Data analysis and optimization system of power supply chain

Abstract

The invention discloses a data analysis and optimization system for a power supply chain, and the system comprises a data collection and integration module which is used for carrying out the data acquisition of each link of power supply through a sensor network, obtaining the sensor data corresponding to each link, carrying out the integration processing of the sensor data corresponding to all links, and obtaining a data collection module; obtaining supply chain data corresponding to each link; the data analysis module is used for carrying out analysis processing on the supply chain data corresponding to each link based on the data characteristics of each link to obtain an analysis result, and carrying out early warning operation based on the analysis result; the optimization decision module is used for performing overall layout optimization on the supply chain data and the analysis result corresponding to each link according to a genetic algorithm to obtain a layout structure optimization scheme, and performing power dispatching optimization on the supply chain data and the analysis result corresponding to each link according to a simulated annealing algorithm to obtain a power dispatching plan; and outputting a layout structure optimization scheme and a power dispatching plan.

Description

Technical Field

[0001] The present invention belongs to the field of electric power technology, and more specifically, relates to a data analysis and optimization system for an electric power supply chain. Background Art

[0002] In today's power sector, the power supply chain covers key links such as power generation, transmission, distribution and consumption. Data on the power supply chain is crucial to ensuring the efficient and stable operation of the power system.

[0003] In the existing technology, there are serious defects in data collection. In the power generation link, the data collection means are single and scattered, and most of the isolated equipment monitors simple parameters such as power generation and basic operating temperature of equipment. There is a lack of a unified collection platform to integrate all relevant data, resulting in a large amount of valuable data loss. In the transmission process, the line status data is mainly obtained by manual periodic inspections. This method not only fails to obtain data in a timely manner, but also fails to continuously and effectively control the data on the line. The data collection in the distribution link is also not perfect. There is a lack of unified summary and management of distribution data in various regions, and data in different regions are often isolated. In the consumption link, the data collection accuracy is low, and it is difficult to accurately reflect deep-level information such as users' electricity usage habits. In other words, there is a problem of poor data processing in the entire link of the power supply chain, which makes it impossible to effectively control and optimize the power supply chain as a whole, reducing the utilization rate of power resources.

[0004] Therefore, how to effectively manage and optimize the power supply chain as a whole and improve the utilization rate of power resources is a key issue that technical personnel in this field are concerned about. Summary of the invention

[0005] The purpose of this application is to provide a data analysis and optimization system for the power supply chain, so as to achieve effective management and optimization of the power supply chain as a whole and improve the utilization rate of power resources.

[0006] In view of the above defects or improvement needs of the prior art, the present invention provides a data analysis and optimization system for a power supply chain, comprising:

[0007] The data acquisition and integration module is used to acquire data from each link of the power supply through the sensor network, obtain sensor data corresponding to each link, and integrate the sensor data corresponding to all links to obtain supply chain data corresponding to each link; wherein the sensor network includes: a sensor network for the power generation link, a sensor network for the power transmission link, a sensor network for the power distribution link, and a sensor network for the consumption link;

[0008] A data analysis module, used to analyze and process the supply chain data corresponding to each link based on the data characteristics of each link, obtain analysis results, and perform early warning operations based on the analysis results;

[0009] An optimization decision module is used to optimize the overall layout of the supply chain data and analysis results corresponding to each link according to a genetic algorithm to obtain a layout structure optimization plan, and to optimize the power dispatching of the supply chain data and analysis results corresponding to each link according to a simulated annealing algorithm to obtain a power dispatching plan; and output the layout structure optimization plan and the power dispatching plan;

[0010] The data interaction module is used to interact with the power system through a compatible interface and a middleware platform so as to obtain the sensor data from the sensor network.

[0011] Optionally, the data collection and integration module includes: a power generation link data collection unit, a power transmission link data collection unit, a power distribution link data collection unit, a consumption link data collection unit, and a data integration unit;

[0012] The power generation link data acquisition unit is used to monitor the changes in the microstructure inside the power equipment through micro sensors to obtain microstructure change data, and use the power generation state data and the microstructure change data obtained by the power generation link sensor network as the sensor data corresponding to the power generation link;

[0013] The power transmission link data acquisition unit is used to use the high-definition camera and electromagnetic induction sensor carried by the drone to regularly inspect the power transmission line and collect line appearance data and electromagnetic field strength data as sensor data corresponding to the power transmission link;

[0014] The power distribution link data acquisition unit is used to record power consumption data and power quality data through smart meters, and to perform short-distance data communication with adjacent smart meters to form a local power distribution data network, and to obtain power consumption data and power quality data from the power distribution data network as sensor data corresponding to the power distribution link;

[0015] The consumption link data collection unit is used as a home appliance data collector based on the Internet of Things to collect data from home appliances of various brands and models, and obtain operating status data and energy consumption data as sensor data corresponding to the consumption link;

[0016] The data integration unit is used to integrate the sensor data corresponding to all links in a preset data format to obtain the supply chain data corresponding to each link.

