of simulation and testing, users must pass identity authentication before they can log in to the system. The host computer verifies the identity of the user using the verification information reserved by the user and the identity information currently entered by the user. If the identity information currently entered by the user matches the reserved verification information, the user is allowed to log in to the system.

[0118] The backup condition may include but is not limited to at least one of the following conditions: the registration time on the blockchain network is less than the preset time, the average daily online time within the preset period is greater than the preset time, the storage space is greater than the preset space, and the location is not the user's system login location, etc. The system login location may be the location of the IP address used by the user to log in to the system.

[0119] The host computer can remotely configure the control parameters of the power system according to the user's test instructions. If the test instruction is triggered by the user at the same time as the simulation instruction is triggered, the host computer can instruct the slave computer to load and run the target simulation program to simulate the operation of the power system while instructing the slave computer to remotely configure the control parameters of the power system.

[0120] The host computer generates a parameter configuration data packet and determines the target hash algorithm in a random manner from a preset hash algorithm library. The parameter configuration data packet carries the local ID information, the user's identification information, the control parameters to be configured, and the identification information of the equipment to be configured in the power system. The hash algorithms stored in the hash algorithm library may include, but are not limited to, MD4, MD5, SHA-1, SHA-256, and SHA-512.

[0121] The host computer generates a first key according to the parameter configuration data packet using the target hash algorithm, encrypts and compresses the parameter configuration data packet using the generated first key, and sends the generated encrypted compressed package and the number of the target hash algorithm to the control device of the power system, wherein the number can be stored in the first position of the TCP / UDP message data field or the end of the header field, so that the control device determines the hash algorithm used for decryption from the hash algorithm library stored in the local or cloud server according to the number, and obtains the parameter configuration data packet using the hash algorithm, and reconfigures the control parameters of the device to be configured based on the parameter configuration data packet and controls the device to be configured to re-run according to the new control parameters. At the same time, the host computer also backs up the compressed package in multiple nodes of the blockchain network in the form of broadcast, and the multiple nodes meet the backup conditions in the broadcast.

[0122] When the host computer receives the actual operation data of the power system returned by the control device of the power system, the host computer generates a test log and backs it up in multiple nodes of the blockchain network in the same way as backing up the simulation operation data.

[0123] It can be understood that if the upper computer instructs the lower computer to remotely configure the control parameters of the power system, the lower computer can generate a test log in the same manner as described above and back it up in multiple nodes of the blockchain network.

[0124] Furthermore, before the upper computer compares and analyzes the simulation operation data with the actual operation data and outputs the analysis results, if the time difference between the time of triggering the analysis and the time of acquiring the simulation operation data and the actual operation data is greater than the preset time difference, then a request to acquire the simulation operation data and the actual operation data is broadcast in the blockchain network to acquire multiple backups of the simulation operation data and the actual operation data from the blockchain network, and when the acquired backups are consistent with the simulation operation data and the actual operation data stored locally in the upper computer, an operation of comparing and analyzing the simulation operation data with the actual operation data and outputting the analysis results is performed, thereby ensuring the authenticity and reliability of the operation data used for comparative analysis.

[0125] Furthermore, in order to increase the speed of consistency comparison and save storage space, a second key can be generated using a randomly determined hash algorithm during backup, and the simulation operation data or actual operation data to be backed up can be encrypted and compressed using the second key to obtain an encrypted compressed package and associate the number of the hash algorithm of the second key with the simulation operation data or actual operation data to be backed up, then delete the original operation data, save the encrypted compressed package locally instead of the original operation data, and back it up in the blockchain network. When a consistency comparison is required, the second key is restored according to the hash algorithm corresponding to the number. If the second key can decompress the corresponding compressed package stored locally and backed up in the blockchain network, it can be confirmed that the obtained backup is consistent with the operation data stored locally.

[0126] Furthermore, the host computer can also use the same backup method as above to back up the analysis results in the blockchain network.

[0127] Optionally, in other embodiments of the present application, the host computer is also used to provide simulation training, and the method further includes: in response to the user's operation on the simulation learning interactive interface, obtaining the data of the target courseware pointed to by the operation from a preset simulation learning courseware resource database, wherein the simulation learning courseware resource database is configured locally on the computer device or on a cloud server; and displaying the content of the target courseware according to the obtained data. The above-mentioned simulation learning courseware may include, but is not limited to, engineering cases, technical specifications, and application examples, etc.

