Capacity market risk level determination method and system based on extreme events

Abstract

The invention provides a capacity market risk level determination method and system based on an extreme event, and the method comprises the steps: obtaining risk assessment parameters of each unit of a power system in each time period within a preset time length, and determining the risk premium of each unit in each time period within the preset time length; inputting the risk assessment parameters into a pre-established capacity market risk assessment model to obtain the capacity price and capacity of each unit in each time period within a preset duration; determining the basic capacity price of each unit in the system in each time period within the preset duration; determining the total settlement amount of each unit in each time period within the preset time length according to the basic capacity price of each unit in each time period within the preset time length and the risk premium; and determining the vulnerability level of the system based on the total settlement amount of each unit in each time period within the preset duration. According to the technical scheme provided by the invention, quantitative evaluation of the risk of the power system under the extreme event is realized, and a scientific basis is provided for improving system toughness and market risk management and control.

Description

Technical Field

[0001] This application relates to the field of power market and power system risk management technology, and in particular to a method and system for determining capacity market risk levels based on extreme events. Background Technology

[0002] As climate change intensifies and the energy transition deepens, the power system faces increasing risks from extreme events. Frequent extreme weather events (such as extreme cold and heat waves), rising failure rates of aging equipment, and various other emergencies all pose serious challenges to the safe and stable operation of the power system.

[0003] From the perspective of system reliability, the traditional capacity market mechanism mainly focuses on the capacity adequacy under normal operating conditions, failing to fully consider the impact of extreme events. When the system encounters extreme weather, the availability of power generation equipment is significantly reduced, the carrying capacity of the transmission network is limited, while electricity demand may surge; equipment failures often occur concentratedly during high load periods, leading to insufficient system reserves; and sudden events may cause local or large-scale power outages, affecting system security.

[0004] From a market mechanism perspective, the existing capacity market lacks an effective assessment and price transmission mechanism for the risks of extreme events. The reliability differences of capacity resources under extreme conditions are not adequately reflected, and the risk-sharing and compensation mechanisms are imperfect, resulting in a lack of incentive for market participants to improve their emergency response capabilities. At the same time, insufficient inter-regional coordination mechanisms make it difficult to achieve optimal allocation of resources and risk sharing across regions.

[0005] From a long-term development perspective, with the increasing proportion of new energy sources and changes in electricity load characteristics, the vulnerability of the power system is further increasing. Extreme events may trigger chain reactions, leading to the rapid accumulation and spread of system risks. Therefore, there is an urgent need to propose a solution that can enhance the system's ability to cope with extreme events and strengthen the resilience of the power system through market-based means. Summary of the Invention

[0006] This application provides a method and system for determining the risk level of the capacity market based on extreme events, in order to at least solve the technical problems of the traditional capacity market mechanism lacking the ability to quantitatively assess the risks of extreme events, provide economic compensation, and classify system vulnerability, which leads to low resource allocation efficiency, insufficient market incentives, and difficulty in improving system resilience when the power system faces extreme weather, equipment failures, and emergencies.

[0007] The first aspect of this application proposes a method for determining the capacity market risk level based on extreme events, the method comprising: The risk assessment parameters of each unit in the power system are obtained for each time period within a preset time period. The parameters include extreme weather data, equipment failure data and system emergency data. The risk premium of each unit is determined for each time period within the preset time period. The risk assessment parameters are input into a pre-established capacity market risk assessment model to obtain the capacity price and capacity of each unit in the power system during each time period within a preset time period. The basic capacity price of each unit in the power system is determined based on the capacity price and capacity of each unit in the power system during each time period within the preset time period. The total settlement amount for each unit in each period within the preset time period is determined based on the base capacity price of each unit in each period within the preset time period and the risk premium. The vulnerability level of the power system is determined based on the total settlement amount of each unit in each time period within a preset time period.

[0008] Preferably, determining the risk premium for each unit in each time period within a preset duration includes: The risk premium of each unit in the power system is determined according to the risk assessment parameters of each time period within the preset time period and the preset comparison rules.

