Electric power insurance supply early warning method and device of electric power system and nonvolatile storage medium

Abstract

The invention discloses an electric power insurance supply early warning method and device of an electric power system and a nonvolatile storage medium. The method comprises the following steps: acquiring historical occurrence frequencies of a plurality of risk indexes and real-time operation data of a plurality of toughness indexes in a target power system; determining first index data corresponding to the plurality of risk indexes based on the historical occurrence frequency; determining second index data and third index data corresponding to the plurality of toughness indexes based on the real-time operation data; based on the first index data, the second index data and the third index data, calculating power supply insurance early warning index data corresponding to the plurality of risk indexes; and based on the power insurance supply early warning index data, determining respective power insurance supply early warning results of the plurality of risk indexes. According to the invention, the technical problem of insufficient comprehensiveness and accuracy of early warning caused by the fact that system toughness and risk whole-process evolution evaluation are not fully fused in power supply insurance early warning is solved.

Description

Technical Field

[0001] This invention relates to the field of power system operation and management technology, and more specifically, to a power supply guarantee early warning method, device, and non-volatile storage medium for power systems. Background Technology

[0002] The stable operation of power systems is crucial for modern society, especially in the face of increasingly complex and diverse risk environments. Power supply early warning technology, as an important means of preventing and responding to power supply crises, has made significant progress. Current power supply early warning technologies primarily focus on warning of impending risks, emphasizing the use of internal monitoring data and operating parameters of the power system, such as the status of power equipment, voltage, and current, to warn of potential faults or accidents. As the cornerstone of ensuring the safe and stable operation of the power grid, power supply risk early warning technology has evolved from equipment risk warning under limited monitoring conditions to early warning throughout the entire process of pre-disaster prevention and post-disaster recovery. Its early warning models and methods have also developed from optimization-based indicator systems and algorithms to intelligent early warning systems driven by artificial intelligence and machine learning.

[0003] Despite some achievements, existing technologies primarily focus on early warning of impending risks, lacking a comprehensive consideration of the spatiotemporal evolution of risks. In particular, they fail to adequately assess the impact of power system resilience on early warning effectiveness, resulting in limitations in the real-time performance and operational efficiency of early warning models, and an incomplete assessment of power supply security risks. Furthermore, in classifying early warning levels, existing technologies still rely on qualitative judgments by experts, lacking objectivity and quantitative evaluation. In complex and volatile power markets and harsh natural conditions, this limits the accuracy and timeliness of early warnings, making it difficult to comprehensively capture the dynamic evolution of power supply security risks.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a power supply guarantee early warning method, device, and non-volatile storage medium for power systems, to at least solve the technical problem of insufficient comprehensiveness and accuracy of early warning caused by the lack of full integration of system resilience and risk evolution assessment in power supply guarantee early warning.

[0006] According to one aspect of the present invention, a power supply guarantee early warning method for a power system is provided, comprising: acquiring historical occurrence frequencies of multiple risk indicators and real-time operational data of multiple resilience indicators in a target power system; determining first indicator data corresponding to each of the multiple risk indicators based on the historical occurrence frequencies, wherein the first indicator data characterizes the real-time occurrence probability of the risk indicator; determining second indicator data and third indicator data corresponding to each of the multiple resilience indicators based on the real-time operational data, wherein the second indicator data characterizes the probability of an anomaly occurring in the resilience indicator, and the third indicator data characterizes the degree of impact of the resilience indicator on the target power system; calculating power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data, and the third indicator data; and determining power supply guarantee early warning results for each of the multiple risk indicators based on the power supply guarantee early warning indicator data, wherein the power supply guarantee early warning results include a power supply guarantee early warning level.

[0007] Optionally, the multiple risk indicators include multiple natural meteorological risk indicators, multiple energy supply risk indicators, multiple socio-economic risk indicators, and multiple geopolitical risk indicators. Among them, the multiple natural meteorological risk indicators include floods, freezing, cold waves, high temperatures, and droughts; the multiple energy supply risk indicators include changes in coal supply status and changes in natural gas supply status; the multiple socio-economic risk indicators include changes in electricity demand due to increased industrial activity and improvements in power facility safety standards; and the multiple geopolitical risk indicators include a decrease in coal imports, a decrease in natural gas imports, and cyberattacks.

[0008] Optionally, the multiple resilience indicators include multiple power source resilience indicators, multiple power grid resilience indicators, multiple load resilience indicators, and multiple mechanism resilience indicators. Among them, the multiple power source resilience indicators include the saturation level of coal supply for power generation, the saturation level of gas supply for power generation, the saturation level of effective installed capacity, and the proportion of hydropower installed capacity. The multiple power grid resilience indicators include the stability of infrastructure and the line structure in abnormal environments. The multiple load resilience indicators include unpredictable loads, cooling loads, and heating loads. The multiple mechanism resilience indicators include the accuracy of load growth forecasting, the collaborative supply guarantee mechanism, and the anomaly handling mechanism.

[0009] Optionally, based on the first indicator data, the second indicator data, and the third indicator data, the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators are calculated, including: obtaining the correlation between multiple risk indicators and multiple resilience indicators; constructing a relationship matrix between multiple risk indicators and multiple resilience indicators based on the correlation; determining the power supply guarantee early warning indicator matrix based on the first indicator data, the second indicator data, the third indicator data, and the relationship matrix; and calculating the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the power supply guarantee early warning indicator matrix.

