A method and system for risk assessment of perimeter equipment of power stations against external attacks

Abstract

The present invention relates to the field of safe operation of power stations and power systems, and provides a method and system for risk assessment of perimeter equipment of power stations against external attacks, including: constructing a scenario database of power station perimeter equipment being attacked from outside, determining the initial event of a chain failure event; conducting event tree chain failure simulation deduction, determining intermediate events and consequence events under different deduction paths; determining the probability of occurrence of intermediate events and consequence events; selecting risk assessment indicators, determining the mapping relationship between risk assessment indicators and risk levels; constructing a risk assessment model for perimeter equipment of power stations, obtaining the risk level and risk ranking of each perimeter equipment of the power station; and providing safety precautions. The present invention is suitable for risk assessment of power stations against external attacks, taking into account the complex mechanism of the occurrence and evolution of power equipment failures, the severity of the direct and subsequent secondary derivative events, and can more accurately assess the safety of power stations under attack.

Description

Technical Field

[0001] The present invention relates to the field of safe operation of power stations and power systems, and in particular to a method and system for risk assessment of perimeter equipment of power stations against external attacks. Background Art

[0002] For the foreseeable future, coal-fired power stations will remain a key source of power for my country's new power system. Therefore, their safe operation will directly impact the safety of the entire power system. After years of technological advancement and improvements in operator quality, the operational safety of my country's coal-fired power stations has been significantly enhanced, enabling long-term safe operation of units. However, the safety of coal-fired power stations encompasses more than just safe operation under normal circumstances; it also encompasses safe operation under exceptional circumstances (such as external attacks from people, vehicles, low-altitude aircraft, floating objects, and projectiles). This latter aspect is particularly crucial in western China, where social instability is prevalent. Within a coal-fired power station, the most vulnerable components are the perimeter equipment, primarily including the hydrogen production station, fuel station, circulating water system / or air cooling system, flue gas denitrification system, flue gas desulfurization system, pulverizing system, coal transportation system, heating system, transformers, and booster stations. When a power station's perimeter equipment system is attacked from the outside, it can cause the equipment to shut down or be damaged, and even explosions, the spread of toxic gases, and other accidents that endanger human and environmental safety. It can also spread to the entire power station through cascading failures, ultimately affecting the power grid and causing serious consequences and significant losses, such as large-scale power outages.

[0003] Currently, most safety risk assessment models for coal-fired power plants assess equipment safety risk levels under normal operation. No literature has specifically addressed the safety risks of power plants under external attacks. Furthermore, existing models struggle to understand the complex mechanisms underlying the occurrence and evolution of power equipment failures, or the severity of direct and subsequent secondary events. Furthermore, they fail to analyze the factors influencing power plant equipment operation and the consequences of power plant equipment failures, making it difficult to accurately assess the risks of equipment within a power plant's perimeter.

[0004] Therefore, it is necessary to conduct research on risk assessment methods for power station perimeter equipment against external attacks to address the shortcomings of existing technologies and to solve or mitigate one or more of the above problems. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide a method and system for risk assessment of power station perimeter equipment against external attacks. Through event tree chain failure simulation and risk assessment, risk ranking of power station perimeter equipment is achieved, providing a basis for power stations to formulate preventive measures.

[0006] The present invention adopts the following technical solutions:

[0007] In one aspect, the present invention provides a method for risk assessment of perimeter equipment of a power station against external attacks, comprising:

[0008] S1. Build a scenario database of external attacks on power station perimeter equipment and determine the initial events of cascading failure events;

[0009] S2. For the initial event in step S1, perform an event tree cascading failure simulation to determine the intermediate events and consequence events of each perimeter device under different simulation paths;

[0010] S3. Determine the probability of occurrence of the intermediate event and the consequence event corresponding to the cascading failure in step S2;

[0011] S4. Select risk assessment indicators and determine the mapping relationship between the risk assessment indicators and risk levels;

[0012] S5. Construct a risk assessment model for perimeter equipment of a power station, and obtain the risk level and risk ranking of each perimeter equipment of the power station based on the risk assessment model for perimeter equipment of the power station, the mapping relationship of step S4, and the probability of occurrence of the intermediate event and the consequence event of step S3.

[0013] According to any of the possible implementations described above, there is further provided an implementation, wherein the method further includes:

[0014] S6. Based on the external attack means and the risk level and risk ranking of each perimeter equipment of the power station obtained in step S5, security precautions are recommended.