[0009] Furthermore, the process of constructing the capacity market risk assessment model includes: To minimize the risk value of the power system, an objective function is constructed for the capacity market risk assessment model. A capacity market risk assessment model is constructed by taking the constraints of power system capacity adequacy, risk response time, risk duration, regional capacity coordination, and capacity resource allocation under risk scenarios as constraints, and combining them with the objective function.

[0010] Furthermore, the objective function is calculated as follows:

[0011] In the formula, For power system risk values, For the unit exist Time-based capacity pricing, For the unit exist Time slot capacity, For the unit exist Extreme weather risk indicators for different time periods For the unit exist The degree of impact of extreme weather risks corresponding to the time period For the unit exist Equipment failure risk indicators for a given period of time For the unit exist The degree of impact of equipment failure risk corresponding to the time period. For the unit exist System emergency risk indicators for a given time period For the unit exist The degree of impact of emergencies corresponding to the time period This is the extreme weather risk weighting coefficient. This refers to the equipment failure risk weighting coefficient. The system's emergency event risk weighting coefficient is denoted by T, where T is the total number of time periods within the preset duration. This represents the total number of generating units in the power system.

[0012] Furthermore, the formula for calculating the power system capacity adequacy constraint is as follows:

[0013] In the formula, for Basic capacity requirements for a given time period for Additional capacity requirements under extreme weather risk scenarios during certain periods. for Additional capacity requirements in scenarios with risk of equipment failure during certain periods. for Additional capacity requirements in scenarios with sudden event risks during specific time periods; The formula for calculating the risk response time constraint is as follows:

[0014] In the formula, For the unit exist Response time for a given period This is the maximum allowable response time under extreme weather risk scenarios. This represents the maximum allowable response time under equipment failure risk scenarios. This refers to the maximum permissible response time under emergency risk scenarios. The formula for calculating the duration of the risk constraint is as follows:

[0015] In the formula, For the unit exist Duration of the period This refers to the minimum duration required under extreme weather risk scenarios. This refers to the minimum duration required under equipment failure risk scenarios. The minimum duration required under emergency risk scenarios; The formula for calculating the regional capacity coordination constraint is as follows:

[0016] In the formula, For the region exist Capacity requirements for different time periods For the region The collection of units within, For the region Additional capacity demand due to extreme weather during time period t For the region Additional capacity requirements due to equipment failure during time period t. For the region Additional capacity requirements due to system emergencies during time period t. Total number of regions; The capacity resource allocation constraints under the risk scenarios include: extreme weather risk assessment constraints, equipment failure risk assessment constraints, and emergency event risk assessment constraints. The calculation formula for the extreme weather risk assessment constraint is as follows:

[0017] In the formula, For extreme weather risk assessment functions, Let t be the temperature during time period t. The humidity during time period t. Let t be the wind speed during time period t. The maximum impact of extreme weather risks, This represents the system's maximum tolerance level for extreme weather risks. The calculation formula for the equipment failure risk assessment constraint is as follows:

[0018] In the formula, For equipment failure risk assessment function, For the unit age, For the unit Maintenance record values, For the unit Fault history values, To determine the maximum impact of equipment failure risk, The upper limit of the system's tolerance for equipment failure risk; The formula for calculating the emergency risk assessment constraints is as follows:

[0019] In the formula, For emergency event risk assessment functions, For the event type in time period t, The range of influence during time period t. Let be the probability of occurrence in time period t. The maximum impact of the emergency risk, This represents the upper limit of the system's tolerance for sudden event risks.

[0020] Furthermore, the formula for calculating the base capacity price of each unit in the power system for each time period within a preset duration is as follows:

[0021] In the formula, For the unit exist Basic capacity price for a given time period.

[0022] Furthermore, the formula for calculating the total settlement amount for each unit in each time period within the preset duration is as follows:

[0023] In the formula, For the unit exist Total settlement amount for the period The maximum risk compensation coefficient, For the unit exist The amount of risk premium for a given period.

[0024] Furthermore, determining the vulnerability level of the power system based on the total settlement amount of each generating unit in each time period within a preset time duration includes: The total amount of the power system is determined based on the total settlement amount of each unit in each time period within a preset time period. The total amount is compared with a preset vulnerability level threshold to determine the vulnerability level of the power system within the current preset time period; wherein, the higher the total amount, the higher the vulnerability level of the power system.