[0010] Optionally, based on the power supply guarantee early warning indicator matrix, calculate the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators, including: based on preset weights, calculate the weighted average of all data in a row corresponding to any risk indicator in the power supply guarantee early warning indicator matrix, and use it as the power supply guarantee early warning indicator data corresponding to any risk indicator.

[0011] Optionally, based on power supply guarantee early warning indicator data, the power supply guarantee early warning results for multiple risk indicators are determined, including: if the power supply guarantee early warning indicator data is less than a first preset threshold, the power supply guarantee early warning result is determined to be a first power supply guarantee early warning level; or if the power supply guarantee early warning indicator data is not less than the first preset threshold and is less than a second preset threshold, the power supply guarantee early warning result is determined to be a second power supply guarantee early warning level; or if the power supply guarantee early warning indicator data is not less than the second preset threshold and is less than a third preset threshold, the power supply guarantee early warning result is determined to be a third power supply guarantee early warning level; or if the power supply guarantee early warning indicator data is not less than the third preset threshold, the power supply guarantee early warning result is determined to be a fourth power supply guarantee early warning level, wherein the risk level represented by the first power supply guarantee early warning level, the second power supply guarantee early warning level, the third power supply guarantee early warning level, and the fourth power supply guarantee early warning level increases progressively.

[0012] According to another aspect of the present invention, a power supply guarantee early warning device for a power system is also provided, comprising: an acquisition module, configured to acquire historical occurrence frequencies of multiple risk indicators and real-time operating data of multiple resilience indicators in a target power system; a first determination module, configured to determine first indicator data corresponding to each of the multiple risk indicators based on the historical occurrence frequencies, wherein the first indicator data characterizes the real-time occurrence probability of the risk indicator; a second determination module, configured to determine second indicator data and third indicator data corresponding to each of the multiple resilience indicators based on the real-time operating data, wherein the second indicator data characterizes the probability of an anomaly occurring in the resilience indicator, and the third indicator data characterizes the degree of impact of the resilience indicator on the target power system; a calculation module, configured to calculate power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data, and the third indicator data; and a third determination module, configured to determine the power supply guarantee early warning result for each of the multiple risk indicators based on the power supply guarantee early warning indicator data, wherein the power supply guarantee early warning result includes a power supply guarantee early warning level.

[0013] According to another aspect of the present invention, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored program, wherein, when the program is running, the device where the non-volatile storage medium is located is controlled to execute any of the above-described power supply guarantee and early warning methods for power systems.

[0014] According to another aspect of the present invention, a computer device is also provided, the computer device including a processor, the processor being configured to run a program, wherein the program, when running, executes any of the above-described power supply guarantee and early warning methods for power systems.

[0015] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements any of the above-described power supply guarantee and early warning methods for power systems.

[0016] In this embodiment of the invention, a power supply guarantee early warning method for power systems is adopted. This method acquires historical occurrence frequencies of multiple risk indicators and real-time operational data of multiple resilience indicators within the target power system. Based on the historical occurrence frequencies, first indicator data corresponding to each of the multiple risk indicators is determined, where the first indicator data represents the real-time occurrence probability of the risk indicator. Based on the real-time operational data, second and third indicator data corresponding to each of the multiple resilience indicators are determined, where the second indicator data represents the probability of anomalies in the resilience indicator, and the third indicator data represents the degree of impact of the resilience indicator on the target power system. Based on the first, second, and third indicator data, power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators is calculated. Based on the power supply guarantee early warning indicator data, power supply guarantee early warning results for each of the multiple risk indicators are determined, where the power supply guarantee early warning results include the power supply guarantee early warning level. This achieves the goal of comprehensively assessing the power supply guarantee early warning level based on both risk level and system resilience, thereby improving the comprehensiveness and accuracy of power supply guarantee early warning for power systems. Furthermore, it solves the technical problem of insufficient comprehensiveness and accuracy of early warnings caused by the inadequate integration of system resilience and risk evolution assessment in power supply guarantee early warning. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0018] Figure 1 A hardware block diagram of a computer terminal for implementing a power supply guarantee and early warning method for a power system is shown.

[0019] Figure 2 This is a flowchart illustrating a power supply guarantee and early warning method for a power system according to an embodiment of the present invention.

[0020] Figure 3 This is a flowchart illustrating the implementation of a power supply guarantee early warning method according to an optional embodiment of the present invention;

[0021] Figure 4This is a structural block diagram of a power supply guarantee and early warning device for a power system provided according to an embodiment of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] According to an embodiment of the present invention, a power supply guarantee early warning method for a power system is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0025] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal for implementing a power supply guarantee and early warning method for power systems is shown. Figure 1 As shown, the computer terminal 10 may include one or more processors (shown as 102a, 102b, ..., 102n in the figure) (the processor may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0026] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10. As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0027] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the power supply guarantee and early warning method for the power system in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the power supply guarantee and early warning method for the power system described above. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0028] The display can be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10.

[0029] Figure 2 This is a flowchart illustrating a power supply guarantee and early warning method for a power system according to an embodiment of the present invention, as shown below. Figure 2 As shown, the method includes the following steps:

[0030] Step S201: Obtain the historical occurrence frequency of multiple risk indicators and the real-time operating data of multiple resilience indicators in the target power system.