[0128] In this way, by utilizing the simulation learning courseware resource database to conduct integrated training and learning, and by vividly displaying the relevant content of wind power and photovoltaic power generation grid connection in smart power systems, users can deepen their understanding of relevant theoretical knowledge and practical operations and improve the effectiveness of simulation training.

[0129] In the following, a distributed wind power generation system and a distributed photovoltaic power generation system are taken as examples to illustrate the data processing method based on the distributed power system provided by the present application.

[0130] Taking distributed wind power generation system as an example

[0131] It can be understood that the shaft output torque of the fan is mainly determined by the fan speed, the windward angle of the blades and the wind speed.

[0132] First, the model of the wind power generation equipment in the wind power generation system and the input and output parameters of the wind power generation equipment input by the user are obtained, wherein the input and output parameters include: win_spd (wind speed), generator_spd (wind turbine speed) and pitch_spd (blade windward angle) as input parameters, and Tm(pu) (output mechanical torque of the wind turbine generator) as output parameter. 。

[0133] Secondly, according to the obtained model and input and output parameters, the key parameters of the wind power generation equipment are obtained, and the object model of the wind power generation equipment is established based on the key parameters. The key parameters may include, but are not limited to: hub height, impeller diameter or swept area, rated power, rated wind speed, etc.

[0134] Then, the field data of the wind power generation equipment is acquired, and based on the field data and the object model, a mathematical expression that can describe the wind power generation equipment is obtained, wherein the field data includes the environmental data of the operation of the wind power generation equipment.

[0135] Afterwards, the mathematical expression is discretized to obtain a discrete model of the wind power generation equipment as a discrete model of the distributed wind power generation system.

[0136] After that, the discrete model is converted into standard C or C++ code to obtain the source code of the simulation program of the wind power generation equipment that can be run in the lower computer, and then the source code is compiled using a preset compiler to obtain an executable simulation program (i.e., the simulation operation package of the wind power generation equipment). At the same time, the source code is scanned to obtain a list of target variables or parameters in the source code, and a cross-index file is generated based on the list for data interaction between the upper computer and the lower computer.

[0137] Finally, the upper computer instructs the lower computer to load and run the simulation program to simulate the operation of the wind power generation equipment, obtains the simulation operation data of the wind power generation equipment collected by the lower computer to simulate the operation of the wind power generation equipment, and uses an oscilloscope to display the obtained simulation operation data in real time in the form of a curve.

[0138] Like this, based on the mathematical model of a typical wind turbine, functional modules of each logical part are established to form a simulation system that is the same as the actual operating wind turbine. By comparing the offline simulation operation data of the wind turbine with the online actual operation data, the status of the actual operating wind turbine can be monitored and alarmed based on the difference between the two.

[0139] Optionally, an oscilloscope tool can be used to record the output characteristics under different setting parameter conditions, such as the output at different pitch angles, different outputs at different wind speeds, and so on.

[0140] Taking distributed photovoltaic power generation system as an example

[0141] It can be understood that a photovoltaic panel is actually a controlled current source, and its output voltage is affected by light and temperature.

[0142] First, in a manner similar to the above-mentioned distributed wind power generation system, the model of the photovoltaic panel and the input and output parameters of the photovoltaic panel input by the user are obtained, wherein the input parameters may include but are not limited to light and temperature, and the output parameters may include but are not limited to output voltage.

[0143] Then, according to the acquired signals and input and output parameters, the simulation program of the photovoltaic panel and the corresponding cross-reference file are obtained in a manner similar to the above-mentioned distributed wind power generation system.

[0144] Afterwards, the upper computer is connected to the lower computer and instructs the lower computer to load and run the simulation program to start the simulation. The upper computer obtains the simulation operation data of the photovoltaic panel collected by the lower computer, and uses an oscilloscope to display the obtained simulation operation data in real time in the form of a curve.

[0145] The user can perform related operations in the curve display window of the oscilloscope, such as: pausing data acquisition, displaying the time currently pointed to by the cursor at the bottom of the cursor by moving the cursor, displaying the current time and the value of the curve at the intersection of the cursor and the curve, or displaying the time difference between the two cursors and the corresponding frequency value at the top of the curve window by moving the cursor, etc.

[0146] like Fig.10 As shown in the figure, the curve shows the changes in the output voltage and current of the photovoltaic panel when it receives light. Since the load is a capacitive load, the current is very large at startup. When the voltage increases, the current gradually decreases to a stable value. By changing the temperature and light intensity and restarting the simulation, different simulation results can be obtained.