[0015] As for any possible implementation described above, a further implementation is provided, in which, in step S1, the external attack means include: people, vehicles, low-altitude aircraft, floating objects or thrown objects; the external attack targets include all peripheral equipment and systems of the power station; and the initial event of the cascading failure event is determined through a scenario construction method.

[0016] As for any possible implementation described above, a further implementation is provided, in step S3, the probability of occurrence of the intermediate event and the consequence event is obtained by statistical analysis of multiple simulation result data and / or real historical data.

[0017] In any of the possible implementations described above, a further implementation is provided, in step S3, the method for calculating the probability of occurrence of a type i consequence event of a certain device is as follows:

[0018]

[0019] Where p ijis the probability of occurrence of the jth consequence event in the i-th consequence event; x ijk is the probability of occurrence of the kth intermediate event of the jth consequence event in the i-th consequence event; M is the number of consequence events included in the i-th consequence event; L is the number of intermediate events corresponding to the jth consequence event in the i-th consequence event.

[0020] As for any possible implementation described above, an implementation is further provided, in step S4, the risk assessment indicators include casualties, half-lethal range (half of the people will die within this range), equipment loss, power grid impact, environmental impact, economic loss and accident recovery time.

[0021] For any of the possible implementations described above, a further implementation is provided, in which step S4 specifically includes:

[0022] S41. Using a large number of event tree cascading failure simulation results, through statistical analysis, we select casualties, equipment loss, grid impact, environmental impact, economic loss and accident recovery time as risk assessment indicators.

[0023] S42. Determine a mapping relationship between each of the risk assessment indicators and the risk level;

[0024] S43. Calculate the risk assessment index of a perimeter device:

[0025]

[0026] Where p i为 The probability of occurrence of type i consequence event; r ij is the quantitative value of the jth risk assessment indicator corresponding to the i-th type of consequence event; N is the number of categories of consequence events;

[0027] S44, fuzzifying the risk assessment index in step S43 using a fuzzy membership function curve;

[0028] S45. Determine the weight of each risk assessment index based on the CRITIC method;

[0029] Assume there are n devices to be evaluated and m risk assessment indicators, forming the original indicator data matrix

[0030]

[0031] Among them, RI ij Represents the value of the j-th risk assessment indicator of the i-th device to be evaluated;

[0032] Step S451: normalization of risk assessment indicators:

[0033] Normalized calculation of positive indicators:

[0034]

[0035] Normalized calculation of negative indicators:

[0036]

[0037] In the formula, RI max , RI min are the maximum and minimum values of the j-th risk assessment index respectively;

[0038] Step S452: Calculate the index comparison strength:

[0039]

[0040]

[0041] S is the standard deviation of the jth indicator;

[0042] Step S453: Calculation of index conflict:

[0043]

[0044] r ij represents the correlation coefficient between risk assessment indicators i and j;

[0045] Step S454: Objective weight W j calculate

[0046]

[0047]

[0048] Any possible implementation as described above, further provides an implementation method, in step S5, a decision tree risk assessment model based on evidence reasoning is adopted, the model input is the fuzzified risk assessment index and the corresponding objective weight, the model output is the risk level and risk ranking of each perimeter device, and the evidence reasoning algorithm is used to implement:

[0049] As for any possible implementation described above, a further implementation is provided, in step S6, the safety precaution measure suggestion includes the type and location of the installed safety precaution warning device, and the safety precaution warning device includes a camera and a radar.

[0050] On the other hand, the present invention also provides a power station perimeter equipment risk assessment system against external attacks, comprising:

[0051] A scenario database module is used to build a scenario database for external attacks on the perimeter equipment of the power station;

[0052] A cascading failure simulation and deduction module is used to determine the initial event of the cascading failure event, perform event tree cascading failure simulation and deduction, determine the intermediate events and consequence events of each perimeter device under different deduction paths; and determine the probability of occurrence of the intermediate events and consequence events;

[0053] The power station perimeter equipment risk assessment module is used to select risk assessment indicators, determine the mapping relationship between the risk assessment indicators and risk levels; and obtain the risk level and risk ranking of each perimeter equipment of the power station based on the mapping relationship and the probability of occurrence of the intermediate events and consequence events.

[0054] On the other hand, the present invention further provides a readable storage medium, comprising a processor and a memory, wherein the processor is connected to the memory, wherein;

[0055] The processor is configured to call and execute the program stored in the memory;

[0056] The memory is used to store the program, and the program is at least used to execute the above-mentioned power station perimeter equipment risk assessment method against external attacks.

