Power grid information analysis system and method based on memory calculation

Abstract

The invention discloses a power grid information analysis system and method based on memory calculation, and relates to the technical field of power grid data analysis and processing. Comprising an endpoint data collection module, a data transmission module, a memory database, a power grid load monitoring module, a memory data calculation module, an energy analysis module, a power supply capability prediction module, a power dispatching control module and an analysis display module. According to the invention, real-time processing and modeling analysis can be rapidly carried out on user data, so that the precision and efficiency of energy management are improved; faults at the end point of the power grid can be found in time, so that the faults are maintained, the power utilization safety of the power grid is guaranteed, meanwhile, the calculation amount of an end point memory database can be reduced, and the system operation stability is guaranteed; stable operation of the power grid is ensured, the situation of power shortage in a certain place is avoided, and stable operation of the power grid is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid data analysis and processing, and in particular to a power grid information analysis system and method based on memory computing. Background Art

[0002] With the continuous advancement of intelligent technology and the widespread application of the Internet, the era of the Internet of Everything has quietly arrived; this change has promoted the digital transformation of all walks of life, especially in the power industry, where the construction of smart grids has gradually become an important direction for future power systems; with the help of advanced communication technology, sensor technology, data analysis technology and artificial intelligence technology, smart grids can monitor the operating status of power systems in real time and automatically adjust power loads, thereby improving the stability and reliability of power grids; at the same time, the widespread application of smart meters and smart power consumption equipment has made the collection and transmission of power consumption data more efficient and accurate, making it easier for power companies to understand the power consumption in various regions in a timely manner and provide a scientific basis for power dispatch and management; in addition, with the large-scale access of renewable energy to the power grid, the dispatch of power systems has become more complex and dynamic. How to use intelligent means to achieve the optimal configuration of power resources and ensure the reliable operation of the power grid has become a hot topic in today's power system research.

[0003] However, although smart grids have played an important role in improving the efficiency and reliability of power systems, existing methods for processing and analyzing electricity consumption data are still insufficient and cannot meet the growing electricity demand and complex grid dispatching requirements. First, with the continuous expansion of the power system scale and the increase in power load, traditional data processing methods can no longer meet the needs of data processing. Second, due to the uneven temporal and spatial scale of electricity consumption, if the subsequent electricity consumption scale cannot be accurately judged and electricity cannot be dispatched in a timely manner, power shortages in a certain area may occur. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to provide a power grid information analysis system based on memory computing to solve the problem that traditional data processing methods cannot meet the needs of data processing. Due to the uneven temporal and spatial distribution of electricity consumption, the existing technology cannot accurately determine the subsequent electricity consumption scale problem.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In the first aspect, an embodiment of the present invention provides a power grid information analysis system based on memory computing, which includes an endpoint data collection module, a data transmission module, a memory database, a power grid load monitoring module, a memory data calculation module, an energy analysis module, a power supply capacity prediction module, a power dispatch control module and an analysis and display module; the endpoint data collection module is used to obtain raw data during the operation of the power grid; the data transmission module is used to process the raw data and transmit it to the memory database; the memory database is used to store the processed data; the power grid load monitoring module is used to monitor the operation status of the power grid; the memory data calculation module is used to read data from the memory database and analyze it; the energy analysis module is used to generate a user demand prediction result based on the analysis result of the memory data calculation module and transmit it to the power supply capacity prediction module; the power supply capacity prediction module is used to predict the future power supply capacity based on the user demand prediction result, and transmit the power supply capacity prediction result to the power dispatch control module; the power dispatch control module is used to formulate a power dispatch plan according to the power supply capacity prediction result, and transmit the power dispatch plan and the power supply capacity prediction result to the analysis and display module; the analysis and display module is used to display the power dispatch plan and the power supply capacity prediction result.