[0147] Furthermore, the user can use the various tools in the menu bar provided in the above-mentioned curve display window to perform preset operations on the curve displayed in the window, such as using the zoom in or zoom out tool to scale the curve graph, or locking the time difference between cursors, and comparing and viewing curves of different segments and the same time difference in the variable and measurement value window, etc.

[0148] Furthermore, the user can also use the tools provided in the mathematical curve operation window to perform operations on the photovoltaic system simulation and / or actual operation curves, such as addition, subtraction, etc., to construct a third curve, and by comparing the differences between the simulation model results (simulation operation curve) and the actual system received data (actual operation curve), analyzing the rationality of the data, etc., judge the various system states and discover fault states in a timely manner.

[0149] Furthermore, users can also use the basic data analysis window to perform various calculations on the collected simulation operation data and / or actual operation data in real time, using the data between the two cursors as samples. These calculations include maximum, minimum, root mean square, cursor difference, mean, etc. In addition, by checking the box in the name column, you can selectively display all or part of the curves in the curve display area.

[0150] Further, combined with Fig.11 , users can also use the "Dynamic Block Diagram" to have a more intuitive understanding of the relationship between input parameters and output parameters, thereby improving the efficiency of equipment control. Specifically, in the "Dynamic Block Diagram" window, when the user double-clicks Fig.11 The parameter setting box in the dotted box on the left is used to modify the operating parameters of the photovoltaic panel. Fig.11 The variable display box in the dotted box on the right displays the changes of the current variables in real time.

[0151] For details not covered in this embodiment, please refer to the above Figures 2 to 3 The relevant contents of the illustrated embodiment will not be repeated here.

[0152] In the embodiments of the present application, on the one hand, by utilizing the upper computer to determine the lower computer for running the target simulation program according to the cross-index file, connecting and instructing the lower computer to load and run the target simulation program to simulate the operation of the power system, the regulation of the power equipment in the distributed power system based on offline simulation is realized, thereby improving the controllability and safety of the debugging of the power equipment in the distributed power system and reducing the debugging cost; on the other hand, by configuring the corresponding oscilloscope for the target simulation program, obtaining the simulation operation data of the power system collected by the lower computer when simulating the operation of the power system, and using the oscilloscope to display the collected simulation operation data in real time, it can help users understand the debugging results more intuitively and improve the convenience and efficiency of debugging of power equipment in the distributed power system.

[0153] Furthermore, the present application also provides a computer-readable storage medium, which may be provided in the computer device in the above embodiments. Figure 2 The memory in the storage and processing circuit 300 in the illustrated embodiment. The computer-readable storage medium stores a computer program, and when the program is executed by the processor, the above-mentioned data processing method based on the distributed power system is implemented. Further, the computer-readable storage medium can also be a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), RAM, a magnetic disk or an optical disk, etc., which can store program codes.

[0154] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0155] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0156] The above is a description of the data processing system, device and method based on the distributed power system provided by the present application. For technicians in this field, according to the ideas of the embodiments of the present application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A data processing system based on a distributed power system, characterized in that: It includes: a host computer and multiple slave computers for running different simulation programs; The host computer is used to obtain a discrete model of the distributed power system, and obtain multiple simulation programs of the distributed power system according to the discrete model, obtain a list of target variables or parameters in the simulation program, generate a cross-reference file containing the list, and synchronize the generated cross-reference file between the host computer and the multiple slave computers; The upper computer is further used to determine a target lower computer for running a target simulation program among the multiple lower computers according to the cross-reference file, connect to and instruct the target lower computer to load and run the target simulation program to simulate the operation of the distributed power system; The host computer is also used to configure a corresponding oscilloscope for the target simulation program; The host computer is further used to obtain the simulation operation data of the distributed power system collected by the target lower computer when simulating the operation of the distributed power system, and to display the collected simulation operation data in real time using the oscilloscope; The cross-reference file is the basis for the upper computer to exchange data and communicate with each of the lower computers. The cross-reference file stores: one or more of variable information for display, parameter information for user operation, and configuration information for management configuration, the mutual dependence between the cross-reference file and each of the lower computers, and the storage location of the source code of each of the lower computers that depends on the cross-reference file; The generating of the cross-reference file containing the list comprises: Acquire field data and an object model of the distributed power system, and obtain a mathematical expression for describing a state of the distributed power system according to the acquired field data and the object model, wherein the object model of the distributed power system includes various components of each power device in the distributed power system; Discretizing the mathematical expression to obtain a discrete model of the distributed power system, and converting the discrete model into a standard C or C++ code to obtain a source code of a simulation program running in the lower computer; and The source code is scanned to obtain a list of target variables or parameters in the source code, and the cross-reference file is generated according to the list.