[0031] In this step, historical data collection is typically achieved through literature review, industry report analysis, and historical database retrieval. The historical frequency of multiple risk indicators in the power system can be obtained by accessing publicly available data from the National Meteorological Administration, Geological Survey, and energy regulatory agencies, or by studying accident records and risk event databases within the target power system. Real-time operational data for resilience indicators is generally collected through sensors, monitoring equipment, and information systems deployed in power plants, transmission lines, load centers, and power market operation centers. For mechanism-side resilience indicators, such as the accuracy of load growth forecasts, real-time analysis and evaluation are required by integrating information from power dispatching systems, market trading systems, and emergency management systems.

[0032] Step S202: Based on historical occurrence frequency, determine the first indicator data corresponding to each of the multiple risk indicators, wherein the first indicator data represents the real-time occurrence probability of the risk indicator.

[0033] In this step, the first indicator data represents the real-time probability of occurrence of the risk indicator, i.e., the risk probability score, which can be used to assess the likelihood of external risks to power supply. The first indicator data is assigned a value between 0 and 1, and its specific value is determined by combining historical frequency statistics with expert questionnaires. Table 1 is a table explaining the threshold values ​​of the first indicator data according to an optional embodiment of the present invention. The specific threshold values ​​of the first indicator data are shown in Table 1.

[0034]

[0035] Table 1. Explanation of the data thresholds for the first indicator.

[0036] Step S203: Based on real-time operating data, determine the second and third indicator data corresponding to each of the multiple resilience indicators. The second indicator data represents the probability of an anomaly occurring in the resilience indicator, and the third indicator data represents the degree of impact of the resilience indicator on the target power system.

[0037] In this step, the second indicator data is used to assess the probability of anomalies in resilience indicators, i.e., the resilience score itself, while the third indicator data is used to assess the degree of impact of resilience indicators on the target power system, i.e., the degree of resilience impact. Specifically, for each resilience indicator, based on real-time operational data, the probability of its deviation from normal operating conditions is assessed, i.e., the probability of anomalies. Further, the impact of each resilience indicator anomaly on the entire power system is assessed. This assessment is based on factors such as the power system's topology, load distribution, and reserve capacity, calculating the potential damage to the system when each resilience indicator anomaly occurs. Some resilience indicators are local indicators, and their anomalies have relatively small impacts, while others are global indicators, and their anomalies will have systemic effects.

[0038] The values ​​of the second and third indicator data are between 0 and 1. Table 2 is an explanation table of resilience assessment thresholds provided according to an optional embodiment of the present invention. The specific thresholds for the above two types of indicator data are shown in Table 2. In addition, resilience can also be comprehensively assessed. The comprehensive resilience assessment score is the product of the corresponding values ​​of the second and third indicator data.

[0039]

[0040] Table 2. Explanation of Toughness Assessment Thresholds

[0041] Step S204: Based on the first indicator data, the second indicator data, and the third indicator data, calculate the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators.

[0042] In this step, the data for the first, second, and third indicators are comprehensively analyzed using a specific mathematical model to obtain power supply early warning indicator data corresponding to each of the multiple risk indicators. Specifically, a risk-resilience coupling relationship matrix is ​​constructed based on the mutual influence between risk and resilience to determine the degree of correlation between each risk and resilience indicator, i.e., which risks directly affect which resilience indicators. Next, the three data types are multiplied by their corresponding values ​​in the coupling matrix using a formula, and then weighted to obtain the power supply early warning indicator data for each risk indicator.

[0043] Step S205: Based on the power supply guarantee early warning indicator data, determine the power supply guarantee early warning results for each of the multiple risk indicators, wherein the power supply guarantee early warning results include the power supply guarantee early warning level.

[0044] In this step, determining the power supply early warning results for multiple risk indicators based on power supply early warning indicator data is essentially a process of mapping the calculated early warning indicator data to specific early warning actions. This process first analyzes the early warning indicator data, assesses the severity of each risk's potential threat to the power system, and preliminarily classifies and grades the risks based on their data values. Subsequently, based on the early warning level, corresponding action strategies are generated, such as adjusting power generation and distribution, enhancing equipment maintenance, and coordinating resource allocation, to ensure that the power system can respond quickly and effectively to risks and reduce their negative impact on power supply.

[0045] Through the above steps, the goal of assessing the power supply guarantee early warning level by comprehensively considering risk level and system resilience is achieved. This improves the comprehensiveness and accuracy of power supply guarantee early warning, and solves the technical problem of insufficient comprehensiveness and accuracy of early warning caused by the lack of full integration of system resilience and risk evolution assessment in power supply guarantee early warning.

[0046] As an optional embodiment, this can be achieved through the following steps: multiple risk indicators include multiple natural meteorological risk indicators, multiple energy supply risk indicators, multiple socio-economic risk indicators, and multiple geopolitical risk indicators. Among them, the multiple natural meteorological risk indicators include floods, freezing, cold waves, high temperatures, and droughts; the multiple energy supply risk indicators include changes in coal supply status and changes in natural gas supply status; the multiple socio-economic risk indicators include changes in electricity demand due to increased industrial activity and improvements in power facility safety standards; and the multiple geopolitical risk indicators include a decrease in coal imports, a decrease in natural gas imports, and cyberattacks.