[0057] The beneficial effects of the present invention are:

[0058] The present invention establishes a connection between possible external attack methods and the perimeter equipment of the power station, realizing full-path cascading failure simulation and deduction; the consequence events and probability of cascading failures can be determined based on the deduction results (and expert opinions); and the established risk assessment model based on evidence reasoning can realize risk assessment and risk ranking of the perimeter equipment of the power station, providing a basis for formulating safety precautions. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 Shown is a logical framework diagram of a method for risk assessment of perimeter equipment of a power station against external attacks according to an embodiment of the present invention.

[0060] Figure 2 Shown is a fuzzy membership function curve diagram in an embodiment.

[0061] Figure 3 Shown are the intermediate events and consequence events corresponding to the hydrogen production system in the embodiment.

[0062] Figure 4 Shown are the probabilities of intermediate events and consequence events corresponding to the initial events of the hydrogen production system in the embodiment. DETAILED DESCRIPTION

[0063] The following will describe in detail specific embodiments of the present invention in conjunction with specific drawings. It should be noted that the technical features or combinations of technical features described in the following embodiments should not be considered in isolation; they can be combined with each other to achieve better technical effects. In the drawings of the following embodiments, the same reference numerals appearing in each drawing represent the same features or components, which can be applied to different embodiments.

[0064] like Figure 1 As shown, an embodiment of the present invention provides a method for risk assessment of perimeter equipment of a power station against external attacks, targeting a coal-fired power station in western China. The method includes:

[0065] S1. Build a scenario database of external attacks on power station perimeter equipment and determine the initial events of cascading failure events;

[0066] External attack methods include: people, vehicles, low-altitude aircraft, floating objects or thrown objects; external attack targets include all equipment and systems around the power station; the initial event of the cascading failure event is determined through scenario construction;

[0067] The perimeter equipment of the power station mainly includes hydrogen production station, oil station, circulating water system / or air cooling system, flue gas denitrification system, flue gas desulfurization system, pulverizing system, coal transportation system, heating system, transformer and booster station.

[0068] S2. For the initial event in step S1, perform event tree chain failure simulation to determine intermediate events and consequence events under different simulation paths;

[0069] In a specific embodiment, the power station fault simulation platform is a fault simulation system developed based on STAR-90; the event tree established is a fuzzy probability event tree, and the intermediate event probabilities can be obtained through statistical analysis of simulation deduction results.

[0070] like Figure 3 As shown, taking the hydrogen production system as an example, intermediate events are events corresponding to each device in the system.

[0071] In a specific embodiment, it is assumed that the explosion of the hydrogen storage tank is the initial event, the plugging of the leak, immediate ignition, delayed ignition and VCE explosion are intermediate events, and the consequences, such as system shutdown, explosion fireball (jet fire), vapor cloud explosion (VCE), flash fire and dissipation in the air, are the consequence events. The probability of each intermediate event and consequence event is as follows: Figure 4 shown.

[0072] S3. Determine the probability of occurrence of the intermediate event and the consequence event corresponding to the cascading failure in step S2;

[0073] The probability of occurrence of the intermediate events and consequence events is obtained by statistical analysis of multiple simulation result data and / or real historical data, and can also be combined with the statistical results of reference expert opinions, taking into account objectivity and comprehensiveness.

[0074] In a specific embodiment, a quantitative calculation is performed based on the established event tree to determine the probability of occurrence of each consequence event. The method for calculating the probability of occurrence of the i-th type consequence event of a certain device is as follows:

[0075]

[0076] Where p ij is the probability of occurrence of the jth consequence event in the i-th consequence event; x ijk is the probability of occurrence of the kth intermediate event of the jth consequence event in the i-th consequence event; M is the number of consequence events included in the i-th consequence event; L is the number of intermediate events corresponding to the jth consequence event in the i-th consequence event.

[0077] S4. Select risk assessment indicators and determine the mapping relationship between the risk assessment indicators and risk levels;

[0078] In a specific embodiment, step S4 specifically includes:

[0079] S41. Using a large number of event tree cascading failure simulation results, through statistical analysis, we select casualties, equipment loss, grid impact, environmental impact, economic loss and accident recovery time as risk assessment indicators.

[0080] S42. Determine a mapping relationship between each of the risk assessment indicators and a risk level. In a specific example, the risk level is represented by a risk assessment index.