[0008] As a preferred solution of the power grid information analysis system based on memory computing described in the present invention, wherein: the output end of the endpoint data collection module is connected to the data transmission module, the output end of the data transmission module is connected to the memory database, the output end of the memory database is connected to the memory data computing module, the output end of the memory data computing module is connected to the energy analysis module, the output end of the energy analysis module is connected to the power supply capacity prediction module, the output end of the power supply capacity prediction module is provided with a power dispatching control module, the output end of the power dispatching control module is provided with an analysis and display module, the output end of the power supply capacity prediction module is connected to the analysis and display module, the output end of the memory database is connected to the power grid load monitoring module, the power grid load monitoring module and the memory data computing module are connected in parallel, and the output end of the power grid load monitoring module is connected to the input end of the endpoint data collection module.

[0009] As a preferred solution of the power grid information analysis system based on memory computing described in the present invention, wherein: the data transmission module includes an endpoint data transmission module, a node data processing module and a node data transmission module; the output end of the endpoint data transmission module is connected to the node data processing module, the output end of the node data processing module is connected to the node data transmission module, and the output end of the node data transmission module is connected to the memory database; the data transmission module also includes a node abnormal data filtering module and an abnormal data analysis and processing module; the input end of the node abnormal data filtering module is connected to the output end of the node data processing module, the output end of the node abnormal data filtering module is connected to the node data transmission module, and the output end of the node abnormal data filtering module is connected to the abnormal data analysis and processing module; the output end of the abnormal data analysis and processing module is connected to the memory data computing module, and the output end of the memory data computing module is connected to the input end of the memory database.

[0010] As a preferred solution of the power grid information analysis system based on memory computing described in the present invention, wherein: the energy analysis module includes user actual data, user usage evaluation, customer payment laziness analysis and cost operation analysis; a data analysis model is generated based on the user actual data, the data analysis model is analyzed through the memory computing mode, and the user usage evaluation is generated according to the analysis results.

[0011] As a preferred solution of the power grid information analysis system based on memory computing of the present invention, the analysis result based on the memory data computing module generates the user demand estimation result, which includes the following steps: the data in the user usage evaluation is analyzed to generate the customer payment indolence analysis, and the average value of the customer's payment cycle value in a fixed period of time is calculated based on the statistical data. The specific formula is as follows:

[0012]

[0013] Among them, K i is the average payment period value; N i Pd is the total number of payment records of customer i during the statistical period; ij The maximum number of days allowed for payment not to be overdue; ij is the number of days of delayed payment; according to the analysis of customer payment delay, the cost operation analysis is obtained, and the average value of a single payment cycle of a customer within a year is calculated. The specific formula is as follows:

[0014]

[0015] Among them, S is the average value of a single payment; T is the number of fixed time periods of a single payment within a year; the final generated cost operation analysis is displayed on the analysis display module.

[0016] As a preferred solution of the power grid information analysis system based on memory computing described in the present invention, wherein: the energy analysis module also includes energy price data, meteorological data, user historical data and user demand forecast; the data analysis model is used to analyze the user's actual data with past energy price data and meteorological data, and determine the relationship between the energy price data, meteorological data and the user's actual data, so as to generate a user demand forecast, and transmit the user demand forecast to the power supply capacity prediction module.

[0017] As a preferred solution of the power grid information analysis system based on memory computing described in the present invention, wherein: the power grid load monitoring module includes a power grid operation monitoring module, a signal transmission module, a data comparison module, a pipe loss repair module and a data update module; the output end of the power grid operation monitoring module is connected to the signal transmission module, the output end of the signal transmission module is connected to the data comparison module, the output end of the data comparison module is connected to the pipe loss repair module, and the output end of the pipe loss repair module is connected to the data update module; the output end of the data update module is connected to the input end of the power grid monitoring module, the output end of the signal transmission module is connected to the input end of the memory database, the memory database and the data comparison module are connected in parallel, and the output end of the memory database is connected to the input end of the data comparison module.

[0018] On the second aspect, in order to further solve the security problems existing in the analysis and processing of power grid data, the embodiments of the present invention provide a power grid information analysis method based on memory computing, which includes: acquiring the original data generated during the operation of the power grid; performing preliminary processing, anomaly detection and in-depth analysis on the original data to obtain processed data; performing in-depth calculation and analysis on the processed data to obtain analysis results; generating user demand estimation results based on the analysis results; predicting future power supply capacity based on the user demand estimation results to obtain power supply capacity prediction results; formulating a power dispatching plan based on the power supply capacity prediction results, and displaying the power supply capacity prediction results and the power dispatching plan; continuously monitoring the operation status of the power grid, obtaining abnormal judgment results and performing repairs.