[0017] Optionally, the data analysis module includes: a power generation link analysis unit, a power transmission link analysis unit, a power distribution link analysis unit, a consumption link analysis unit, and a data early warning unit;

[0018] The power generation link analysis unit is used to train the deep learning algorithm according to the historical operation data of the power generation equipment to obtain the equipment health model, and to perform equipment health prediction on the supply chain data of the power generation link based on the equipment health model to obtain a health mode. When the health mode is an abnormal mode, the fault type and severity are determined based on the supply chain data of the power generation link as the analysis result of the power generation link;

[0019] The power transmission link analysis unit is used to process the supply chain data of the power transmission link using a cluster analysis algorithm to obtain different risk level areas as the analysis results of the power transmission link;

[0020] The power distribution link analysis unit is used to perform power distribution scenario analysis on the supply chain data of the power distribution link based on the power distribution analysis model to obtain the analysis result of the power distribution link;

[0021] The consumption link analysis unit is used to analyze the supply chain data of the consumption link by using an association rule mining algorithm to obtain a usage association pattern and obtain an analysis result of the consumption link;

[0022] The data early warning unit is used to monitor the analysis results through a real-time data processing platform and send an early warning signal when abnormal fluctuations occur in the data.

[0023] Optionally, the optimization decision module includes: a decision optimization implementation unit, a scheduling planning unit, and a result output unit;

[0024] The implementation decision optimization unit is used to optimize the overall layout of the supply chain data and analysis results corresponding to each link according to the genetic algorithm to obtain a layout structure optimization plan;

[0025] The dispatch planning unit is used to optimize the power dispatching for the supply chain data and analysis results corresponding to each link according to the simulated annealing algorithm to obtain a power dispatching plan;

[0026] The result output unit is used to output the layout structure optimization plan and the power dispatching plan.

[0027] Optionally, the data interaction module is specifically used to construct the compatible interface and the middleware platform based on the software information and hardware information of the power equipment, and interact with the power system through the compatible interface and the middleware platform to obtain the sensor data from the sensor network.

[0028] Optionally, it also includes: a decision support module, which is used to construct a decision support interface, and display the analysis results, the layout structure optimization plan, and the power dispatch plan through the decision support interface.

[0029] Optionally, it also includes: an external system interaction module, which is used to acquire data from the weather forecast system and the energy market trading system respectively through a preset network link, obtain meteorological data and energy market trading data, and add the meteorological data and the energy market trading data to the supply chain data.

[0030] The present application provides a data analysis and optimization system for a power supply chain, including:

[0031] The data acquisition and integration module is used to acquire data from each link of the power supply through the sensor network, obtain sensor data corresponding to each link, and integrate the sensor data corresponding to all links to obtain supply chain data corresponding to each link; wherein the sensor network includes: a sensor network for the power generation link, a sensor network for the power transmission link, a sensor network for the power distribution link, and a sensor network for the consumption link;

[0032] A data analysis module, used to analyze and process the supply chain data corresponding to each link based on the data characteristics of each link, obtain analysis results, and perform early warning operations based on the analysis results;

[0033] An optimization decision module is used to optimize the overall layout of the supply chain data and analysis results corresponding to each link according to a genetic algorithm to obtain a layout structure optimization plan, and to optimize the power dispatching of the supply chain data and analysis results corresponding to each link according to a simulated annealing algorithm to obtain a power dispatching plan; and output the layout structure optimization plan and the power dispatching plan;

[0034] The data interaction module is used to interact with the power system through a compatible interface and a middleware platform so as to obtain the sensor data from the sensor network.

[0035] It has the following beneficial effects:

[0036] Through the data acquisition and integration module, the data of each link of the power supply chain is fully acquired and effectively integrated, providing a data basis for overall management and control. The data analysis module can deeply analyze the data of each link, discover problems in time and issue early warnings, which is conducive to precise management and optimization. The optimization decision module uses genetic algorithms and simulated annealing algorithms to optimize the overall layout and power dispatching respectively, improving the allocation efficiency and utilization rate of power resources. The data interaction module ensures the smooth flow and sharing of data and enhances the synergy of the supply chain. The system realizes the effective management and optimization of the power supply chain as a whole, greatly improves the utilization rate of power resources, makes the power supply more stable and efficient, and meets the society's demand for electricity. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0038] Figure 1 A schematic diagram of the structure of a data analysis and optimization system for a power supply chain provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] The core of this application is to provide a data analysis and optimization system for the power supply chain, so as to achieve effective management and optimization of the power supply chain as a whole and improve the utilization rate of power resources.

