A method for quantitatively measuring and calculating the power supply risk early warning level of southwest power grid based on flexibility adequacy probability evaluation

Abstract

The application discloses a kind of southwest power grid risk early warning grade quantification measurement method based on flexibility adequacy probability evaluation, steps include: step 1) calculating power grid risk index;Step 2) calculating expected flexibility gap index, flexibility deficiency probability;Step 3) calculating the risk quantification value caused by ATC deficiency in channel level;Step 4) the expected flexibility gap index and the risk quantification value caused by ATC deficiency in channel level are written into power grid risk index set, and the updated power grid risk index set is standardized, to obtain power grid risk grade;Step 5) outputting early warning output data set for dispatch, market and operation management.The application realizes the unified, comparable, publishable hierarchical early warning of provincial and regional power grid risk, supports power grid in multiple provinces, multiple channels, multiple scene supply coordination and dispatch optimization.

Description

Technical Field

[0001] This invention relates to the field of power grid safe operation, specifically a quantitative calculation method for the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy. Background Technology

[0002] The Southwest region is characterized by a high proportion of renewable energy installed capacity, strong seasonality in water and meteorological conditions, and a power grid receiving-end structure featuring "multiple power sources, long-distance transmission, and significant differences in electricity consumption across provinces." This results in large fluctuations in the power grid's demand for flexibility resources such as peak shaving, frequency regulation, reserves, and demand response at different times. Traditional power grid reliability or adequacy assessments primarily focus on installed capacity, load levels, and the safety margin of key transmission lines. While these assessments reflect the static availability of power ("whether there is electricity" and "whether the lines can transmit it"), they fail to depict the dynamic flexibility guarantee level of "being able to mobilize, withstand, and respond in time" under scenarios involving high proportions of renewable energy, inter-provincial consumption, and time-of-use support. To support supply guarantee decisions coordinated at the provincial or even inter-provincial levels, it is necessary to aggregate and assess the flexibility adjustment capabilities of multiple aspects, including the power source side, energy storage side, and load side. Furthermore, it is crucial to comprehensively predict uncertain information such as load, electricity prices, weather, and renewable energy output in a scenario-based manner, evaluating "flexibility adequacy" in a probabilistic sense. This will ultimately form a quantifiable, tiered, and predictable characterization of supply guarantee risks.

[0003] Existing research on power grid risk early warning and power supply security mainly follows two approaches: one is an early warning method based on traditional reliability / adequacy indicators, using techniques such as LOLP, EENS, and network N-1 security verification to give the risk level under a certain operating mode. However, these are mostly deterministic or single-scenario assessments, lacking a quantitative mapping of "flexibility gap probability - early warning level," making it difficult to directly guide the daily power supply security early warning of provincial power grids. The other approach focuses on the transmission capacity assessment and trading space analysis of large or regional power grids, determining tradable electricity or inter-regional support capabilities through power flow calculations, ATC / transmission margin measurements, etc. However, most studies treat channels as fixed boundaries, failing to incorporate the flexibility aggregation capabilities of provinces (or entities) within a province, as well as the actual mutual support capabilities between provinces, into the same quantitative early warning framework. In other words, existing solutions either lean towards "capacity + reliability," making it difficult to reflect flexibility scenario fluctuations; or they only address "whether inter-provincial channels are available," without addressing "how much available flexibility can be aggregated behind the channels and with what probability it can be guaranteed." Therefore, there is a need for a quantitative calculation technology for power grid supply guarantee risk warning levels that can simultaneously address provincial-level flexibility aggregation, characterize the cross-provincial transaction space in the southwest region, and take the probability of flexibility adequacy as the core. Summary of the Invention

[0004] The purpose of this invention is to provide a quantitative calculation method for the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, including the following steps:

[0005] Step 1) Calculate the power grid supply guarantee risk indicators based on the power grid component failure probability model and the power grid accident occurrence probability model, thereby constructing a power grid supply guarantee risk indicator set;

[0006] Step 2) Conduct a probability assessment of the adequacy of the power grid and a measurement of its flexibility, and calculate the expected flexibility gap index and the probability of insufficient flexibility;

[0007] Step 3) Based on the expected quantile, divide the cross-provincial trading space and calculate the quantitative value of risk caused by insufficient ATC at the channel level;

[0008] Step 4) Write the expected flexibility gap index and the risk quantification value caused by insufficient ATC at the channel level into the power grid supply guarantee risk index set, and standardize the updated power grid supply guarantee risk index set to obtain the power grid supply guarantee risk level.

[0009] Step 5) Based on the power grid supply risk level, the probability of insufficient flexibility, and the updated power grid supply risk indicator set, output an early warning output dataset for dispatching, market and operation management.