[0025] A second aspect of this application proposes a capacity market risk level determination system based on extreme events, the system comprising: The acquisition module is used to acquire risk assessment parameters of each unit in the power system for each time period within a preset time period. The parameters include extreme weather data, equipment failure data and system emergency data, and determine the risk premium of each unit for each time period within the preset time period. The input module is used to input the risk assessment parameters into a pre-established capacity market risk assessment model to obtain the capacity price and capacity of each unit in the power system during each time period within a preset time period. The first determining module is used to determine the basic capacity price of each unit in the power system for each time period within a preset time period based on the capacity price and capacity of each unit in the power system for each time period within a preset time period; The second determining module is used to determine the total settlement amount of each unit in each period within the preset time period based on the base capacity price of each unit in each period within the preset time period and the risk premium. The third determination module is used to determine the vulnerability level of the power system based on the total settlement amount of each unit in each time period within a preset time period.

[0026] A third aspect of this application provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the method described in the first aspect.

[0027] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects: This application proposes a method and system for determining capacity market risk levels based on extreme events. The method includes: acquiring risk assessment parameters for each generating unit in a power system at each time period within a preset timeframe, the parameters including extreme weather data, equipment failure data, and system emergency event data, and determining the risk premium for each generating unit at each time period within the preset timeframe; inputting the risk assessment parameters into a pre-established capacity market risk assessment model to obtain the capacity price and capacity of each generating unit in the power system at each time period within the preset timeframe; determining the base capacity price for each generating unit in the power system at each time period within the preset timeframe based on the capacity price and capacity of each generating unit in the power system at each time period within the preset timeframe; determining the total settlement amount for each generating unit at each time period within the preset timeframe based on the base capacity price and the risk premium; and determining the vulnerability level of the power system based on the total settlement amount for each generating unit at each time period within the preset timeframe. The technical solution proposed in this application realizes a quantitative assessment of power system risk under extreme events, providing a scientific basis for improving system resilience and market risk management.

[0028] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0029] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart illustrating a method for determining capacity market risk levels based on extreme events, according to an embodiment of this application; Figure 2 This is a structural diagram of a capacity market risk level determination system based on extreme events, according to one embodiment of this application. Detailed Implementation

[0030] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0031] This application proposes a method and system for determining capacity market risk levels based on extreme events. The method includes: acquiring risk assessment parameters for each generating unit in a power system at each time period within a preset timeframe, the parameters including extreme weather data, equipment failure data, and system emergency event data, and determining the risk premium for each generating unit at each time period within the preset timeframe; inputting the risk assessment parameters into a pre-established capacity market risk assessment model to obtain the capacity price and capacity of each generating unit in the power system at each time period within the preset timeframe; determining the base capacity price for each generating unit in the power system at each time period within the preset timeframe based on the capacity price and capacity of each generating unit in the power system at each time period within the preset timeframe; determining the total settlement amount for each generating unit at each time period within the preset timeframe based on the base capacity price and the risk premium; and determining the vulnerability level of the power system based on the total settlement amount for each generating unit at each time period within the preset timeframe. The technical solution proposed in this application realizes a quantitative assessment of power system risk under extreme events, providing a scientific basis for improving system resilience and market risk management.

[0032] The following description, with reference to the accompanying drawings, illustrates a method and system for determining capacity market risk levels based on extreme events, according to embodiments of this application.

[0033] Example 1 Figure 1 This is a flowchart illustrating a method for determining capacity market risk levels based on extreme events, according to an embodiment of this application. Figure 1 As shown, the method includes: Step 1: Obtain risk assessment parameters for each unit of the power system during each period within a preset time period. The parameters include extreme weather data, equipment failure data, and system emergency data. Determine the risk premium for each unit during each period within the preset time period. In this embodiment of the disclosure, the risk premium for each unit in each time period within a preset duration includes: The risk premium of each unit in the power system is determined according to the risk assessment parameters of each time period within the preset time period and the preset comparison rules.

[0034] It should be noted that the preset comparison rule, i.e., the risk price formation mechanism, is determined by the system's preset "automatic identification rule for dominant risk scenarios." This means that the quantitative results of the three types of risk indicators are compared in real time, and the corresponding risk premium calculation path is selected based on the extreme scenario corresponding to the maximum value of the risk indicator.