[0019] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the power grid information analysis system based on memory computing as described in the first aspect of the present invention is implemented.

[0020] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the power grid information analysis system based on memory computing as described in the first aspect of the present invention is implemented.

[0021] The beneficial effects of the present invention are as follows: the present invention utilizes memory computing to directly store data in a memory database for processing. Compared with traditional disk storage, the present invention has the advantages of fast access speed, high read and write efficiency, and strong concurrency performance. It can quickly process and model user data in real time, thereby improving the accuracy and efficiency of energy management. Based on a combination of node processing and endpoint processing, preliminary analysis and processing of endpoint data is performed at the node to integrate the data, and the integrated data is sent to the memory database for final analysis. It can timely discover faults at the power grid endpoints, thereby repairing the faulty parts to ensure the power grid's electricity safety, and at the same time reduce the amount of calculation of the endpoint memory database to ensure the stability of the system operation. By analyzing and processing energy price data, meteorological data, and user historical data, subsequent user demand estimates are obtained, and the power of the entire power grid is controlled, and the power is regulated and dispatched to ensure that the power grid can operate stably, avoid power shortages in certain places, and ensure the stable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0023] Figure 1 This is a flow chart of the system of the present invention in Example 1.

[0024] Figure 2 This is a flow chart of the data transmission module of the present invention in Example 1.

[0025] Figure 3 Schematic diagram of the power grid load monitoring module of the present invention in Example 1.

[0026] Figure 4 This is a flow chart of the energy analysis module of the present invention in Example 1.

[0027] Figure 5 This is a schematic diagram of the structure of the computer device in Example 3. DETAILED DESCRIPTION

[0028] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0029] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0030] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0031] Example 1

[0032] Reference Figure 1 to Figure 4 , which is the first embodiment of the present invention, and provides a power grid information analysis system based on memory computing, including:

[0033] Endpoint data collection module, data transmission module, memory database, power grid load monitoring module, memory data calculation module, energy analysis module, power supply capacity prediction module, power dispatching control module and analysis and display module, wherein the system flow chart of the present invention is as follows Figure 1 shown.

[0034] Preferably, the endpoint data collection module is used to obtain raw data during the operation of the power grid.

[0035] Specifically, the output end of the endpoint data collection module is connected to the data transmission module, the output end of the data transmission module is connected to the memory database, the output end of the memory database is connected to the memory data calculation module, the output end of the memory data calculation module is connected to the energy analysis module, the output end of the energy analysis module is connected to the power supply capacity prediction module, the output end of the power supply capacity prediction module is provided with a power dispatching control module, the output end of the power dispatching control module is provided with an analysis and display module, the output end of the power supply capacity prediction module is connected to the analysis and display module, the output end of the memory database is connected to the power grid load monitoring module, the power grid load monitoring module and the memory data calculation module are connected in parallel, and the output end of the power grid load monitoring module is connected to the input end of the endpoint data collection module, wherein the node collects and processes the data of the endpoint and monitors the status of the endpoint. When the data processing is completed, the processed data will be transmitted to the memory database, so as to model and analyze the data, facilitate and intuitively observe the analysis results, facilitate subsequent power dispatch in the power grid, and ensure stable operation of the power grid.

[0036] Preferably, the data transmission module is used to process the original data and transmit it to the memory database.

[0037] Specifically, Figure 2 The flowchart of the data transmission module of the present invention is shown, and the data transmission module includes an endpoint data transmission module, a node data processing module and a node data transmission module.

[0038] Specifically, the output end of the endpoint data transmission module is connected to the node data processing module, the output end of the node data processing module is connected to the node data transmission module, and the output end of the node data transmission module is connected to the memory database.

[0039] Furthermore, the data transmission module also includes a node abnormal data filtering module and an abnormal data analysis and processing module.

[0040] Specifically, the input end of the node abnormal data filtering module is connected to the output end of the node data processing module, the output end of the node abnormal data filtering module is connected to the node data transmission module, and the output end of the node abnormal data filtering module is connected to the abnormal data analysis and processing module.