[0047] Optionally, a risk characterization index system can be constructed by identifying potential external risks to power supply security in the power system. External risks refer to any potential factors that may disrupt the power system's supply and demand balance, which are usually beyond the control of power system planning and operation, such as natural meteorological risks like high temperatures and cold waves. Through literature review, surveys, and other means to review historical supply security risks, as well as analysis of future climate characteristics and assessment of power supply and demand, it is identified that external risks to power supply security mainly come from cross-system factors such as natural meteorological systems, energy supply systems, economic and social systems, and geopolitical systems. Twelve risk characterization indicators are further extracted and labeled T1 to T12. Table 3 is a table of external risk characterization indexes for power supply security provided by an optional embodiment of the present invention, and the specific meanings of multiple risk indicators are shown in Table 3.

[0048]

[0049] Table 3. External Risk Characterization Index System for Power Supply Security

[0050] As an optional embodiment, it can be achieved through the following steps: multiple resilience indicators include multiple power source resilience indicators, multiple power grid resilience indicators, multiple load resilience indicators, and multiple mechanism resilience indicators. Among them, the multiple power source resilience indicators include the saturation level of coal supply for power generation, the saturation level of gas supply for power generation, the saturation level of effective installed capacity, and the proportion of hydropower installed capacity. The multiple power grid resilience indicators include the stability of infrastructure and the line structure in abnormal environments. The multiple load resilience indicators include unpredictable loads, cooling loads, and heating loads. The multiple mechanism resilience indicators include the accuracy of load growth prediction, the collaborative supply guarantee mechanism, and the anomaly handling mechanism.

[0051] Optionally, resilience indicators can be extracted by identifying the inherent resilience of the power system. Resilience refers to the adaptability of a power system when facing external risks; insufficient resilience will allow risks to damage the system. Overall, power system resilience is mainly reflected in four aspects: power source, grid, load, and mechanism. Through preliminary analysis of the potential impact paths of external risks on the internal structure of the power system, a secondary indicator system for representing power system resilience is further extracted, labeled R1 to R12. Table 4 shows the power system internal resilience characterization indicator system provided by an optional embodiment of the present invention, with the specific meanings of multiple resilience indicators as shown in Table 4.

[0052]

[0053] Table 4. Power System Internal Resilience Characterization Index System

[0054] As an optional embodiment, this can be achieved through the following steps: Calculating power supply early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data, and the third indicator data, including: obtaining the correlation between multiple risk indicators and multiple resilience indicators; constructing a relationship matrix between multiple risk indicators and multiple resilience indicators based on the correlation; determining the power supply early warning indicator matrix based on the first indicator data, the second indicator data, the third indicator data, and the relationship matrix; and calculating the power supply early warning indicator data corresponding to each of the multiple risk indicators based on the power supply early warning indicator matrix.

[0055] Optionally, firstly, through literature review and expert consultation, a systematic analysis is conducted to identify which risk factors directly impact the resilience of power systems, thereby identifying the correlation patterns between risk and resilience. Secondly, based on these correlations, a relationship matrix is ​​constructed between multiple risk indicators and multiple resilience indicators, namely the risk-resilience coupling matrix (TR). This coupling matrix presents the correlation between risk and resilience, but not all risks will affect the resilience of every system. Specifically, This indicates that the i-th type of risk is not associated with the j-th type of resilience; This indicates that the i-th type of risk is associated with the j-th type of resilience.

[0056] Furthermore, considering the joint early warning of system resilience and risk evolution, a power supply guarantee early warning indicator matrix is ​​formed. The power supply guarantee early warning indicator matrix is ​​denoted as... W The first indicator data is denoted as The second indicator data is denoted as The third indicator data is denoted as Power supply guarantee early warning indicator matrix elements W [ i ][ j The calculation formula is as follows:

[0057]

[0058] in, i , j The maximum values ​​are the number of identified risk and resilience types, respectively.

[0059] Finally, the elements in the power supply guarantee early warning indicator matrix are further processed to obtain the power supply guarantee early warning indicator data for each risk indicator, thereby quantifying the risk. i For potential threats to power supply, an early warning score is generated for each risk, which serves as the data basis for subsequent early warning level classification.

[0060] As an optional embodiment, this can be achieved through the following steps: Based on the power supply guarantee early warning indicator matrix, calculate the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators, including: based on preset weights, calculate the weighted average of all data in a row corresponding to any risk indicator in the power supply guarantee early warning indicator matrix, and use this as the power supply guarantee early warning indicator data corresponding to any risk indicator.

[0061] Optionally, the power supply guarantee early warning indicator data is recorded as W [ i ], W [ i [This is the first in the power supply guarantee early warning indicator matrix] i The weighted average of the risk scores is determined by pre-setting the weights. In this optional embodiment, since the importance of resilience has already been considered in the resilience assessment, each resilience index is given the same weight, i.e.:

[0062]

[0063] The higher the value of the power supply guarantee early warning indicator, the higher the level and degree of risk.