[0081] The mapping relationship can be implemented in a variety of ways, and is required to objectively reflect the corresponding relationship between risk assessment indicators and risk levels. For example, in a specific embodiment, a risk assessment indicator system commonly used in the field and a risk index quantification standard for each assessment indicator can be used, as shown in Table 1:

[0082] Table 1 Risk assessment indicator system and risk index quantification standard

[0083]

[0084] S43. Calculate the risk assessment index of a perimeter device:

[0085]

[0086] Where p i为 The probability of occurrence of type i consequence event; r ijis the quantitative value of the j-th risk assessment indicator corresponding to the i-th type of consequence event;

[0087] S44, the risk assessment index in step S43 is fuzzified using a fuzzy membership function curve, such as Figure 2 As shown;

[0088] S45. Determine the weight of each risk assessment index based on the CRITIC method;

[0089] Assume there are n devices to be evaluated and m risk assessment indicators, forming the original indicator data matrix

[0090]

[0091] Among them, RI ij Represents the value of the j-th risk assessment indicator of the i-th device to be evaluated;

[0092] Step S451: normalization of risk assessment indicators:

[0093] Normalized calculation of positive indicators:

[0094]

[0095] Normalized calculation of negative indicators:

[0096]

[0097] In the formula, RI max , RI min are the maximum and minimum values of the j-th risk assessment index respectively;

[0098] Step S452: Calculate the index comparison strength:

[0099]

[0100]

[0101] S is the standard deviation of the j-th risk assessment indicator;

[0102] Step S453: Calculation of index conflict:

[0103]

[0104] r ij represents the correlation coefficient between risk assessment indicators i and j;

[0105] Step S454: Objective weight W j calculate

[0106]

[0107]

[0108] S5. Construct a risk assessment model for perimeter equipment at the power station. Based on the risk assessment model, the mapping relationship from step S4, and the probability of occurrence of the intermediate and consequence events from step S3, determine the risk level and risk ranking for each perimeter equipment at the power station. In one specific embodiment, a decision tree risk assessment model based on evidence-based reasoning is employed. The model inputs are a fuzzified risk assessment index and an objective weight, and the model outputs the risk level and risk ranking for each perimeter equipment, implemented using an evidence-based reasoning algorithm.

[0109] In another embodiment, a fuzzy comprehensive evaluation model for power station perimeter equipment risk assessment is used. The model input is the fuzzified risk assessment index and objective weight, and the model output is the risk level and risk ranking (assessment result) of each perimeter equipment. This is achieved using a fuzzy comprehensive algorithm. Specifically:

[0110] Assume that the perimeter equipment to be evaluated is P, and its factor set U={u1,u2,…,u n}, evaluation level set V = {v1,v2,…,v m}. For each factor in U according to Figure 2 The membership function shown above gives the evaluation matrix:

[0111]

[0112] According to step S454, the objective weight set of each factor W = {w1, w2, ..., w n}

[0113] The evaluation result set

[0114] After normalization, we get B=(b1,b2,…,b m ) to determine the risk level and risk ranking (risk assessment level) of the perimeter equipment.

[0115] As a specific embodiment, the method further includes:

[0116] S6. Based on the external attack method and the risk level and risk ranking of each perimeter device of the power station obtained in step S5, security precaution measures are recommended. In one embodiment, the security precaution measures include the type and location of the installed security precaution warning device, which includes a camera and a radar.

[0117] An embodiment of the present invention provides a readable storage medium, characterized by comprising a processor and a memory, wherein the processor is connected to the memory, wherein;

[0118] The processor is configured to call and execute the program stored in the memory;

[0119] The memory is used to store the program, and the program is used to execute the above-mentioned power station perimeter equipment risk assessment method against external attacks.

[0120] The present invention establishes a connection between possible external attack methods and the perimeter equipment of the power station, realizing the full-path cascading failure simulation and deduction; the consequence events and probability of cascading failures can be determined based on the deduction results and expert opinions; the established risk assessment model based on evidence reasoning can realize risk assessment and risk ranking of the perimeter equipment of the power station, providing a basis for formulating safety precautions, and has broad application prospects.

[0121] Although several embodiments of the present invention have been described herein, those skilled in the art will appreciate that modifications may be made to the embodiments herein without departing from the spirit of the present invention. The above embodiments are merely exemplary and should not be used as limitations on the scope of the present invention.