[0041] The output end of the abnormal data analysis and processing module is connected to the memory data calculation module, and the output end of the memory data calculation module is connected to the input end of the memory database. The user endpoint transmits data to the node data processing module through the endpoint data transmission module. The node performs preliminary analysis and processing on the data of each endpoint, which can quickly respond to the situation of the endpoint, discover abnormal data in time, and facilitate monitoring or maintenance of abnormal endpoints. The abnormal data that cannot be processed is processed by the memory data calculation module to maintain the smooth operation of the power grid. After the node data processing module completes the data processing, it transmits the data to the memory database of the endpoint to facilitate subsequent analysis and processing.

[0042] Furthermore, by using a program to set a predetermined threshold, abnormal power consumption is screened, and the screened normal data is transmitted. The procedure is as follows:

[0043] import pandas as pd

[0044] data=pd.read_csv('electricity.csv')

[0045] data.dropna(inplace=True)

[0046] threshold=10000

[0047] abnormal_data=data[data['power consumption']>threshold]

[0048] print("Abnormal power consumption data is as follows:")

[0049] print(abnormal_data)

[0050] import matplotlib.pyplot as pltplt.figure(figsize=(10,6))

[0051] plt.plot(data['date'],data['power consumption'],label='normal power consumption')

[0052] plt.scatter(abnormal_data['date'],abnormal_data['power consumption'],color='red',label='abnormal power consumption')

[0053] plt.xlabel('date')

[0054] plt.ylabel('Electricity consumption (kWh)')

[0055] plt.title('Abnormal power consumption screening')

[0056] plt.legend()

[0057] plt.show()

[0058] Preferably, the in-memory database is used to store the processed data.

[0059] Preferably, the power grid load monitoring module is used to monitor the operating status of the power grid.

[0060] Specifically, Figure 3 The figure shows a schematic diagram of a power grid load monitoring module of the present invention, which includes a power grid operation monitoring module, a signal transmission module, a data comparison module, a pipe damage repair module and a data update module.

[0061] Furthermore, the output end of the power grid operation monitoring module is connected to the signal transmission module, the output end of the signal transmission module is connected to the data comparison module, the output end of the data comparison module is connected to the pipe damage repair module, and the output end of the pipe damage repair module is connected to the data update module.

[0062] The output end of the data update module is connected to the input end of the power grid monitoring module, the output end of the signal transmission module is connected to the input end of the memory database, the memory database and the data comparison module are connected in parallel, and the output end of the memory database is connected to the input end of the data comparison module.

[0063] It should be noted that when the endpoint data collection module collects the user's electricity consumption data, the node monitors the data through the power grid operation monitoring module. When abnormal data is found, it is compared with the previous data through the data comparison module to determine whether maintenance is needed. If maintenance is required, a signal is sent to the maintenance personnel, and they perform maintenance at the same time. After the maintenance is completed, the data is updated through the data update module to determine whether the maintenance is successful.

[0064] If maintenance is not required, the abnormal data will be sent to the memory data calculation module, so as to calculate the abnormal data and judge the situation of the abnormal data to facilitate subsequent power adjustment.

[0065] Preferably, the memory data calculation module is used to read data from the memory database and perform analysis.

[0066] Preferably, the energy analysis module is used to generate user demand estimation results based on the analysis results of the memory data calculation module and transmit them to the power supply capacity prediction module.

[0067] Specifically, Figure 4 The figure shows the flow chart of the energy analysis module of the present invention, which includes actual user data, user usage evaluation, customer payment delay analysis and cost operation analysis.

[0068] Furthermore, a data analysis model is generated based on the actual user data, the data analysis model is analyzed through an in-memory computing model, and a user usage evaluation is generated based on the analysis results.

[0069] Specifically, generating a user demand estimation result based on the analysis result of the memory data calculation module includes the following steps: after analyzing the data in the user usage evaluation, a customer payment delay analysis is generated, and the average payment cycle value of the customer in a fixed period is calculated based on the statistical data, that is, the average payment cycle value. The specific formula is as follows:

[0070]

[0071] Among them, K i is the average payment period value; N i Pd is the total number of payment records of customer i during the statistical period; ij The maximum number of days allowed for payment not to be overdue; ij The number of days for delayed payment. The smaller the value, the higher the enthusiasm for payment, the less advance payment and the lower the operating cost.