[0064] As an optional embodiment, this can be achieved through the following steps: determining the power supply guarantee early warning results for multiple risk indicators based on power supply guarantee early warning indicator data, including: determining the power supply guarantee early warning result as a first power supply guarantee early warning level when the power supply guarantee early warning indicator data is less than a first preset threshold; or determining the power supply guarantee early warning result as a second power supply guarantee early warning level when the power supply guarantee early warning indicator data is not less than the first preset threshold and is less than a second preset threshold; or determining the power supply guarantee early warning result as a third power supply guarantee early warning level when the power supply guarantee early warning indicator data is not less than the second preset threshold and is less than a third preset threshold; or determining the power supply guarantee early warning result as a fourth power supply guarantee early warning level when the power supply guarantee early warning indicator data is not less than the third preset threshold, wherein the risk level represented by the first power supply guarantee early warning level, the second power supply guarantee early warning level, the third power supply guarantee early warning level, and the fourth power supply guarantee early warning level increases progressively.

[0065] Optionally, based on power supply guarantee early warning indicator data W [ i The risk level can be divided into four levels: extremely severe, severe, moderate, and general, distinguished by red, orange, yellow, and blue colors, respectively. Specifically, the warning level thresholds are predetermined. If the power supply warning indicator data is less than the first preset threshold (0.3), the power supply warning result is determined to be at the first power supply warning level, i.e., general risk level; if the power supply warning indicator data is not less than the first preset threshold and less than the second preset threshold (0.6), the power supply warning result is determined to be at the second power supply warning level, i.e., moderate risk level; if the power supply warning indicator data is not less than the second preset threshold and less than the third preset threshold (0.8), the power supply warning result is determined to be at the third power supply warning level, i.e., severe risk level; and if the power supply warning indicator data is not less than the third preset threshold, the power supply warning result is determined to be at the fourth power supply warning level, i.e., extremely severe risk level. The risk level increases progressively from the first to the fourth level. Table 5 is an explanation table of the power supply warning level thresholds provided by an optional embodiment of the present invention, and the classification criteria for each warning level are shown in Table 5.

[0066]

[0067] Table 5. Explanation of Power Supply Guarantee Early Warning Level Thresholds

[0068] As an alternative embodiment, Figure 3 This is a flowchart illustrating the implementation of a power supply guarantee early warning method according to an optional embodiment of the present invention. Figure 3As shown, the power supply early warning method in this optional embodiment first requires identifying potential external risks to the power system and refining a risk indicator system covering natural meteorology, energy supply, economic and social factors, and geopolitical fields. Based on historical data analysis and expert evaluation, the probability of occurrence of the aforementioned risk indicators is quantitatively assessed and assigned fixed values. Secondly, the system's own resilience is identified, and resilience characterization indicators are extracted from four dimensions: power source, grid, load, and mechanism. Based on real-time monitoring data, the current state of the aforementioned resilience indicators is quantitatively assessed, including their probability of anomalies and the degree of impact on the overall power system.

[0069] Furthermore, a risk-resilience coupling matrix is ​​constructed based on the mutual influence between risk and resilience, and a joint risk-resilience early warning model is built based on the aforementioned data and matrix. The model comprehensively utilizes risk probability scores, resilience status scores, and the coupling matrix, and calculates the power supply guarantee early warning index data for each risk indicator through formula calculations. W [ i This has enabled the initial determination of risk quantification and early warning levels.

[0070] Finally, based on the calculation W [ i The values, referencing pre-defined warning thresholds, determine the specific power supply warning level for each risk indicator, with risk levels increasing progressively from level one to level four. These levels guide real-time monitoring and management decisions regarding power supply risks. The results will be applied to power supply monitoring and dispatching, initiating corresponding emergency measures and recovery strategies based on the warning level to ensure the safe and stable operation of the power system. Simultaneously, the dynamic evolution of risks will be continuously monitored to optimize power supply strategies and enhance system resilience.

[0071] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0072] Through the above description of the embodiments, those skilled in the art can clearly understand that the power supply guarantee and early warning method for power systems according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0073] According to embodiments of the present invention, an apparatus for implementing the above-described power supply guarantee early warning method for power systems is also provided. Figure 4 This is a structural block diagram of a power supply guarantee and early warning device for a power system according to an embodiment of the present invention, such as... Figure 4 As shown, the device includes: an acquisition module 41, a first determination module 42, a second determination module 43, a calculation module 44, and a third determination module 45. The device will be described below.

[0074] The acquisition module 41 is used to acquire the historical occurrence frequency of multiple risk indicators and the real-time operating data of multiple resilience indicators in the target power system.

[0075] The first determining module 42, connected to the acquiring module 41, is used to determine the first indicator data corresponding to each of the multiple risk indicators based on the historical occurrence frequency, wherein the first indicator data represents the real-time occurrence probability of the risk indicator.

[0076] The second determining module 43, connected to the first determining module 42, is used to determine the second indicator data and the third indicator data corresponding to each of the multiple resilience indicators based on real-time operating data. The second indicator data represents the probability of an anomaly occurring in the resilience indicator, and the third indicator data represents the degree of impact of the resilience indicator on the target power system.

[0077] The calculation module 44, connected to the second determination module 43, is used to calculate the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data, and the third indicator data.

[0078] The third determining module 45, connected to the calculation module 44, is used to determine the power supply early warning results of multiple risk indicators based on the power supply early warning indicator data. The power supply early warning results include the power supply early warning level.

