Power supply area resource allocation system based on electric power data

Abstract

The invention discloses a power supply area resource allocation system based on power data, which comprises a data acquisition module, a data processing module, a resource allocation module, a monitoring and early warning module and a user interaction module, and is characterized in that the data acquisition module is used for acquiring power data in a power supply area in real time, including parameters such as power consumption, voltage, current and power factor; the invention relates to the technical field of electric power engineering. According to the power supply area resource allocation system based on the power data, the power data in the power supply area are collected and analyzed in real time, the system can accurately master the power demand trend and the load characteristics, so that a more reasonable power resource allocation strategy is formulated, the power loss and waste can be effectively reduced, and the resource allocation efficiency is improved. And sufficient power supply can be ensured in the peak period of power demand, and the overall efficiency and stability of power supply are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power engineering, and in particular to a power supply area resource allocation system based on electric power data. Background Art

[0002] Electricity resources are one of the indispensable and important resources in modern society. Its stable supply is crucial to economic development, social stability and the normal operation of people's lives. However, with the acceleration of urbanization and the continuous growth of electricity demand, power supply areas are facing more and more challenges. Especially during some peak periods of electricity demand, how to reasonably allocate and dispatch electricity resources to ensure the stability and reliability of power supply has become an urgent problem to be solved.

[0003] The traditional way of allocating resources in power supply areas mainly relies on manual judgment and dispatching experience. This method is not only inefficient, but also difficult to cope with the complex and changeable changes in power demand. With the continuous development of information technology, especially the widespread application of technologies such as big data, cloud computing and the Internet of Things, new solutions have been provided for the allocation of resources in power supply areas. By collecting and analyzing power data, real-time monitoring and intelligent dispatching of power resources can be achieved, thereby improving the stability and reliability of power supply.

[0004] At present, although some power supply regional resource allocation systems based on power data have been applied, there are still some problems. For example, the data collection scope of some systems is limited and cannot fully reflect the power demand situation in the power supply area; some systems have insufficient data processing and analysis capabilities, making it difficult to achieve accurate scheduling of power resources; and some systems are not highly intelligent and cannot automatically adapt to changes in power demand. In response to this, we propose a power supply regional resource allocation system based on power data to solve the above problems. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a power supply area resource allocation system based on power data, which solves the problems raised in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a power supply area resource allocation system based on power data, including a data acquisition module, a data processing module, a resource allocation module, a monitoring and early warning module, and a user interaction module. The data acquisition module is used to collect power data in the power supply area in real time, including parameters such as power consumption, voltage, current, and power factor. The data processing module is used to receive and process the power data transmitted by the data acquisition module, and perform data analysis, mining and prediction to obtain the power demand trend, load characteristics and abnormal information in the power supply area. The resource allocation module formulates a power resource allocation strategy based on the analysis results of the data processing module, including power distribution, scheduling and optimization, to ensure the stability and reliability of power supply. The monitoring and early warning module is used to monitor the power resource allocation situation in the power supply area in real time, and issue an early warning signal when an abnormality occurs. The early warning signal includes the early warning level, early warning content, and early warning time key information. The user interaction module is used to provide a user interface and an intelligent voice assistant function, which is used to display power data, allocation strategies, early warning information, and receive user operation instructions and query requests.

[0007] Preferably, the output end of the data acquisition module is electrically connected to the input end of the data processing module, the output end of the data processing module is electrically connected to the input end of the resource allocation module, the output end of the resource allocation module is electrically connected to the input end of the monitoring and early warning module, and the output end of the monitoring and early warning module is electrically connected to the input end of the user interaction module.

[0008] Preferably, the data acquisition module includes a smart meter unit, a sensor network unit, and a data receiving and storage unit; the data processing module includes a data preprocessing unit, a data analysis unit, and a data visualization unit; the resource allocation module includes a power resource assessment unit, an allocation strategy formulation unit, and an execution and monitoring unit; the monitoring and early warning module includes a real-time monitoring unit, an early warning signal generation unit, and an early warning information release unit; and the user interaction module includes a user interface design unit, an instruction receiving and processing unit, and an information feedback unit.