[0072] The cost operation analysis is obtained based on the analysis of the customer's payment delay, and the average value of a single payment cycle of the customer in a year, that is, the average value of a single payment, is calculated. The specific formula is as follows:

[0073]

[0074] Among them, S is the average value of a single payment; T is the number of fixed time periods of a single payment in a year, thus obtaining the average operating cost S of a single customer in each time period.

[0075] The final generated cost operation analysis is displayed on the analysis display module.

[0076] Furthermore, the energy analysis module also includes energy price data, meteorological data, user historical data and user demand forecast.

[0077] Specifically, the data analysis model is used to analyze the actual user data with past energy price data and meteorological data, determine the relationship between energy price data, meteorological data and the actual user data, thereby generating a user demand estimate, and transmitting the user demand estimate to the power supply capacity prediction module.

[0078] It should be noted that after the endpoint data transmission module transfers the actual user data to the memory database, it uses modeling analysis to derive cost operation analysis, summarize the cost of power grid operation, calculate profitability, and optimize the power grid, reduce operating costs, and increase economic benefits. At the same time, the user's actual data is analyzed and compared with energy price data, meteorological data, and user historical data to calculate subsequent user demand estimates and accurately derive the power consumption of each area. The power supply is then predicted through the power supply prediction module, making it convenient to dispatch power through the power dispatch control module, and to dispatch power from wealthy areas to power-deficient areas, thereby ensuring the smooth operation of the power grid in power-deficient areas and guaranteeing basic power supply needs.

[0079] Preferably, the power supply capacity prediction module is used to predict future power supply capacity based on the user demand estimation result, and transmit the power supply capacity prediction result to the power dispatch control module.

[0080] Preferably, the power dispatch control module is used to formulate a power dispatch plan according to the power supply capacity prediction results, and transmit the power dispatch plan and the power supply capacity prediction results to the analysis and display module.

[0081] Preferably, the analysis and display module is used to display the power dispatch plan and power supply capacity prediction results.

[0082] Preferably, the present invention performs preliminary analysis and processing on the data of the endpoint through the node, thereby greatly reducing the data calculation scale of the endpoint. Because the preliminary processing is performed through the node, it can respond quickly to the situation of the endpoint, and in the energy analysis module, memory computing can realize real-time processing and modeling of historical energy price data, meteorological data and user historical data. By using memory computing, the power supply capacity can be predicted, thereby optimizing the energy supply chain, and electricity can be transferred from wealthy areas to scarce areas to ensure the smooth operation of the power grid. At the same time, memory computing can also form user usage evaluations, derive cost operation analysis, and accurately calculate the cost of power grid operation, thereby optimizing the power grid, reducing operating costs, and increasing economic benefits.

[0083] In summary, the present invention utilizes memory computing to directly store data in a memory database for processing. Compared with traditional disk storage, the present invention has the advantages of fast access speed, high read and write efficiency, and strong concurrency performance. It can quickly process and model user data in real time, thereby improving the accuracy and efficiency of energy management. Based on the combination of node processing and endpoint processing, the endpoint data is preliminarily analyzed and processed at the node, thereby integrating the data, and sending the integrated data to the memory database for final analysis. It can timely discover the fault of the power grid endpoint, thereby repairing the faulty part to ensure the power grid's electricity safety, and at the same time reduce the amount of calculation of the endpoint memory database to ensure the stability of the system operation. By analyzing and processing energy price data, meteorological data, and user historical data, subsequent user demand estimates are obtained, and the power of the entire power grid is controlled, and the power is regulated and dispatched to ensure that the power grid can operate stably, avoid power shortages in certain places, and ensure the stable operation of the power grid.