[0079] It should be noted that the aforementioned acquisition module 41, first determination module 42, second determination module 43, calculation module 44, and third determination module 45 correspond to steps S201 to S205 in the embodiments. Multiple modules implement the same instances and application scenarios as their corresponding steps, but are not limited to the content disclosed in the above embodiments. It should also be noted that the aforementioned modules, as part of the device, can run on the computer terminal 10 provided in the embodiments.

[0080] Embodiments of the present invention may provide a computer device. Optionally, in this embodiment, the computer device may be located in at least one of a plurality of network devices in a computer network. The computer device includes a memory and a processor.

[0081] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the power supply guarantee early warning method and device for power systems in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the aforementioned power supply guarantee early warning method for power systems. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0082] The processor can access information and application programs stored in the memory via a transmission device to perform the following steps: acquiring historical occurrence frequencies of multiple risk indicators and real-time operational data of multiple resilience indicators in the target power system; determining first indicator data corresponding to each of the multiple risk indicators based on the historical occurrence frequencies, wherein the first indicator data represents the real-time occurrence probability of the risk indicator; determining second and third indicator data corresponding to each of the multiple resilience indicators based on the real-time operational data, wherein the second indicator data represents the probability of an anomaly in the resilience indicator, and the third indicator data represents the degree of impact of the resilience indicator on the target power system; calculating power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the first, second, and third indicator data; and determining power supply guarantee early warning results for each of the multiple risk indicators based on the power supply guarantee early warning indicator data, wherein the power supply guarantee early warning results include the power supply guarantee early warning level.

[0083] Optionally, the processor may also execute program code that performs the following steps: multiple risk indicators include multiple natural meteorological risk indicators, multiple energy supply risk indicators, multiple socio-economic risk indicators, and multiple geopolitical risk indicators. Among these, the multiple natural meteorological risk indicators include floods, freezing, cold waves, high temperatures, and droughts; the multiple energy supply risk indicators include changes in coal supply status and changes in natural gas supply status; the multiple socio-economic risk indicators include changes in electricity demand due to increased industrial activity and improvements in power facility safety standards; and the multiple geopolitical risk indicators include a decrease in coal imports, a decrease in natural gas imports, and cyberattacks.

[0084] Optionally, the processor may also execute program code for the following steps: multiple resilience indicators include multiple power supply resilience indicators, multiple power grid resilience indicators, multiple load resilience indicators, and multiple mechanism resilience indicators. Among them, the multiple power supply resilience indicators include the saturation level of coal supply for power generation, the saturation level of gas supply for power generation, the saturation level of effective installed capacity, and the proportion of hydropower installed capacity. The multiple power grid resilience indicators include the stability of infrastructure and the line structure in abnormal environments. The multiple load resilience indicators include unpredictable loads, cooling loads, and heating loads. The multiple mechanism resilience indicators include the accuracy of load growth prediction, the collaborative supply guarantee mechanism, and the anomaly handling mechanism.

[0085] Optionally, the processor may also execute program code that performs the following steps: calculating power supply early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data, and the third indicator data, including: obtaining the correlation between the multiple risk indicators and the multiple resilience indicators; constructing a relationship matrix between the multiple risk indicators and the multiple resilience indicators based on the correlation; determining the power supply early warning indicator matrix based on the first indicator data, the second indicator data, the third indicator data, and the relationship matrix; and calculating the power supply early warning indicator data corresponding to each of the multiple risk indicators based on the power supply early warning indicator matrix.

[0086] Optionally, the processor may also execute program code for the following steps: based on the power supply guarantee early warning indicator matrix, calculate the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators, including: based on preset weights, calculate the weighted average of all data in a row corresponding to any risk indicator in the power supply guarantee early warning indicator matrix, as the power supply guarantee early warning indicator data corresponding to any risk indicator.

[0087] Optionally, the processor may also execute program code for the following steps: determining the power supply early warning results for multiple risk indicators based on power supply early warning indicator data, including: determining the power supply early warning result as a first power supply early warning level when the power supply early warning indicator data is less than a first preset threshold; or determining the power supply early warning result as a second power supply early warning level when the power supply early warning indicator data is not less than the first preset threshold and is less than a second preset threshold; or determining the power supply early warning result as a third power supply early warning level when the power supply early warning indicator data is not less than the second preset threshold and is less than a third preset threshold; or determining the power supply early warning result as a fourth power supply early warning level when the power supply early warning indicator data is not less than the third preset threshold, wherein the risk level represented by the first power supply early warning level, the second power supply early warning level, the third power supply early warning level, and the fourth power supply early warning level increases progressively.

[0088] This invention provides a power supply guarantee early warning scheme for power systems. It involves acquiring historical occurrence frequencies of multiple risk indicators and real-time operational data of multiple resilience indicators within the target power system; determining first indicator data corresponding to each risk indicator based on historical occurrence frequencies, where the first indicator data represents the real-time occurrence probability of the risk indicator; determining second and third indicator data corresponding to each resilience indicator based on real-time operational data, where the second indicator data represents the probability of anomalies in the resilience indicator, and the third indicator data represents the degree of impact of the resilience indicator on the target power system; calculating power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the first, second, and third indicator data; and determining power supply guarantee early warning results for each of the multiple risk indicators based on the power supply guarantee early warning indicator data, where the power supply guarantee early warning results include a power supply guarantee early warning level. This achieves the goal of comprehensively assessing the power supply guarantee early warning level by integrating risk level and system resilience, thereby solving the technical problem of insufficient comprehensiveness and accuracy of early warnings caused by the inadequate integration of system resilience and risk evolution assessment in power supply guarantee early warning.