[0035] When the risk index value corresponding to the extreme weather scenario is at its maximum, the formula is used. Calculate the risk premium; When the risk indicator value corresponding to the equipment failure scenario is at its maximum, the formula is used. Calculate the risk premium; When the risk indicator value corresponding to the emergency event scenario is at its maximum, the formula is used. Calculate the risk premium; in, This is the premium coefficient for extreme weather risk. This is the premium factor for equipment failure risk. This is the premium coefficient for the risk of unforeseen events.

[0036] Step 2: Input the risk assessment parameters into the pre-established capacity market risk assessment model to obtain the capacity price and capacity of each unit in the power system in each time period within the preset time period; In this embodiment of the disclosure, the process of constructing the capacity market risk assessment model includes: To minimize the risk value of the power system, an objective function is constructed for the capacity market risk assessment model. A capacity market risk assessment model is constructed by taking the constraints of power system capacity adequacy, risk response time, risk duration, regional capacity coordination, and capacity resource allocation under risk scenarios as constraints, and combining them with the objective function.

[0037] It should be noted that the objective function is calculated as follows:

[0038] In the formula, For power system risk values, For the unit exist Time-based capacity pricing, For the unit exist Time slot capacity, For the unit exist Extreme weather risk indicators for different time periods For the unit exist The degree of impact of extreme weather risks corresponding to the time period For the unit exist Equipment failure risk indicators for a given period of time For the unit exist The degree of impact of equipment failure risk corresponding to the time period. For the unit exist System emergency risk indicators for a given time period For the unit exist The degree of impact of emergencies corresponding to the time period This is the extreme weather risk weighting coefficient. This refers to the equipment failure risk weighting coefficient. The system's emergency event risk weighting coefficient is denoted by T, where T is the total number of time periods within the preset duration. This represents the total number of generating units in the power system.

[0039] The formula for calculating the power system capacity adequacy constraint is as follows:

[0040] In the formula, for Basic capacity requirements for a given time period for Additional capacity requirements under extreme weather risk scenarios during certain periods. for Additional capacity requirements in scenarios with risk of equipment failure during certain periods. for Additional capacity requirements in scenarios with sudden event risks during specific time periods; The formula for calculating the risk response time constraint is as follows:

[0041] In the formula, For the unit exist Response time for a given period This is the maximum allowable response time under extreme weather risk scenarios. This represents the maximum allowable response time under equipment failure risk scenarios. This refers to the maximum permissible response time under emergency risk scenarios. The formula for calculating the duration of the risk constraint is as follows:

[0042] In the formula, For the unit exist Duration of the period This refers to the minimum duration required under extreme weather risk scenarios. This refers to the minimum duration required under equipment failure risk scenarios. The minimum duration required under emergency risk scenarios; The formula for calculating the regional capacity coordination constraint is as follows:

[0043] In the formula, For the region exist Capacity requirements for different time periods For the region The collection of units within, For the region Additional capacity demand due to extreme weather during time period t For the region Additional capacity requirements due to equipment failure during time period t. For the region Additional capacity requirements due to system emergencies during time period t. Total number of regions; The capacity resource allocation constraints under the risk scenarios include: extreme weather risk assessment constraints, equipment failure risk assessment constraints, and emergency event risk assessment constraints. The calculation formula for the extreme weather risk assessment constraint is as follows:

[0044] In the formula, For extreme weather risk assessment functions, Let t be the temperature during time period t. The humidity during time period t. Let t be the wind speed during time period t. The maximum impact of extreme weather risks, This represents the system's maximum tolerance level for extreme weather risks. The calculation formula for the equipment failure risk assessment constraint is as follows:

[0045] In the formula, For equipment failure risk assessment function, For the unit age, For the unit Maintenance record values, For the unit Fault history values, To determine the maximum impact of equipment failure risk, The upper limit of the system's tolerance for equipment failure risk; The formula for calculating the emergency risk assessment constraints is as follows:

[0046] In the formula, For emergency event risk assessment functions, For the event type in time period t, The range of influence during time period t. Let be the probability of occurrence in time period t. The maximum impact of the emergency risk, This represents the upper limit of the system's tolerance for sudden event risks.