[0009] Preferably, the data processing module includes time series analysis, cluster analysis, and regression analysis, and conducts in-depth mining and analysis of power data to obtain key information on power demand trends, peak and valley periods, and load characteristics within the power supply area.

[0010] Preferably, the resource allocation module can automatically adjust the allocation strategy of power resources according to changes in power demand, including allocating power resources from other power supply areas, starting backup power supplies, adjusting power output or prices, etc.

[0011] Preferably, the monitoring and early warning module can monitor the allocation of power resources in the power supply area in real time, and send out early warning signals in the event of abnormal power data, power grid failure or insufficient power supply, to remind users to take timely countermeasures.

[0012] Preferably, the user interaction module provides a concise and clear user interface, which facilitates users to understand the power data, deployment strategies, and early warning information within the power supply area, and realize voice interaction with the system through the intelligent voice assistant function.

[0013] Preferably, the system can also be integrated and linked with other power systems, such as coordinated scheduling and optimization with distributed energy systems and energy storage systems, to achieve more efficient and sustainable power supply.

[0014] Beneficial Effects

[0015] The present invention provides a power supply area resource allocation system based on power data. Compared with the prior art, it has the following beneficial effects:

[0016] (1) By collecting and analyzing power data in the power supply area in real time, the system can accurately grasp the power demand trend and load characteristics, and thus formulate a more reasonable power resource allocation strategy, which can not only effectively reduce power loss and waste, but also ensure sufficient power supply during peak power demand periods, thereby improving the overall efficiency and stability of power supply.

[0017] (2) The system’s built-in monitoring and early warning module can monitor the allocation of power resources in real time and issue early warning signals in a timely manner when an abnormality occurs. This real-time monitoring and early warning mechanism helps to promptly discover and resolve potential problems in power grid operation, reduce the number and duration of power outages, and improve users’ satisfaction and trust in power supply.

[0018] (3) By introducing advanced technologies such as the Internet of Things, data analysis and intelligent scheduling algorithms, the system realizes the intelligent collection, processing and analysis of power data, as well as the intelligent allocation and monitoring of power resources. This not only improves the intelligence level of the power system, but also provides strong support for energy conservation, emission reduction and green development in the power industry, and helps promote the sustainable development of the power industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a system block diagram of the present invention;

[0020] Figure 2 It is a schematic diagram of a data acquisition module of the present invention;

[0021] Figure 3 It is a schematic diagram of a data processing module of the present invention;

[0022] Figure 4It is a schematic diagram of a resource allocation module of the present invention;

[0023] Figure 5 This is a schematic diagram of the monitoring and early warning module of the present invention;

[0024] Figure 6 Schematic diagram of the user interaction module of the present invention.

[0025] In the figure: 01, data acquisition module; 02, data processing module; 03, resource allocation module; 04, monitoring and early warning module; 05, user interaction module; 011, smart meter unit; 012, sensor network unit; 013, data receiving and storage unit; 021, data preprocessing unit; 022, data analysis unit; 023, data visualization unit; 031, power resource evaluation unit; 032, allocation strategy formulation unit; 033, execution and monitoring unit; 041, real-time monitoring unit; 042, early warning signal generation unit; 043, early warning information release unit; 051, user interface design unit; 052, instruction receiving and processing unit; 053, information feedback unit. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] The present invention provides three technical solutions, including the following embodiments:

[0028] Example 1

[0029] See also Figure 1The power supply area resource allocation system based on power data includes a data acquisition module 01, a data processing module 02, a resource allocation module 03, a monitoring and early warning module 04, and a user interaction module 05. The data acquisition module 01 is used to collect power data in the power supply area in real time, including parameters such as power consumption, voltage, current, and power factor. The data processing module 02 is used to receive and process the power data transmitted by the data acquisition module, and perform data analysis, mining, and prediction to obtain the power demand trend, load characteristics, and abnormal information in the power supply area. The resource allocation module 03 formulates a power resource allocation strategy based on the analysis results of the data processing module, including power distribution, scheduling, and optimization, to ensure the stability and reliability of power supply. The monitoring and early warning module 04 is used to monitor the power resource allocation in the power supply area in real time, and issue an early warning signal when an abnormality occurs. The early warning signal includes key information such as the early warning level, early warning content, and early warning time. The user interaction module 05 is used to provide a user interface and an intelligent voice assistant function, which is used to display power data, allocation strategies, early warning information, and receive user operation instructions and query requests.