[0010] Furthermore, the fault probability model for power grid components is shown below:

[0011] (1)

[0012] in: This indicates normal weather. Indicates severe weather. This indicates the component failure rate during alternating weather conditions. This refers to the annual operating hours of the component under normal conditions. This is the duration of normal weather. For the duration of severe weather; Duration of alternating weather; The proportion of failures occurring during severe weather to the total number of failures throughout the year; The proportion of faults occurring under alternating weather conditions to the total number of faults throughout the year; This is the average operating time of the component before it fails. Failure rate of power system components related to weather.

[0013] Furthermore, the probability model for power grid accidents is shown below:

[0014] (2)

[0015] (3)

[0016] In the formula, For inclusion The system state obtained by sampling the power system of each component; This represents the total number of samples. Accident status Number of times it appears; For any element in a power system The probability of service interruption; For components Random numbers obtained from sampling; This refers to the component state corresponding to this sampling.

[0017] Furthermore, the power grid supply risk indicators include load shedding risk indicators, overload risk indicators, and voltage over-limit risk indicators;

[0018] Among them, the risk index of load loss ; For the first The probability of an accident occurring. This indicates the severity of system load loss under this condition;

[0019] Overload risk indicators ; This indicates the severity of the overload under this condition;

[0020] Voltage over-limit risk indicators ; This indicates the severity of voltage exceedance under this condition.

[0021] Furthermore, the expected flexibility gap indicator is as follows:

[0022] (4)

[0023] In the formula, For the scene The probability of occurrence; ; Representing a scene The unmet flexibility capacity in the next time period t;

[0024] Unmet flexibility capacity ; The flexibility requirement for time period t; To provide flexible supply capacity for time period t; Power can be adjusted up or down for equivalent flexibility.

[0025] Furthermore, the cross-provincial trading space includes a safe trading zone, an early warning trading zone, and a mutual assistance trading zone;

[0026] The safe trading zone, early warning trading zone, and mutual assistance trading zone are divided according to the cross-provincial trading volume Q of the channel in time period t;

[0027] Among them, the secure trading zone meets the requirements. ; This represents the maximum transaction volume that can be accommodated at a given confidence level. It is the inverse function of the empirical distribution function of the sample. Desired quantile parameters; available transmission capacity ; For transmission reliability margin, This is the amount of reserve space available for mutual assistance. For existing contract transmission volume;

[0028] Early warning trading zone meets ;

[0029] Mutual aid trading zone meets ;

[0030] When the available transmission capacity is obtained from real-time or short-term forecasts Less than the release index At that time, the mutual assistance allocation or quota adjustment mechanism will be based on the gap in the channel trading space. trigger.

[0031] Furthermore, the quantification of risk caused by insufficient ATC at the channel level. As shown below:

[0032] (5)

[0033] In the formula, when hour, ; Available transmission capacity is obtained from real-time or short-term forecasts.

[0034] Furthermore, step 4, which involves standardizing the updated power grid supply guarantee risk indicator set, includes the following steps:

[0035] Step 4.1) Set the perception scale for risk indicators and the range of risk levels;

[0036] Step 4.2) Establish a judgment matrix based on the perceptual scale, that is:

[0037] (6)

[0038] Step 4.3) Perform eigenvalue analysis on the judgment matrix, find the eigenvector corresponding to the largest eigenvalue, and normalize it to obtain the weight vector. ;

[0039] Step 4.4) Combine the risk indicators and weights to obtain the comprehensive risk assessment value. ; For risk indicator vectors, This is the weight vector;

[0040] Step 4.5) Calculate the comprehensive risk assessment value. Match the risk level range to determine the current risk level of the power system;

[0041] The risk levels are divided into four levels. Level 1 risk level means that the power grid is in a normal or controllable state; Level 2 risk level means that the power grid operation has flexibility or channel constraints; Level 3 risk level means that the power grid's supply capacity is limited and inter-provincial mutual assistance or intra-provincial start-up and shutdown need to be arranged in advance; Level 4 risk level means that the power grid supply risk is high and emergency and load management measures need to be activated.

[0042] Furthermore, steps 1-4 are executed periodically. When the risk level changes, a new early warning level is simultaneously issued to the provincial and regional dispatch terminals, and step 5 is executed.

[0043] Furthermore, in step 5, the early warning output dataset for scheduling, market and operation management includes the power grid supply risk level, the probability of insufficient flexibility, the updated power grid supply risk indicator set, and the remaining risk of the regional / interconnected system after mutual assistance.

[0044] The causes of the warning include insufficient flexibility, limited channels, and voltage / overload risks.

[0045] Among them, real-time / predictive Less than When the risk quantification value caused by insufficient ATC at the channel level exceeds the threshold or accounts for the largest proportion, the warning cause is channel restriction.

[0046] When the voltage over-limit risk indicator or overload risk indicator exceeds the threshold / contributes the most, the warning is issued because of voltage / overload risk.