[0047] Step 3: Determine the basic capacity price of each unit in the power system for each time period within the preset duration based on the capacity price and capacity of each unit in the power system for each time period within the preset duration; In this embodiment of the disclosure, the formula for calculating the base capacity price of each unit in the power system for each time period within a preset duration is as follows:

[0048] In the formula, For the unit exist Basic capacity price for a given time period.

[0049] Step 4: Determine the total settlement amount for each unit in each period within the preset duration based on the base capacity price and the risk premium for each unit in each period within the preset duration; In this embodiment of the disclosure, the formula for calculating the total settlement amount of each unit in each time period within a preset duration is as follows:

[0050] In the formula, For the unit exist Total settlement amount for the period The maximum risk compensation coefficient, For the unit exist The amount of risk premium for a given period.

[0051] Step 5: Determine the vulnerability level of the power system based on the total settlement amount of each unit in each time period within the preset time period.

[0052] In this embodiment of the disclosure, step 5 specifically includes: The total amount of the power system is determined based on the total settlement amount of each unit in each time period within a preset time period. The total amount is compared with a preset vulnerability level threshold to determine the vulnerability level of the power system within the current preset time period; wherein, the higher the total amount, the higher the vulnerability level of the power system.

[0053] It should be noted that the total settlement amount for each unit i in each time period t is obtained. Subsequently, the market operator completes the market-based settlement and payment process based on the results. Specifically, the system automatically generates a legally binding differentiated capacity fee settlement statement, listing the basic capacity revenue of each unit for each time period. Risk premium income (And indicate the corresponding risk scenario type, such as extreme weather, equipment failure, or emergency) and peak risk compensation. After aggregation, the total payable settlement information for the period is released to the relevant market participants through the power trading platform, automatically triggering the bank or financial system to complete the fund transfer, ensuring that capacity providers receive comprehensive benefits including risk compensation in a timely manner. At the same time, market operators, while protecting trade secrets, publicly disclose the aggregated settlement information, such as the total amount of risk premiums paid across the entire network due to various extreme events and their spatiotemporal distribution, to enhance market transparency and credibility.

[0054] After settlement, the system structurally associates the risk premium payment record of each settlement with its corresponding risk scenario assessment data and stores it in the "risk-compensation" mapping database. This database records each risk premium in detail. The corresponding key risk indicators, scenario types, occurrence times, aircraft locations, and payment amounts form a traceable and auditable data chain. Regulatory agencies can use this database to audit the reasonableness and accuracy of risk premium payments, for example, to verify whether high weather risk premiums were obtained during specific extreme weather warnings. Whether the generating units are indeed located in the affected geographical area, and their risk indicators. Does it align with meteorological data? Furthermore, long-term accumulated settlement data, after statistical analysis, can form a risk-return guideline for capacity investment, clearly revealing historical return levels under different regions and risk types. This provides data-driven references for market participants' long-term investment and renovation decisions, guiding resources towards areas with weak system resilience.

[0055] Total risk premium paid in each period Essentially, this quantifies the "resilience cost" a system incurs to withstand extreme events, serving as a key economic signal for assessing the overall vulnerability of the system. By continuously monitoring the changing trends and structural components of this cost (such as the proportion of various risk premiums), system operators and regulatory agencies can identify long-term patterns and weaknesses in risk exposure. If a certain type of risk premium is found to remain consistently high or grow rapidly, it indicates that existing market resources and mechanisms are insufficient to mitigate this type of risk. This will trigger a dynamic optimization process for market rules: for example, adjusting the corresponding risk premium coefficient. or risk loss coefficient The value of the threshold for risk scenario assessment is revised, and new resilience capacity products (such as rapid response capacity, black start service, etc.) are designed and introduced to continuously improve the market's adaptability to extreme events and the overall resilience of the system through mechanism iteration.

[0056] This application proposes a method for determining the capacity market risk level based on extreme events. With the goal of minimizing system risk, it establishes a multi-dimensional risk assessment system encompassing extreme weather, equipment failures, and system emergencies, enabling accurate identification and quantitative assessment of different types of extreme events. This method constructs constraints on system emergency capacity demand and capacity resource allocation under risk scenarios, and designs a corresponding risk price formation mechanism, ensuring that market prices accurately reflect the system risk level under extreme events. Through the organic combination of the risk assessment model and the price mechanism, the method improves the power system's ability to cope with extreme events, enhances system operational resilience, and is of great significance for ensuring power supply reliability and improving system safety.