[0084] Embodiment 2 is an embodiment of the present invention, which provides a power grid information analysis method based on memory computing, including: obtaining the original data generated during the operation of the power grid; performing preliminary processing, anomaly detection and in-depth analysis on the original data to obtain processed data; performing in-depth calculation and analysis on the processed data to obtain analysis results; generating user demand estimation results based on the analysis results; predicting future power supply capacity based on the user demand estimation results to obtain power supply capacity prediction results; formulating a power dispatching plan based on the power supply capacity prediction results, and displaying the power supply capacity prediction results and the power dispatching plan; continuously monitoring the operation status of the power grid, obtaining abnormal judgment results and performing repairs.

[0085] Embodiment 3 is an embodiment of the present invention, which is different from the previous embodiment in that:

[0086] like Figure 5As shown, if the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0087] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0088] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0089] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0090] Example 4 is an embodiment of the present invention, which provides a power grid information analysis system based on memory computing. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0091] This example uses the endpoint data collection module to obtain the data of each endpoint in the power grid. These data come from user terminal devices in different regions. The data processing module of the node is configured to pre-process the original data, and the processed data is transmitted to the memory database; the data is transmitted to the memory database through the data transmission module. For abnormal power consumption data, the program sets a threshold to filter and eliminates data that obviously does not conform to normal usage, thereby ensuring the accuracy and credibility of the data; the collected power grid data is analyzed in real time through the memory calculation module, especially in the energy analysis module, which introduces real-time energy price data, meteorological data and user historical data to generate more accurate user demand estimates; based on the results of the energy analysis module, the power supply capacity prediction module calculates the future power demand of each region and formulates corresponding power dispatching plans; the dispatching control module formulates a dispatching plan based on the power supply capacity prediction results, and displays the dispatching plan through the analysis and display module, optimizes the operation mode of the power grid, and ensures that sufficient power can be provided during peak demand periods. Table 1 shows the experimental data of the system operation status.

[0092] Table 1 Experimental data table of the operating status of the system of the present invention

[0093] Parameter name Endpoint A Endpoint B Endpoint C Endpoint D Voltage (V) 220 218 219 223 Load(kW) 150 180 130 160 Electricity consumption (kWh) 1200 1300 1100 1250 Abnormal data (times) 1 0 1 0

[0094] It can be seen from Table 1 that the present invention can effectively collect real-time data of each endpoint and transmit it to the memory database for subsequent calculation and analysis; in terms of abnormal data screening, the table shows the number of abnormal data of each endpoint. Through the abnormal data filtering module in the data transmission module, abnormal power consumption can be quickly discovered and screened, thereby improving the response speed of the system. For example, endpoint A and endpoint C each have 1 abnormal data, while endpoint B and endpoint D have no abnormal data, indicating that the system can efficiently identify and process abnormal data, effectively reducing the operation risk of the power grid.

[0095] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A power grid information analysis system based on memory computing, characterized in that: include: Endpoint data collection module, data transmission module, memory database, power grid load monitoring module, memory data calculation module, energy analysis module, power supply capacity prediction module, power dispatching control module and analysis and display module; The endpoint data collection module is used to obtain the original data during the operation of the power grid; The data transmission module is used to process the original data and transmit it to the memory database; The memory database is used to store processed data; The power grid load monitoring module is used to monitor the power grid operation status; The memory data calculation module is used to read data from the memory database and analyze it; The energy analysis module is used to generate a user demand estimation result based on the analysis result of the memory data calculation module and transmit it to the power supply capacity prediction module; The power supply capacity prediction module is used to predict the future power supply capacity based on the user demand estimation result, and transmit the power supply capacity prediction result to the power dispatch control module; The power dispatch control module is used to formulate a power dispatch plan according to the power supply capacity prediction results, and transmit the power dispatch plan and the power supply capacity prediction results to the analysis and display module; The analysis and display module is used to display the power dispatch plan and power supply capacity prediction results.

2. The power grid information analysis system based on memory computing according to claim 1, characterized in that: The output end of the endpoint data collection module is connected to the data transmission module, the output end of the data transmission module is connected to the memory database, the output end of the memory database is connected to the memory data calculation module, the output end of the memory data calculation module is connected to the energy analysis module, the output end of the energy analysis module is connected to the power supply capacity prediction module, the output end of the power supply capacity prediction module is provided with a power dispatching control module, the output end of the power dispatching control module is provided with an analysis and display module, the output end of the power supply capacity prediction module is connected to the analysis and display module, the output end of the memory database is connected to the power grid load monitoring module, the power grid load monitoring module and the memory data calculation module are connected in parallel, and the output end of the power grid load monitoring module is connected to the input end of the endpoint data collection module.