[0047] When flexibility-related indicators exceed the threshold or have the greatest contribution, the warning is triggered by insufficient flexibility.

[0048] Available inter-provincial mutual assistance capacity .

[0049] The technical effect of this invention is beyond doubt. This invention constructs a quantitative calculation technology for the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy. By establishing a provincial power grid flexible adjustment capability aggregation assessment model and combining it with the panoramic prediction of flexibility demand, the probability of flexibility adequacy at the provincial level is obtained.

[0050] This invention proposes a method for characterizing the inter-provincial trading space within flexible resource zones in the Southwest region, quantifying inter-provincial mutual assistance capabilities into a capability boundary for participating in supply guarantee.

[0051] This invention designs quantitative rules and hierarchical thresholds that map sufficiency probability to early warning levels, thereby achieving unified, comparable, and publishable hierarchical early warnings for provincial and regional power grid supply risks, supporting power grid supply coordination and scheduling optimization in multiple provinces, multiple channels, and multiple scenarios. Attached Figure Description

[0052] Figure 1 Basic steps for adequacy assessment;

[0053] Figure 2 This is a flowchart of a quantitative method for early warning of power supply risks in the Southwest region based on probability assessment of flexibility adequacy. Detailed Implementation

[0054] The present invention will be further described below with reference to embodiments, but it should not be construed that the scope of the present invention is limited to the following embodiments. Various substitutions and modifications made based on ordinary technical knowledge and common practices in the art without departing from the above-described technical concept of the present invention should be included within the scope of protection of the present invention.

[0055] Example 1:

[0056] See Figures 1 to 2 A quantitative calculation method for the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy includes the following steps:

[0057] Step 1) Calculate the power grid supply guarantee risk indicators based on the power grid component failure probability model and the power grid accident occurrence probability model, thereby constructing a power grid supply guarantee risk indicator set;

[0058] Step 2) Conduct a probability assessment of the adequacy of the power grid and a measurement of its flexibility, and calculate the expected flexibility gap index and the probability of insufficient flexibility;

[0059] Step 3) Based on the expected quantile, divide the cross-provincial trading space and calculate the quantitative value of risk caused by insufficient ATC at the channel level;

[0060] Step 4) Write the expected flexibility gap index and the risk quantification value caused by insufficient ATC at the channel level into the power grid supply guarantee risk index set, and standardize the updated power grid supply guarantee risk index set to obtain the power grid supply guarantee risk level.

[0061] Step 5) Based on the power grid supply risk level, the probability of insufficient flexibility, and the updated power grid supply risk indicator set, output an early warning output dataset for dispatching, market and operation management.

[0062] Example 2:

[0063] A quantitative calculation method for the risk warning level of power supply guarantee in the Southwest Power Grid based on the probability assessment of flexibility adequacy is provided. The technical content is the same as in Example 1. Furthermore, the failure probability model of power grid components is as follows:

[0064] (1)

[0065] in: This indicates normal weather. Indicates severe weather. This indicates the component failure rate during alternating weather conditions. This refers to the annual operating hours of the component under normal conditions. This is the duration of normal weather. For the duration of severe weather; Duration of alternating weather; The proportion of failures occurring during severe weather to the total number of failures throughout the year; The proportion of faults occurring under alternating weather conditions to the total number of faults throughout the year; This is the average operating time of the component before it fails. Failure rate of power system components related to weather.

[0066] Example 3:

[0067] A quantitative calculation method for the early warning level of power supply guarantee risk in the Southwest Power Grid based on the probability assessment of flexibility adequacy, with the same technical content as any one of Examples 1-2, further wherein the probability model for the occurrence of power grid accidents is as follows:

[0068] (2)

[0069] (3)

[0070] In the formula, For inclusion The system state obtained by sampling the power system of each component; This represents the total number of samples. Accident status Number of times it appears; For any element in a power system The probability of service interruption; For components Random numbers obtained from sampling; This refers to the component state corresponding to this sampling.

[0071] Example 4:

[0072] A quantitative calculation method for the early warning level of power supply guarantee risk in Southwest China Power Grid based on the probability assessment of flexibility adequacy, with the same technical content as any one of Examples 1-3. Further, the power grid supply guarantee risk indicators include load shedding risk indicators, overload risk indicators, and voltage over-limit risk indicators.

[0073] Among them, the risk index of load loss ; For the first The probability of an accident occurring. This indicates the severity of system load loss under this condition;

[0074] Overload risk indicators ; This indicates the severity of the overload under this condition;

[0075] Voltage over-limit risk indicators ; This indicates the severity of voltage exceedance under this condition.