[0030] The output end of the data acquisition module 01 is electrically connected to the input end of the data processing module 02, the output end of the data processing module 02 is electrically connected to the input end of the resource allocation module 03, the output end of the resource allocation module 03 is electrically connected to the input end of the monitoring and early warning module 04, and the output end of the monitoring and early warning module 04 is electrically connected to the input end of the user interaction module 05.

[0031] The power supply area resource allocation system based on power data of the present invention can be applied to power supply areas such as urban power grids, industrial parks, and large residential areas. The following is an example of an urban power grid:

[0032] First, smart meters and sensor networks are deployed in the city power grid to collect power data. Smart meters are installed at the power entrance of each power user or household to monitor power consumption and power parameters in real time. Sensor networks are distributed in key locations of the power grid, such as substations and transmission lines, to monitor the operating status of the power grid and power parameters.

[0033] Then, the collected power data is transmitted to the data processing module 02 for processing and analysis. The data processing module 02 uses advanced data analysis techniques, such as time series analysis, cluster analysis, regression analysis, etc., to conduct in-depth mining and analysis of power data to obtain key information such as power demand trends, peak and valley periods, and load characteristics of the urban power grid.

[0034] Then, according to the analysis results, the resource allocation module 03 formulates a power resource allocation strategy. The allocation strategy includes specific measures such as the allocation, scheduling and optimization of power resources, aiming to ensure the stability and reliability of the power supply of the urban power grid. For example, during the peak period of power demand, the demand can be met by allocating power resources from other power supply areas or starting backup power supplies; during the trough period of power demand, resources can be saved by reducing power output or adjusting power prices.

[0035] At the same time, the monitoring and early warning module 04 monitors the power resource allocation of the urban power grid in real time and issues an early warning signal when an abnormality occurs. The early warning signal includes key information such as the early warning level, early warning content, and early warning time, which can help users understand the abnormal situation of the power grid in a timely manner and take corresponding countermeasures.

[0036] Finally, the user interaction module 05 provides a user interface and intelligent voice assistant functions to facilitate users to understand the operation status and deployment results of the urban power grid. Users can query the real-time data, historical data, deployment strategy and other information of the power grid through the user interface; at the same time, they can also interact with the system through the intelligent voice assistant function to query and understand relevant information.