3. The power grid information analysis system based on memory computing according to claim 2, characterized in that: The data transmission module includes an endpoint data transmission module, a node data processing module and a node data transmission module; The output end of the endpoint data transmission module is connected to the node data processing module, the output end of the node data processing module is connected to the node data transmission module, and the output end of the node data transmission module is connected to the memory database; The data transmission module also includes a node abnormal data filtering module and an abnormal data analysis and processing module; The input end of the node abnormal data filtering module is connected to the output end of the node data processing module, the output end of the node abnormal data filtering module is connected to the node data transmission module, and the output end of the node abnormal data filtering module is connected to the abnormal data analysis and processing module; The output end of the abnormal data analysis and processing module is connected to the memory data calculation module, and the output end of the memory data calculation module is connected to the input end of the memory database.

4. The power grid information analysis system based on memory computing according to claim 3, characterized in that: The energy analysis module includes actual user data, user usage evaluation, customer payment delay analysis, and cost operation analysis; A data analysis model is generated based on the actual user data, the data analysis model is analyzed through an in-memory computing mode, and a user usage evaluation is generated according to the analysis results.

5. The power grid information analysis system based on memory computing according to claim 4, characterized in that: The generating of the user demand estimation result based on the analysis result of the memory data calculation module comprises the following steps: The data in the user usage evaluation is analyzed to generate a customer payment delay analysis, and the average value of the customer's payment cycle value in a fixed period of time is calculated based on the statistical data. The specific formula is as follows: Among them, K i is the average payment period value; N i Pd is the total number of payment records of customer i during the statistical period; ij The maximum number of days allowed for payment not to be overdue; ij The number of days that payment is late; The cost operation analysis is obtained based on the analysis of the customer's payment delay, and the average value of a customer's single payment cycle within a year is calculated. The specific formula is as follows: Where S is the average value of a single payment; T is the number of fixed time periods of a single payment in a year; The final generated cost operation analysis is displayed on the analysis display module.

6. The power grid information analysis system based on memory computing according to claim 5, characterized in that: The energy analysis module also includes energy price data, meteorological data, user historical data, and user demand estimates; The data analysis model is used to analyze the user's actual data with past energy price data and meteorological data, determine the relationship between the energy price data, meteorological data and the user's actual data, thereby generating a user demand estimate, and transmitting the user demand estimate to the power supply capacity prediction module.

7. The power grid information analysis system based on memory computing according to claim 6, characterized in that: The power grid load monitoring module includes a power grid operation monitoring module, a signal transmission module, a data comparison module, a pipe damage repair module and a data update module; The output end of the power grid operation monitoring module is connected to the signal transmission module, the output end of the signal transmission module is connected to the data comparison module, the output end of the data comparison module is connected to the pipe damage repair module, and the output end of the pipe damage repair module is connected to the data update module; The output end of the data update module is connected to the input end of the power grid monitoring module, the output end of the signal transmission module is connected to the input end of the memory database, the memory database and the data comparison module are connected in parallel, and the output end of the memory database is connected to the input end of the data comparison module.

8. A method for analyzing power grid information based on memory computing, based on the power grid information analysis system based on memory computing according to any one of claims 1 to 7, characterized in that: include, Obtain the original data generated during the operation of the power grid; Perform preliminary processing, anomaly detection and in-depth analysis on the raw data to obtain processed data; Perform in-depth calculation and analysis on the processed data to obtain analysis results; Generate user demand estimation results based on the analysis results; Predict the future power supply capacity based on the user demand estimation result to obtain the power supply capacity prediction result; Formulate a power dispatch plan based on the power supply capacity forecast results, and display the power supply capacity forecast results and power dispatch plan; Continuously monitor the operation status of the power grid, obtain abnormal judgment results and make repairs.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the power grid information analysis system based on memory computing according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the power grid information analysis system based on memory computing according to any one of claims 1 to 7 are implemented.

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