[0040] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0041] The following describes an example of an electric power supply chain data analysis and optimization system provided by the present application.

[0042] Please refer to Figure 1 , Figure 1 A schematic diagram of the structure of a data analysis and optimization system for a power supply chain provided in an embodiment of the present application.

[0043] In this embodiment, the system may include:

[0044] The data acquisition and integration module 10 is used to acquire data from each link of the power supply through the sensor network, obtain sensor data corresponding to each link, and integrate the sensor data corresponding to all links to obtain supply chain data corresponding to each link; wherein the sensor network includes: a sensor network for the power generation link, a sensor network for the power transmission link, a sensor network for the power distribution link, and a sensor network for the consumption link;

[0045] The data collection and integration module 10 collects data comprehensively through sensor networks in different links, including power generation, transmission, distribution and consumption, and then integrates these data to obtain complete supply chain data. In the power generation link, micro sensors are used to monitor the changes in the internal microstructure of the equipment, combined with the power generation status data; drone inspections are used to obtain line data in the power transmission link; smart meters and data communications are used to obtain relevant data in the power distribution link; and home appliance data collectors are used in the consumption link to obtain home appliance data. Finally, integration is performed through a preset data format.

[0046] It can be seen that being able to comprehensively and accurately obtain data from all links in the power supply chain provides a reliable data basis for subsequent analysis and optimization, avoids data omissions and isolation, and helps to achieve overall control of the supply chain.

[0047] The data analysis module 20 is used to analyze and process the supply chain data corresponding to each link based on the data characteristics of each link, obtain analysis results, and perform early warning operations based on the analysis results;

[0048] The data analysis module 20 uses corresponding analysis methods to process the data according to the characteristics of each link to discover potential problems and issue early warnings in a timely manner. The power generation link uses deep learning algorithms to train the equipment health model for prediction; the transmission link uses clustering analysis algorithms to divide risk level areas; the distribution link performs scenario analysis based on the distribution analysis model; the consumption link uses association rule mining algorithms to analyze usage association patterns. At the same time, monitoring is carried out through a real-time data processing platform.

[0049] This module can accurately analyze data from each link, promptly detect equipment failures, line risks and other problems, and provide early warnings, which will help to take targeted measures to ensure the stable operation of the power supply chain and improve power supply reliability.

[0050] The optimization decision module 30 is used to optimize the overall layout of the supply chain data and analysis results corresponding to each link according to the genetic algorithm to obtain a layout structure optimization plan, and to optimize the power dispatching of the supply chain data and analysis results corresponding to each link according to the simulated annealing algorithm to obtain a power dispatching plan; and output the layout structure optimization plan and the power dispatching plan;

[0051] The optimization decision module 30 uses a genetic algorithm to optimize the overall layout of the supply chain data and a simulated annealing algorithm to optimize the power dispatching to improve the efficiency and economy of the supply chain. The genetic algorithm finds the optimal layout structure optimization plan based on the data and analysis results of each link; the simulated annealing algorithm generates the best power dispatching plan based on the same data and results.

[0052] It has achieved global optimization of the power supply chain, making the layout more reasonable and the power dispatch more scientific, which can effectively reduce costs, improve the utilization efficiency of power resources, and enhance the responsiveness and adaptability of the supply chain.

[0053] The data interaction module 40 is used to interact with the power system through a compatible interface and a middleware platform to obtain sensor data from the sensor network.

[0054] The data interaction module 40 achieves efficient interaction with the power system by building a compatible interface and middleware platform to ensure smooth acquisition and transmission of data. Based on the software and hardware information of the power equipment, a compatible interface and middleware platform are created to enable seamless interaction with the power system, thereby smoothly acquiring sensor data from the sensor network. This ensures timely acquisition and sharing of data, breaks down information barriers between systems, enables data from all links to interact in real time, provides strong support for data analysis and optimized decision-making, and helps improve the coordination and operational efficiency of the entire supply chain.