[0057] In summary, the capacity market risk level determination method proposed in this embodiment, based on extreme events, enables a quantitative assessment of power system risks under extreme events, providing a scientific basis for improving system resilience and market risk management.

[0058] Example 2 Figure 2 Here is a structural diagram of a capacity market risk level determination system based on extreme events, according to an embodiment of this application. Figure 2 As shown, the system includes: The acquisition module 100 is used to acquire risk assessment parameters of each unit in the power system for each period within a preset time period. The parameters include extreme weather data, equipment failure data and system emergency data, and determine the risk premium of each unit for each period within the preset time period. The input module 200 is used to input the risk assessment parameters into a pre-established capacity market risk assessment model to obtain the capacity price and capacity of each unit in the power system during each time period within a preset time period. The first determining module 300 is used to determine the basic capacity price of each unit in the power system for each time period within a preset time period based on the capacity price and capacity of each unit in the power system for each time period within a preset time period. The second determining module 400 is used to determine the total settlement amount of each unit in each period within the preset time period based on the base capacity price of each unit in each period within the preset time period and the risk premium. The third determination module 500 is used to determine the vulnerability level of the power system based on the total settlement amount of each unit in each time period within a preset time period.

[0059] In this embodiment of the disclosure, the acquisition module 100 is further configured to: The risk premium of each unit in the power system is determined according to the risk assessment parameters of each time period within the preset time period and the preset comparison rules.

[0060] In this embodiment of the disclosure, the process of constructing the capacity market risk assessment model includes: To minimize the risk value of the power system, an objective function is constructed for the capacity market risk assessment model. A capacity market risk assessment model is constructed by taking the constraints of power system capacity adequacy, risk response time, risk duration, regional capacity coordination, and capacity resource allocation under risk scenarios as constraints, and combining them with the objective function.

[0061] It should be noted that the objective function is calculated as follows:

[0062] In the formula, For power system risk values, For the unit exist Time-based capacity pricing, For the unit exist Time slot capacity, For the unit exist Extreme weather risk indicators for different time periods For the unit exist The degree of impact of extreme weather risks corresponding to the time period For the unit exist Equipment failure risk indicators for a given period of time For the unit exist The degree of impact of equipment failure risk corresponding to the time period. For the unit exist System emergency risk indicators for a given time period For the unit exist The degree of impact of emergencies corresponding to the time period This is the extreme weather risk weighting coefficient. This refers to the equipment failure risk weighting coefficient. The system's emergency event risk weighting coefficient is denoted by T, where T is the total number of time periods within the preset duration. This represents the total number of generating units in the power system.

[0063] The formula for calculating the power system capacity adequacy constraint is as follows:

[0064] In the formula, for Basic capacity requirements for a given time period for Additional capacity requirements under extreme weather risk scenarios during certain periods. for Additional capacity requirements in scenarios with risk of equipment failure during certain periods. for Additional capacity requirements in scenarios with sudden event risks during specific time periods; The formula for calculating the risk response time constraint is as follows:

[0065] In the formula, For the unit exist Response time for a given period This is the maximum allowable response time under extreme weather risk scenarios. This represents the maximum allowable response time under equipment failure risk scenarios. This refers to the maximum permissible response time under emergency risk scenarios. The formula for calculating the duration of the risk constraint is as follows:

[0066] In the formula, For the unit exist Duration of the period This refers to the minimum duration required under extreme weather risk scenarios. This refers to the minimum duration required under equipment failure risk scenarios. The minimum duration required under emergency risk scenarios; The formula for calculating the regional capacity coordination constraint is as follows:

[0067] In the formula, For the region exist Capacity requirements for different time periods For the region The collection of units within, For the region Additional capacity demand due to extreme weather during time period t For the region Additional capacity requirements due to equipment failure during time period t. For the region Additional capacity requirements due to system emergencies during time period t. Total number of regions; The capacity resource allocation constraints under the risk scenarios include: extreme weather risk assessment constraints, equipment failure risk assessment constraints, and emergency event risk assessment constraints. The calculation formula for the extreme weather risk assessment constraint is as follows:

[0068] In the formula, For extreme weather risk assessment functions, Let t be the temperature during time period t. The humidity during time period t. Let t be the wind speed during time period t. The maximum impact of extreme weather risks, This represents the system's maximum tolerance level for extreme weather risks. The calculation formula for the equipment failure risk assessment constraint is as follows:

[0069] In the formula, For equipment failure risk assessment function, For the unit age, For the unit Maintenance record values, For the unit Fault history values, To determine the maximum impact of equipment failure risk, The upper limit of the system's tolerance for equipment failure risk; The formula for calculating the emergency risk assessment constraints is as follows:

[0070] In the formula, For emergency event risk assessment functions, For the event type in time period t, The range of influence during time period t. Let be the probability of occurrence in time period t. The maximum impact of the emergency risk, This represents the upper limit of the system's tolerance for sudden event risks.

[0071] It should be noted that the calculation formula for the base capacity price of each unit in the power system for each time period within the preset duration is as follows:

[0072] In the formula, For the unit exist Basic capacity price for a given time period.

[0073] It should be noted that the formula for calculating the total settlement amount for each unit in each time period within the preset duration is as follows:

[0074] In the formula, For the unit exist Total settlement amount for the period The maximum risk compensation coefficient, For the unit exist The amount of risk premium for a given period.

[0075] In this embodiment of the disclosure, the third determining module 500 is further configured to: The total amount of the power system is determined based on the total settlement amount of each unit in each time period within a preset time period. The total amount is compared with a preset vulnerability level threshold to determine the vulnerability level of the power system within the current preset time period; wherein, the higher the total amount, the higher the vulnerability level of the power system.

[0076] In summary, the capacity market risk level determination system based on extreme events proposed in this embodiment realizes the quantitative assessment of power system risks under extreme events, and provides a scientific basis for improving system resilience and market risk management.

[0077] Example 3 To implement the above embodiments, this disclosure also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in Embodiment 1.

[0078] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0079] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0080] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for determining the capacity market risk level based on extreme events, characterized in that, The method includes: The risk assessment parameters of each unit in the power system are obtained for each time period within a preset time period. The parameters include extreme weather data, equipment failure data and system emergency data. The risk premium of each unit is determined for each time period within the preset time period. The risk assessment parameters are input into a pre-established capacity market risk assessment model to obtain the capacity price and capacity of each unit in the power system during each time period within a preset time period. The basic capacity price of each unit in the power system is determined based on the capacity price and capacity of each unit in the power system during each time period within the preset time period. The total settlement amount for each unit in each period within the preset time period is determined based on the base capacity price of each unit in each period within the preset time period and the risk premium. The vulnerability level of the power system is determined based on the total settlement amount of each unit in each time period within a preset time period.

2. The method as described in claim 1, characterized in that, The determination of the risk premium for each unit in each time period within a preset duration includes: The risk premium of each unit in the power system is determined according to the risk assessment parameters of each time period within the preset time period and the preset comparison rules.

3. The method as described in claim 2, characterized in that, The process of constructing the capacity market risk assessment model includes: To minimize the risk value of the power system, an objective function is constructed for the capacity market risk assessment model. A capacity market risk assessment model is constructed by taking power system capacity adequacy constraints, risk response time constraints, risk duration constraints, regional capacity coordination constraints, and capacity resource allocation constraints under risk scenarios as constraints, and combining them with the objective function.

4. The method as described in claim 3, characterized in that, The objective function is calculated as follows: In the formula, For power system risk values, For the unit exist Time-based capacity pricing, For the unit exist Time slot capacity, For the unit exist Extreme weather risk indicators for different time periods For the unit exist The degree of impact of extreme weather risks corresponding to the time period For the unit exist Equipment failure risk indicators for a given period of time For the unit exist The degree of impact of equipment failure risk corresponding to the time period. For the unit exist System emergency risk indicators for a given time period For the unit exist The degree of impact of emergencies corresponding to the time period This is the extreme weather risk weighting coefficient. This refers to the equipment failure risk weighting coefficient. The system's emergency event risk weighting coefficient is denoted by T, where T is the total number of time periods within the preset duration. This represents the total number of generating units in the power system.