[0089] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a non-volatile storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0090] Embodiments of the present invention also provide a non-volatile storage medium. Optionally, in this embodiment, the aforementioned non-volatile storage medium can be used to store the program code executed by the power supply guarantee and early warning method for the power system provided in the above embodiments.

[0091] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0092] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: acquiring historical occurrence frequencies of multiple risk indicators and real-time operational data of multiple resilience indicators in the target power system; determining first indicator data corresponding to each of the multiple risk indicators based on the historical occurrence frequencies, wherein the first indicator data represents the real-time occurrence probability of the risk indicator; determining second and third indicator data corresponding to each of the multiple resilience indicators based on the real-time operational data, wherein the second indicator data represents the probability of an anomaly occurring in the resilience indicator, and the third indicator data represents the degree of impact of the resilience indicator on the target power system; calculating power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the first, second, and third indicator data; and determining power supply guarantee early warning results for each of the multiple risk indicators based on the power supply guarantee early warning indicator data, wherein the power supply guarantee early warning results include power supply guarantee early warning levels.

[0093] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: multiple risk indicators include multiple natural meteorological risk indicators, multiple energy supply risk indicators, multiple socio-economic risk indicators, and multiple geopolitical risk indicators. Among them, the multiple natural meteorological risk indicators include floods, freezing, cold waves, high temperatures, and droughts; the multiple energy supply risk indicators include changes in coal supply status and changes in natural gas supply status; the multiple socio-economic risk indicators include changes in electricity demand due to increased industrial activity and improvements in power facility safety standards; and the multiple geopolitical risk indicators include a decrease in coal imports, a decrease in natural gas imports, and cyberattacks.

[0094] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: multiple resilience indicators include multiple power supply resilience indicators, multiple power grid resilience indicators, multiple load resilience indicators, and multiple mechanism resilience indicators, wherein the multiple power supply resilience indicators include the saturation level of coal supply for power generation, the saturation level of gas supply for power generation, the saturation level of effective installed capacity, and the proportion of hydropower installed capacity; the multiple power grid resilience indicators include the stability of infrastructure and the line structure under abnormal environments; the multiple load resilience indicators include unpredictable loads, cooling loads, and heating loads; and the multiple mechanism resilience indicators include the accuracy of load growth prediction, the collaborative supply guarantee mechanism, and the anomaly handling mechanism.

[0095] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: calculating power supply early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data, and the third indicator data, including: obtaining the correlation between the multiple risk indicators and the multiple resilience indicators; constructing a relationship matrix between the multiple risk indicators and the multiple resilience indicators based on the correlation; determining the power supply early warning indicator matrix based on the first indicator data, the second indicator data, the third indicator data, and the relationship matrix; and calculating the power supply early warning indicator data corresponding to each of the multiple risk indicators based on the power supply early warning indicator matrix.

[0096] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: based on the power supply guarantee early warning index matrix, calculate the power supply guarantee early warning index data corresponding to each of the multiple risk indicators, including: based on preset weights, calculate the weighted average of all data in a row corresponding to any risk indicator in the power supply guarantee early warning index matrix, as the power supply guarantee early warning index data corresponding to any risk indicator.

[0097] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the power supply early warning results of multiple risk indicators based on power supply early warning indicator data, including: determining the power supply early warning result as a first power supply early warning level when the power supply early warning indicator data is less than a first preset threshold; or determining the power supply early warning result as a second power supply early warning level when the power supply early warning indicator data is not less than the first preset threshold and is less than a second preset threshold; or determining the power supply early warning result as a third power supply early warning level when the power supply early warning indicator data is not less than the second preset threshold and is less than a third preset threshold; or determining the power supply early warning result as a fourth power supply early warning level when the power supply early warning indicator data is not less than the third preset threshold, wherein the risk level represented by the first power supply early warning level, the second power supply early warning level, the third power supply early warning level, and the fourth power supply early warning level increases progressively.

[0098] Embodiments of the present invention also provide a computer program product, including a computer program. Optionally, in this embodiment, when the computer program is executed by a processor, it can: acquire the historical occurrence frequency of multiple risk indicators and the real-time operating data of multiple resilience indicators in a target power system; determine the first indicator data corresponding to each of the multiple risk indicators based on the historical occurrence frequency, wherein the first indicator data represents the real-time occurrence probability of the risk indicator; determine the second indicator data and the third indicator data corresponding to each of the multiple resilience indicators based on the real-time operating data, wherein the second indicator data represents the probability of an anomaly in the resilience indicator, and the third indicator data represents the degree of impact of the resilience indicator on the target power system; calculate the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data, and the third indicator data; and determine the power supply guarantee early warning result for each of the multiple risk indicators based on the power supply guarantee early warning indicator data, wherein the power supply guarantee early warning result includes the power supply guarantee early warning level.