[0055] In summary, this embodiment uses the data acquisition and integration module 10 to comprehensively acquire data from all links of the power supply chain and effectively integrate them, providing a data basis for overall management and control. The data analysis module 20 can deeply analyze the data of each link, discover problems in a timely manner and issue warnings, which is conducive to precise management and optimization. The optimization decision module 30 uses genetic algorithms and simulated annealing algorithms to optimize the overall layout and power dispatching, respectively, and improves the allocation efficiency and utilization rate of power resources. The data interaction module 40 ensures the smooth flow and sharing of data and enhances the synergy of the supply chain. The system realizes the effective management and optimization of the power supply chain as a whole, greatly improves the utilization rate of power resources, makes the power supply more stable and efficient, and meets the society's demand for electricity.

[0056] Optionally, the data collection and integration module 10 includes: a power generation link data collection unit, a power transmission link data collection unit, a power distribution link data collection unit, a consumption link data collection unit, and a data integration unit;

[0057] The data acquisition unit of the power generation link is used to monitor the changes of the microstructure inside the power equipment through micro sensors to obtain the microstructure change data, and use the power generation state data and microstructure change data obtained by the sensor network of the power generation link as the sensor data corresponding to the power generation link;

[0058] The data collection unit for the power transmission link is used to regularly inspect the power transmission line using a high-definition camera and electromagnetic induction sensor carried by a drone, and collect line appearance data and electromagnetic field strength data as sensor data corresponding to the power transmission link;

[0059] The data acquisition unit of the power distribution link is used to record power consumption data and power quality data through smart meters, and to communicate with adjacent smart meters over short distances to form a local power distribution data network, and to obtain power consumption data and power quality data from the power distribution data network as sensor data corresponding to the power distribution link;

[0060] The consumption link data collection unit is used for the home appliance data collector based on the Internet of Things to collect data from various brands and models of home appliances, and obtain the operating status data and energy consumption data as the sensor data corresponding to the consumption link;

[0061] The data integration unit is used to integrate and process the sensor data corresponding to all links in a preset data format to obtain the supply chain data corresponding to each link.

[0062] Optionally, the data analysis module 20 includes: a power generation link analysis unit, a power transmission link analysis unit, a power distribution link analysis unit, a consumption link analysis unit, and a data early warning unit;

[0063] The power generation link analysis unit is used to train the deep learning algorithm according to the historical operation data of the power generation equipment to obtain the equipment health model, and to predict the equipment health of the supply chain data of the power generation link based on the equipment health model to obtain the health mode. When the health mode is an abnormal mode, the fault type and severity are determined based on the supply chain data of the power generation link as the analysis result of the power generation link;

[0064] The power transmission link analysis unit is used to process the supply chain data of the power transmission link using a cluster analysis algorithm to obtain different risk level areas as the analysis results of the power transmission link;

[0065] The power distribution link analysis unit is used to perform power distribution scenario analysis on the supply chain data of the power distribution link based on the power distribution analysis model to obtain the analysis results of the power distribution link;

[0066] The consumption link analysis unit is used to analyze the supply chain data of the consumption link by using the association rule mining algorithm, obtain the usage association pattern, and obtain the analysis result of the consumption link;

[0067] The data early warning unit is used to monitor the analysis results through the real-time data processing platform and send early warning signals when abnormal fluctuations occur in the data.

[0068] Optionally, the optimization decision module 30 includes: a decision optimization implementation unit, a scheduling plan unit, and a result output unit;

[0069] Implement a decision optimization unit to optimize the overall layout of the supply chain data and analysis results corresponding to each link according to the genetic algorithm to obtain a layout structure optimization plan;

[0070] The dispatch planning unit is used to optimize the power dispatching based on the supply chain data and analysis results corresponding to each link according to the simulated annealing algorithm to obtain the power dispatching plan;

[0071] The result output unit is used to output the layout structure optimization plan and power dispatch plan.

[0072] Optionally, the data interaction module 40 is specifically used to build a compatible interface and a middleware platform based on the software information and hardware information of the power equipment, and interact with the power system through the compatible interface and the middleware platform to obtain sensor data from the sensor network.

[0073] Optionally, also include:

[0074] The decision support module is used to build a decision support interface and display the analysis results, layout structure optimization plan, and power dispatch plan through the decision support interface.

[0075] Optionally, also include:

[0076] The external system interaction module is used to acquire data from the weather forecast system and the energy market transaction system respectively through a preset network link, obtain meteorological data and energy market transaction data, and add the meteorological data and energy market transaction data to the supply chain data.

[0077] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0078] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0079] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0080] The above is a detailed introduction to a data analysis and optimization system for a power supply chain provided by the present application. This article uses specific examples to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of the present application.