5. The method as described in claim 4, characterized in that, The formula for calculating the power system capacity adequacy constraint is as follows: In the formula, for Basic capacity requirements for a given time period for Additional capacity requirements under extreme weather risk scenarios during certain periods. for Additional capacity requirements in scenarios with risk of equipment failure during certain periods. for Additional capacity requirements in scenarios with sudden event risks during specific time periods; The formula for calculating the risk response time constraint is as follows: In the formula, For the unit exist Response time for a given period This is the maximum allowable response time under extreme weather risk scenarios. This represents the maximum allowable response time under equipment failure risk scenarios. This refers to the maximum permissible response time under emergency risk scenarios. The formula for calculating the duration of the risk constraint is as follows: In the formula, For the unit exist Duration of the period This refers to the minimum duration required under extreme weather risk scenarios. This refers to the minimum duration required under equipment failure risk scenarios. The minimum duration required under emergency risk scenarios; The formula for calculating the regional capacity coordination constraint is as follows: In the formula, For the region exist Capacity requirements for different time periods For the region The collection of units within, For the region Additional capacity demand due to extreme weather during time period t For the region Additional capacity requirements due to equipment failure during time period t. For the region Additional capacity requirements due to system emergencies during time period t. Total number of regions; The capacity resource allocation constraints under the risk scenarios include: extreme weather risk assessment constraints, equipment failure risk assessment constraints, and emergency event risk assessment constraints. The calculation formula for the extreme weather risk assessment constraint is as follows: In the formula, For extreme weather risk assessment functions, Let t be the temperature during time period t. The humidity during time period t. Let t be the wind speed during time period t. The maximum impact of extreme weather risks, This represents the system's maximum tolerance level for extreme weather risks. The calculation formula for the equipment failure risk assessment constraint is as follows: In the formula, For equipment failure risk assessment function, For the unit age, For the unit Maintenance record values, For the unit Fault history values, To determine the maximum impact of equipment failure risk, The upper limit of the system's tolerance for equipment failure risk; The formula for calculating the emergency risk assessment constraints is as follows: In the formula, For emergency event risk assessment functions, For the event type in time period t, The range of influence during time period t. Let be the probability of occurrence in time period t. The maximum impact of the emergency risk, This represents the upper limit of the system's tolerance for sudden event risks.

6. The method as described in claim 5, characterized in that, The formulas for calculating the base capacity price of each unit in the power system for each time period within a preset duration are as follows: In the formula, For the unit exist Basic capacity price for a given time period.

7. The method as described in claim 6, characterized in that, The formula for calculating the total settlement amount for each unit in each time period within the preset duration is as follows: In the formula, For the unit exist Total settlement amount for the period The maximum risk compensation coefficient, For the unit exist The amount of risk premium for a given period.

8. The method as described in claim 7, characterized in that, The determination of the vulnerability level of the power system based on the total settlement amount of each generating unit in each time period within a preset time period includes: The total amount of the power system is determined based on the total settlement amount of each unit in each time period within a preset time period. The total amount is compared with a preset vulnerability level threshold to determine the vulnerability level of the power system within the current preset time period; wherein, the higher the total amount, the higher the vulnerability level of the power system.

9. A capacity market risk level determination system based on extreme events, characterized in that, The system includes: The acquisition module is used to acquire risk assessment parameters of each unit in the power system for each time period within a preset time period. The parameters include extreme weather data, equipment failure data and system emergency data, and determine the risk premium of each unit for each time period within the preset time period. The input module is used to input the risk assessment parameters into a pre-established capacity market risk assessment model to obtain the capacity price and capacity of each unit in the power system during each time period within a preset time period. The first determining module is used to determine the basic capacity price of each unit in the power system for each time period within a preset time period based on the capacity price and capacity of each unit in the power system for each time period within a preset time period; The second determining module is used to determine the total settlement amount of each unit in each period within the preset time period based on the base capacity price of each unit in each period within the preset time period and the risk premium. The third determination module is used to determine the vulnerability level of the power system based on the total settlement amount of each unit in each time period within a preset time period.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-8.

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