Claims

1. A method for risk assessment of perimeter equipment of a power station against external attacks, characterized in that: The method comprises: S1. Build a scenario database of external attacks on power station perimeter equipment and determine the initial events of cascading failure events; S2. For the initial event in step S1, perform an event tree cascading failure simulation to determine the intermediate events and consequence events of each perimeter device under different simulation paths; S3. Determine the probability of occurrence of the intermediate event and the consequence event corresponding to the cascading failure in step S2; S4. Select risk assessment indicators and determine the mapping relationship between the risk assessment indicators and risk levels; S5. Construct a risk assessment model for perimeter equipment of the power station, and obtain the risk level and risk ranking of each perimeter equipment of the power station based on the risk assessment model for perimeter equipment of the power station, the mapping relationship of step S4, and the probability of occurrence of the intermediate event and the consequence event of step S3; In step S4, the risk assessment indicators include casualties, median lethal range, equipment loss, grid impact, environmental impact, economic loss, and accident recovery time; Step S4 specifically includes: S41. Using a large number of event tree cascading failure simulation results, through statistical analysis, we select casualties, equipment loss, grid impact, environmental impact, economic loss and accident recovery time as risk assessment indicators. S42. Determine a mapping relationship between each of the risk assessment indicators and the risk level; S43. Calculate the risk assessment index of a perimeter device: Where p i is the probability of occurrence of the i-th type consequence event; r ij is the quantitative value of the j-th risk assessment indicator corresponding to the i-th type of consequence event; S44, fuzzifying the risk assessment index in step S43 using a fuzzy membership function curve; S45. Determine the weight of each risk assessment index based on the CRITIC method; Assume there are n devices to be evaluated and m risk assessment indicators, forming the original indicator data matrix Among them, RI ij Indicates the value of the j-th risk assessment indicator for the i-th device to be evaluated; Step S451: normalization of risk assessment indicators: Normalized calculation of positive indicators: Normalized calculation of negative indicators: In the formula, RI max , RI min are the maximum and minimum values of the j-th risk assessment index respectively; Step S452: Calculate the index comparison strength: S j is the standard deviation of the j-th risk assessment indicator; Step S453: Calculation of index conflict: r ij represents the correlation coefficient between risk assessment index i and risk assessment index j; Step S454: Objective weight W j calculate: 。 2. The method for risk assessment of perimeter equipment of a power station against external attacks according to claim 1, characterized in that: The method further comprises: S6. Based on the external attack means and the risk level and risk ranking of each perimeter equipment of the power station obtained in step S5, security precautions are recommended.

3. The method for risk assessment of perimeter equipment of a power station against external attacks according to claim 1, characterized in that: In step S1, external attack means include: people, vehicles, low-altitude aircraft, floating objects or thrown objects; external attack targets include all power station perimeter equipment and systems; the initial event of the cascading failure event is determined through the scenario construction method.

4. The method for risk assessment of perimeter equipment of a power station against external attacks according to claim 1, characterized in that: In step S3, the probability of occurrence of the intermediate events and consequence events is obtained by statistically analyzing multiple simulation result data and / or real historical data.

5. The method for risk assessment of perimeter equipment of a power station against external attacks according to claim 1, characterized in that: In step S3, the probability of occurrence of a type i consequence event of a certain device is calculated as follows: (1) Where p ij is the probability of occurrence of the jth consequence event in the i-th consequence event; x ijk is the probability of occurrence of the kth intermediate event of the jth consequence event in the i-th type of consequence event; M is the number of consequence events contained in the i-th type of consequence events; L is the number of intermediate events corresponding to the j-th consequence event in the i-th type of consequence events.

6. The method for risk assessment of perimeter equipment of a power station against external attacks according to claim 1, characterized in that: In step S5, a decision tree risk assessment model based on evidence reasoning is adopted. The model input is the fuzzified risk assessment index and the corresponding objective weight. The model output is the risk level and risk ranking of each perimeter device, which is implemented using the evidence reasoning algorithm.

7. The method for risk assessment of perimeter equipment of a power station against external attacks according to claim 2, characterized in that: In step S6, the safety precaution measure suggestion includes the type and location of the installed safety precaution warning device, and the safety precaution warning device includes a camera and a radar.

8. A power station perimeter equipment risk assessment system for external attacks, characterized in that: The system is used to implement the method for risk assessment of perimeter equipment of a power station against external attacks according to any one of claims 1 to 7, and the system includes: A scenario database module is used to build a scenario database for external attacks on the perimeter equipment of the power station; A cascading failure simulation and deduction module is used to determine the initial event of the cascading failure event, perform event tree cascading failure simulation and deduction, determine the intermediate events and consequence events of each perimeter device under different deduction paths; and determine the probability of occurrence of the intermediate events and consequence events; The power station perimeter equipment risk assessment module is used to select risk assessment indicators, determine the mapping relationship between the risk assessment indicators and risk levels; and obtain the risk level and risk ranking of each perimeter equipment of the power station based on the mapping relationship and the probability of occurrence of the intermediate events and consequence events.

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