Claims

1. A data analysis and optimization system for a power supply chain, characterized in that: include: The data acquisition and integration module is used to acquire data from each link of the power supply through the sensor network, obtain sensor data corresponding to each link, and integrate the sensor data corresponding to all links to obtain supply chain data corresponding to each link; wherein the sensor network includes: a sensor network for the power generation link, a sensor network for the power transmission link, a sensor network for the power distribution link, and a sensor network for the consumption link; A data analysis module, used to analyze and process the supply chain data corresponding to each link based on the data characteristics of each link, obtain analysis results, and perform early warning operations based on the analysis results; An optimization decision module is used to optimize the overall layout of the supply chain data and analysis results corresponding to each link according to a genetic algorithm to obtain a layout structure optimization plan, and to optimize the power dispatching of the supply chain data and analysis results corresponding to each link according to a simulated annealing algorithm to obtain a power dispatching plan; and output the layout structure optimization plan and the power dispatching plan; The data interaction module is used to interact with the power system through a compatible interface and a middleware platform so as to obtain the sensor data from the sensor network.

2. The data analysis and optimization system according to claim 1, characterized in that: The data collection and integration module includes: a power generation link data collection unit, a power transmission link data collection unit, a power distribution link data collection unit, a consumption link data collection unit, and a data integration unit; The power generation link data acquisition unit is used to monitor the changes in the microstructure inside the power equipment through micro sensors to obtain microstructure change data, and use the power generation state data and the microstructure change data obtained by the power generation link sensor network as the sensor data corresponding to the power generation link; The power transmission link data acquisition unit is used to use the high-definition camera and electromagnetic induction sensor carried by the drone to regularly inspect the power transmission line and collect line appearance data and electromagnetic field strength data as sensor data corresponding to the power transmission link; The power distribution link data acquisition unit is used to record power consumption data and power quality data through smart meters, and to perform short-distance data communication with adjacent smart meters to form a local power distribution data network, and to obtain power consumption data and power quality data from the power distribution data network as sensor data corresponding to the power distribution link; The consumption link data collection unit is used as a home appliance data collector based on the Internet of Things to collect data from home appliances of various brands and models, and obtain operating status data and energy consumption data as sensor data corresponding to the consumption link; The data integration unit is used to integrate the sensor data corresponding to all links in a preset data format to obtain the supply chain data corresponding to each link.

3. The data analysis and optimization system according to claim 2, characterized in that: The data analysis module includes: a power generation link analysis unit, a power transmission link analysis unit, a power distribution link analysis unit, a consumption link analysis unit, and a data early warning unit; The power generation link analysis unit is used to train the deep learning algorithm according to the historical operation data of the power generation equipment to obtain the equipment health model, and to perform equipment health prediction on the supply chain data of the power generation link based on the equipment health model to obtain a health mode. When the health mode is an abnormal mode, the fault type and severity are determined based on the supply chain data of the power generation link as the analysis result of the power generation link; The power transmission link analysis unit is used to process the supply chain data of the power transmission link using a cluster analysis algorithm to obtain different risk level areas as the analysis results of the power transmission link; The power distribution link analysis unit is used to perform power distribution scenario analysis on the supply chain data of the power distribution link based on the power distribution analysis model to obtain the analysis result of the power distribution link; The consumption link analysis unit is used to analyze the supply chain data of the consumption link by using an association rule mining algorithm to obtain a usage association pattern and obtain an analysis result of the consumption link; The data early warning unit is used to monitor the analysis results through a real-time data processing platform and send an early warning signal when abnormal fluctuations occur in the data.

4. The data analysis and optimization system according to claim 3, characterized in that: The optimization decision module includes: a decision optimization implementation unit, a scheduling plan unit, and a result output unit; The implementation decision optimization unit is used to optimize the overall layout of the supply chain data and analysis results corresponding to each link according to the genetic algorithm to obtain a layout structure optimization plan; The dispatch planning unit is used to optimize the power dispatching for the supply chain data and analysis results corresponding to each link according to the simulated annealing algorithm to obtain a power dispatching plan; The result output unit is used to output the layout structure optimization plan and the power dispatching plan.

5. The data analysis and optimization system according to claim 4, characterized in that: The data interaction module is specifically used to construct the compatible interface and the middleware platform based on the software information and hardware information of the power equipment, and interact with the power system through the compatible interface and the middleware platform to obtain the sensor data from the sensor network.

6. The data analysis and optimization system according to claim 5, characterized in that: Also includes: The decision support module is used to construct a decision support interface, and to display the analysis results, the layout structure optimization plan, and the power dispatch plan through the decision support interface.

7. The data analysis and optimization system according to claim 6, characterized in that: Also includes: The external system interaction module is used to acquire data from the weather forecast system and the energy market transaction system respectively through a preset network link, obtain meteorological data and energy market transaction data, and add the meteorological data and the energy market transaction data to the supply chain data.

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