[0037] Example 2

[0038] Based on Example 1, see Figure 2-Figure 6As shown, the data acquisition module 01 includes a smart meter unit 011, a sensor network unit 012, and a data receiving and storage unit 013. The smart meter is one of the core devices of the data acquisition module, which can monitor the power usage in the power supply area in real time, including parameters such as voltage, current, and power factor. The smart meter transmits the collected data to other parts of the data acquisition module through wireless communication or wired communication. The sensor network unit is composed of multiple sensors, which are distributed in key positions in the power supply area and are used to monitor the operating status of power equipment and the parameters of power lines. The sensor network unit transmits the collected data to the data acquisition module through wireless communication. The data receiving and storage unit is responsible for receiving the data transmitted by the smart meter and the sensor network unit, and storing it in the local database or cloud storage. At the same time, the data receiving and storage unit also has data cleaning and preprocessing functions, which can remove useless information such as duplicate data and abnormal data, and improve the efficiency and accuracy of subsequent data processing. The data processing module 02 includes a data preprocessing unit 021, a data analysis unit 022, and a data Visualization unit 023, data preprocessing unit 021 is responsible for further processing and cleaning the received power data, including noise removal, missing value filling, standardization and other steps. These processing steps can ensure the accuracy and consistency of the data and provide a reliable basis for subsequent analysis and modeling. Data analysis unit 022 uses advanced data analysis techniques, such as time series analysis, cluster analysis, regression analysis, etc., to conduct in-depth mining and analysis of the processed power data. Through data analysis, key information such as power demand trends, peak and valley periods, and load characteristics in the power supply area can be obtained, providing a scientific basis for resource allocation. Data visualization unit 023 displays the analysis results in the form of charts, curves, maps, etc., so that users can intuitively understand the power demand situation in the power supply area. At the same time, data visualization unit 023 can display the analysis results in the form of charts, curves, maps, etc., so that users can intuitively understand the power demand situation in the power supply area.023 also supports user-defined query and filtering functions, and can provide personalized data display services according to user needs. The resource allocation module 03 includes a power resource evaluation unit 031, a deployment strategy formulation unit 032, and an execution and monitoring unit 033. The power resource evaluation unit 031 evaluates the power resources in the power supply area according to the power demand provided by the data analysis unit. The evaluation content includes the total amount, distribution, and availability of power resources, etc., to provide a basis for subsequent deployment decisions. The deployment strategy formulation unit 032 formulates a power resource deployment strategy based on the power resource evaluation results and the actual situation in the power supply area. The deployment strategy includes the allocation, The specific measures such as dispatching and optimization are aimed at ensuring the stability and reliability of power supply. The execution and monitoring unit 033 is responsible for executing the allocation strategy and monitoring the use of power resources in the allocation process in real time. At the same time, the execution and monitoring unit also has a feedback mechanism, which can adjust the allocation strategy in time according to the monitoring results to ensure that the allocation effect reaches the expected goal. The monitoring and early warning module 04 includes a real-time monitoring unit 041, an early warning signal generation unit 042, and an early warning information release unit 043. The real-time monitoring unit 041 collects and analyzes power data to understand the power resource allocation situation in the power supply area in real time. At the same time, the real-time monitoring unit 041 also has data analysis and prediction functions, which can Predict future power demand trends and possible problems. The early warning signal generation unit 042 generates an early warning signal based on the data and analysis results provided by the real-time monitoring unit. The early warning signal includes key information such as the warning level, warning content, and warning time, which can help users to promptly understand abnormal conditions in the power supply area and take corresponding countermeasures. The early warning information release unit 043 is responsible for releasing the early warning signal to relevant personnel and equipment. The release methods include text messages, emails, telephone calls, etc., which can ensure that the early warning information is timely and accurately conveyed to relevant personnel and equipment. The user interaction module 05 includes a user interface design unit 051, an instruction receiving and processing unit 052, and a signal processing unit 053. The information feedback unit 053, the user interface design unit 051 is responsible for designing the layout, style and function of the user interface. The user interface should be concise, easy to operate, and convenient for users to understand the operation status and deployment results of the system. The instruction receiving and processing unit 052 is responsible for receiving the instructions and information input by the user through the user interface and processing them. The processing results include executing the user's instructions, updating the system status, returning the query results, etc. The information feedback unit 053 is responsible for feeding back the system's operation status and deployment results to the user. The feedback methods include displaying the results, issuing prompt sounds, popping up prompt boxes, etc., which can ensure that the user can understand the system's operation status and deployment results in a timely manner.

[0039] Example 3

[0040] Based on Example 2, see Figure 1-Figure 6As shown, the data processing module 02 includes time series analysis, cluster analysis, and regression analysis, which conducts in-depth mining and analysis of power data to obtain key information on power demand trends, peak and valley periods, and load characteristics within the power supply area.

[0041] The resource allocation module 03 can automatically adjust the allocation strategy of power resources according to changes in power demand, including allocating power resources from other power supply areas, starting backup power supplies, adjusting power output or prices, etc.

[0042] The monitoring and early warning module 04 can monitor the power resource allocation in the power supply area in real time, and send out early warning signals in the event of abnormal power data, power grid failure or insufficient power supply, to remind users to take timely response measures.

[0043] The user interaction module 05 provides a concise and clear user interface, which makes it easy for users to understand the power data, deployment strategies, and early warning information in the power supply area, and realize voice interaction with the system through the intelligent voice assistant function.