[0099] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0100] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0101] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0102] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0103] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0104] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0105] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A power supply guarantee early warning method for a power system, characterized in that, include: Acquire historical occurrence frequency of multiple risk indicators and real-time operational data of multiple resilience indicators in the target power system; Based on the historical occurrence frequency, the first indicator data corresponding to each of the multiple risk indicators is determined, wherein the first indicator data represents the real-time occurrence probability of the risk indicator. Based on the real-time operating data, second and third indicator data corresponding to each of the multiple resilience indicators are determined, wherein the second indicator data represents the probability of the resilience indicator occurring abnormally, and the third indicator data represents the degree of impact of the resilience indicator on the target power system. Based on the first indicator data, the second indicator data, and the third indicator data, calculate the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators; Based on the power supply guarantee early warning indicator data, the power supply guarantee early warning results for each of the multiple risk indicators are determined, wherein the power supply guarantee early warning results include the power supply guarantee early warning level.

2. The method according to claim 1, characterized in that, The multiple risk indicators include multiple natural meteorological risk indicators, multiple energy supply risk indicators, multiple socio-economic risk indicators, and multiple geopolitical risk indicators. Among them, the multiple natural meteorological risk indicators include floods, freezing, cold waves, high temperatures, and droughts; the multiple energy supply risk indicators include changes in coal supply status and changes in natural gas supply status; the multiple socio-economic risk indicators include changes in electricity demand due to increased industrial activity and improvements in power facility safety standards; and the multiple geopolitical risk indicators include a decrease in coal imports, a decrease in natural gas imports, and cyberattacks.

3. The method according to claim 1, characterized in that, The multiple resilience indicators include multiple power source resilience indicators, multiple power grid resilience indicators, multiple load resilience indicators, and multiple mechanism resilience indicators. Among them, the multiple power source resilience indicators include the saturation level of coal supply for power generation, the saturation level of gas supply for power generation, the saturation level of effective installed capacity, and the proportion of hydropower installed capacity. The multiple power grid resilience indicators include the stability of infrastructure and the line structure under abnormal environments. The multiple load resilience indicators include unpredictable loads, cooling loads, and heating loads. The multiple mechanism resilience indicators include the accuracy of load growth prediction, the collaborative supply guarantee mechanism, and the anomaly handling mechanism.

4. The method according to claim 1, characterized in that, The calculation of power supply early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data, and the third indicator data includes: Obtain the correlation between the multiple risk indicators and the multiple resilience indicators; Based on the aforementioned relationships, a relationship matrix between the multiple risk indicators and the multiple resilience indicators is constructed; Based on the first indicator data, the second indicator data, the third indicator data, and the relationship matrix, a power supply guarantee early warning indicator matrix is ​​determined; Based on the power supply guarantee early warning index matrix, calculate the power supply guarantee early warning index data corresponding to each of the multiple risk indicators.

5. The method according to claim 4, characterized in that, The calculation of power supply early warning indicator data corresponding to each of the multiple risk indicators based on the power supply early warning indicator matrix includes: Based on preset weights, the weighted average of all data in the row corresponding to any risk indicator in the power supply early warning indicator matrix is ​​calculated, and this average is used as the power supply early warning indicator data corresponding to any risk indicator.

6. The method according to any one of claims 1 to 5, characterized in that, The process of determining the power supply early warning results for each of the multiple risk indicators based on the power supply early warning indicator data includes: If the power supply guarantee early warning indicator data is less than a first preset threshold, the power supply guarantee early warning result is determined to be the first power supply guarantee early warning level; Alternatively, if the power supply guarantee early warning indicator data is not less than the first preset threshold and is less than the second preset threshold, the power supply guarantee early warning result shall be determined as the second power supply guarantee early warning level. Alternatively, if the power supply warning is not less than the second preset threshold and less than the third preset threshold of the indicator data, the power supply warning result shall be determined as the third power supply warning level. Alternatively, if the power supply guarantee early warning indicator data is not less than the third preset threshold, the power supply guarantee early warning result is determined to be the fourth power supply guarantee early warning level, wherein the risk level represented by the first power supply guarantee early warning level, the second power supply guarantee early warning level, the third power supply guarantee early warning level, and the fourth power supply guarantee early warning level increases progressively.

7. A power supply early warning device for a power system, characterized in that, include: The acquisition module is used to acquire historical occurrence frequencies of multiple risk indicators and real-time operational data of multiple resilience indicators in the target power system. The first determining module is used to determine the first indicator data corresponding to each of the plurality of risk indicators based on the historical occurrence frequency, wherein the first indicator data represents the real-time occurrence probability of the risk indicator. The second determining module is used to determine, based on the real-time operating data, the second indicator data and the third indicator data corresponding to each of the plurality of resilience indicators, wherein the second indicator data represents the probability of the resilience indicator occurring abnormally, and the third indicator data represents the degree of impact of the resilience indicator on the target power system. The calculation module is used to calculate the power supply guarantee early warning indicator data corresponding to each of the multiple risk indicators based on the first indicator data, the second indicator data and the third indicator data; The third determining module is used to determine the power supply early warning result of each of the multiple risk indicators based on the power supply early warning indicator data, wherein the power supply early warning result includes the power supply early warning level.

8. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the non-volatile storage medium to execute the power supply guarantee and early warning method for the power system according to any one of claims 1 to 6.

9. A computer device, characterized in that, include: Memory and processor The memory stores computer programs; The processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, the processor performs the power supply guarantee and early warning method for the power system according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the power supply guarantee and early warning method for the power system according to any one of claims 1 to 6.

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