2. The system according to claim 1, characterized in that The host computer is also used to generate multiple cross-reference files or cross-reference file sets using simulation and / or control source files, so as to be used for the host computer to exchange data with the underlying lower computers.

3. The system according to claim 1, characterized in that The host computer is also used for: Using the oscilloscope to generate a real-time change curve corresponding to the simulation operation data, and displaying the generated real-time change curve in a curve display window; Based on the user's operation on the curve adjustment function menu in the curve display window, a corresponding operation is performed on the real-time change curve.

4. The system according to claim 3, characterized in that The host computer is also used for: Based on the user's operation on the mathematical curve calculation menu, displaying a mathematical curve operation window; According to the operation parameters input by the user in the mathematical curve operation window, a corresponding operation is performed on the curve displayed in the curve display window; A third curve is constructed according to the calculation result, and the constructed third curve is displayed in the curve display window.

5. The system according to claim 3, characterized in that The host computer is also used for: When the user clicks on the data analysis menu in the curve display window, the data between the two cursors pointed to by the user during the preset selection operation is obtained, the obtained data is calculated and analyzed, and the analysis results are output in the data analysis window.

6. The system according to claim 1, wherein: The host computer is also used for: Acquire actual operation data of the power system collected by an external collection device, and use the oscilloscope to display the acquired actual operation data in real time; The simulation operation data is compared and analyzed with the actual operation data, and the analysis result is output.

7. The system according to claim 1, characterized in that The host computer is also used for: In response to the user's operation on the simulation learning interactive interface, the data of the target courseware pointed to by the operation is obtained from a preset simulation learning courseware resource database, wherein the simulation learning courseware resource database is configured on the host computer or the cloud server; Based on the acquired data, the content of the target courseware is displayed.

8. The system of claim 1, wherein: The upper computer is further used to construct a blockchain network using a plurality of the lower computers, and store the simulation data and the remote test data through the blockchain network; The host computer is further used to send the operating conditions to the target lower computer while instructing the target lower computer to load and run the target simulation program; The lower computer is used to search for a standby lower computer in the blockchain network when the target lower computer does not meet the operating conditions, and send the target simulation program to the standby lower computer, so as to simulate the operation of the distributed power system through the standby lower computer and obtain the simulation operation data.

9. A data processing method based on a distributed power system, characterized in that: include: Obtaining a discrete model of the distributed power system through a host computer, and obtaining multiple simulation programs of the distributed power system according to the discrete model, obtaining a list of target variables or parameters in the simulation program, generating a cross-index file containing the list, and synchronizing the generated cross-index file between the host computer and multiple slave computers; According to the cross-reference file, determining a target slave computer for running a target simulation program among the multiple slave computers, connecting and instructing the target slave computer to load and run the target simulation program to simulate the operation of the distributed power system; Configuring a corresponding oscilloscope for the target simulation program; Acquire simulation operation data of the distributed power system collected by the target lower computer when simulating the operation of the distributed power system, and display the collected simulation operation data in real time using the oscilloscope; The cross-reference file is the basis for the upper computer to exchange data and communicate with each of the lower computers. The cross-reference file stores: one or more of variable information for display, parameter information for user operation, and configuration information for management configuration, the mutual dependence between the cross-reference file and each of the lower computers, and the storage location of the source code of each of the lower computers that depends on the cross-reference file; The generating of the cross-reference file containing the list comprises: Acquire field data and an object model of the distributed power system, and obtain a mathematical expression for describing a state of the distributed power system according to the acquired field data and the object model, wherein the object model of the distributed power system includes various components of each power device in the distributed power system; Discretizing the mathematical expression to obtain a discrete model of the distributed power system, and converting the discrete model into a standard C or C++ code to obtain a source code of a simulation program running in the lower computer; and The source code is scanned to obtain a list of target variables or parameters in the source code, and the cross-reference file is generated according to the list.

10. A data processing device based on a distributed power system, characterized in that: include: A memory and a processor coupled to the memory, wherein the memory stores executable program code, and the processor calls the executable program code to execute the data processing method based on the distributed power system as claimed in claim 9.

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