[0044] The system can also be integrated and linked with other power systems, such as coordinated scheduling and optimization with distributed energy systems and energy storage systems to achieve more efficient and sustainable power supply.

[0045] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0046] The above embodiments of the invention are described in detail, but the contents are only preferred embodiments of the invention and cannot be considered to limit the scope of the invention. All equivalent changes and improvements made within the scope of the invention should still fall within the scope of the invention.

Claims

1. A power supply area resource allocation system based on power data, characterized by: The invention comprises a data acquisition module (01), a data processing module (02), a resource allocation module (03), a monitoring and early warning module (04), and a user interaction module (05). The data acquisition module (01) is used to collect power data in the power supply area in real time, including parameters such as power consumption, voltage, current, power factor, etc. The data processing module (02) is used to receive and process the power data transmitted by the data acquisition module, and perform data analysis, mining and prediction to obtain the power demand trend, load characteristics and abnormal information in the power supply area. The resource allocation module (03) formulates a power resource allocation strategy according to the analysis result of the data processing module, including power distribution, scheduling and optimization, to ensure the stability and reliability of power supply. The monitoring and early warning module (04) is used to monitor the power resource allocation situation in the power supply area in real time, and issue an early warning signal when an abnormality occurs. The early warning signal includes key information such as early warning level, early warning content and early warning time. The user interaction module (05) is used to provide a user interface and an intelligent voice assistant function, and is used to display power data, allocation strategy, early warning information, and receive user operation instructions and query requests.

2. The power supply area resource allocation system based on power data according to claim 1 is characterized in that: The output end of the data acquisition module (01) is electrically connected to the input end of the data processing module (02), the output end of the data processing module (02) is electrically connected to the input end of the resource allocation module (03), the output end of the resource allocation module (03) is electrically connected to the input end of the monitoring and early warning module (04), and the output end of the monitoring and early warning module (04) is electrically connected to the input end of the user interaction module (05).

3. The power supply area resource allocation system based on power data according to claim 1 is characterized in that: The data acquisition module (01) comprises a smart meter unit (011), a sensor network unit (012), and a data receiving and storage unit (013); the data processing module (02) comprises a data preprocessing unit (021), a data analysis unit (022), and a data visualization unit (023); the resource allocation module (03) comprises an electric power resource evaluation unit (031), an allocation strategy formulation unit (032), and an execution and monitoring unit (033); the monitoring and early warning module (04) comprises a real-time monitoring unit (041), an early warning signal generation unit (042), and an early warning information release unit (043); and the user interaction module (05) comprises a user interface design unit (051), an instruction receiving and processing unit (052), and an information feedback unit (053).

4. The power supply area resource allocation system based on power data according to claim 1, characterized in that: The data processing module (02) includes time series analysis, cluster analysis, and regression analysis, and conducts in-depth mining and analysis of power data to obtain key information on power demand trends, peak and valley periods, and load characteristics within the power supply area.

5. The power supply area resource allocation system based on power data according to claim 1 is characterized in that: The resource allocation module (03) can automatically adjust the allocation strategy of power resources according to changes in power demand, including allocating power resources from other power supply areas, starting backup power supplies, adjusting power output or price, etc.

6. The power supply area resource allocation system based on power data according to claim 1, characterized in that: The monitoring and early warning module (04) is capable of real-time monitoring of the allocation of power resources in the power supply area, and issuing early warning signals in the event of abnormal power data, power grid failure or power supply shortage, to remind users to take timely countermeasures.

7. The power supply area resource allocation system based on power data according to claim 1, characterized in that: The user interaction module (05) provides a concise and clear user interface, which facilitates users to understand the power data, deployment strategies, and early warning information in the power supply area, and realizes voice interaction with the system through the intelligent voice assistant function.

8. The power supply area resource allocation system based on power data according to claim 1, characterized in that: The system can also be integrated and linked with other power systems, such as coordinated scheduling and optimization with distributed energy systems and energy storage systems to achieve more efficient and sustainable power supply.

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