[0076] Example 5:

[0077] A quantitative calculation method for the risk warning level of power supply guarantee in Southwest China's power grid, based on probability assessment of flexibility adequacy, is provided. The technical content is the same as any one of Examples 1-4. Further, the expected flexibility gap index is as follows:

[0078] (4)

[0079] In the formula, For the scene The probability of occurrence (or sample weight) satisfies Under this weighting, the severity of the gap in each scenario is assessed. The expected flexibility gap index is obtained by weighted summation. . Representing a scene The unmet flexibility capacity (gap) in the next time period t is calculated as follows:

[0080] in For the flexibility requirements of time period t, To provide flexibility in time period t, and , , The equivalent flexibility is adjusted by increasing / decreasing the power, respectively.

[0081] Unmet flexibility capacity ; The flexibility requirement for time period t; To provide flexible supply capacity for time period t; Power can be adjusted up or down for equivalent flexibility.

[0082] Example 6:

[0083] A quantitative calculation method for the risk warning level of Southwest Power Grid based on the probability assessment of flexibility adequacy, with the same technical content as any one of Examples 1-5, further comprising a safe trading zone, a warning trading zone, and a mutual assistance trading zone for cross-provincial transactions;

[0084] In the cross-provincial trading space division, Q represents the cross-provincial trading volume (or planned trading power) of the channel in time period t, and based on this, the safe trading zone, the early warning trading zone, and the mutual assistance trading zone are defined; among them For a given confidence / quantile parameter The maximum transaction volume that can be accommodated.

[0085] When the available transmission capacity is obtained from real-time or short-term forecasts Below the release target When there is a shortage of trading space in a channel, it can be characterized by "gap volume". Output quantity and trigger mechanisms such as mutual aid allocation or quota adjustment accordingly.

[0086] Among them, the secure trading zone meets the requirements. ; This represents the maximum transaction volume that can be accommodated at a given confidence level. It is the inverse function of the empirical distribution function of the sample. Desired quantile parameters; available transmission capacity ; For transmission reliability margin, This is the amount of reserve space available for mutual assistance. For existing contract transmission volume;

[0087] Early warning trading zone meets ;

[0088] Mutual aid trading zone meets ;

[0089] When the available transmission capacity is obtained from real-time or short-term forecasts Less than the release target At that time, the mutual assistance allocation or quota adjustment mechanism will be based on the gap in the channel trading space. trigger.

[0090] Example 7:

[0091] A quantitative calculation method for the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, with the same technical content as any one of embodiments 1-6, further including the quantitative value of the risk caused by insufficient ATC at the channel level. As shown below:

[0092] (5)

[0093] In the formula, when hour, ; Available transmission capacity is obtained from real-time or short-term forecasts.

[0094] Example 8:

[0095] A quantitative calculation method for the early warning level of power supply guarantee risk in Southwest China's power grid based on probability assessment of flexibility adequacy, with technical content identical to any one of embodiments 1-7, further comprising the following steps in step 4: standardizing the updated power grid supply guarantee risk indicator set.

[0096] Step 4.1) Set the perception scale for risk indicators and the range of risk levels;

[0097] Step 4.2) Establish a judgment matrix based on the perceptual scale, that is:

[0098] (6)

[0099] Step 4.3) Perform eigenvalue analysis on the judgment matrix, find the eigenvector corresponding to the largest eigenvalue, and normalize it to obtain the weight vector. ;

[0100] Step 4.4) Combine the risk indicators and weights to obtain the comprehensive risk assessment value. ; For risk indicator vectors, This is the weight vector;

[0101] Step 4.5) Calculate the comprehensive risk assessment value. Match the risk level range to determine the current risk level of the power system;

[0102] The risk levels are divided into four levels. Level 1 risk level means that the power grid is in a normal or controllable state; Level 2 risk level means that the power grid operation has flexibility or channel constraints; Level 3 risk level means that the power grid's supply capacity is limited and inter-provincial mutual assistance or intra-provincial start-up and shutdown need to be arranged in advance; Level 4 risk level means that the power grid supply risk is high and emergency and load management measures need to be activated.

[0103] Example 9:

[0104] A quantitative calculation method for the risk warning level of Southwest Power Grid based on the probability assessment of flexibility adequacy is provided. The technical content is the same as any one of Examples 1-8. Further, steps 1-4 are executed periodically. When the risk level changes, a new warning level is issued to the provincial and regional dispatching terminals at the same time, and step 5 is executed.

[0105] Example 10:

[0106] A quantitative calculation method for the early warning level of power supply guarantee risk in Southwest China Power Grid based on the probability assessment of flexibility adequacy, with the same technical content as any one of embodiments 1-9. Further, in step 5, the early warning output dataset for dispatching, market and operation management includes the power grid supply guarantee risk level, the probability of insufficient flexibility, the updated power grid supply guarantee risk index set, and the remaining risk of the regional / interconnected system after mutual assistance.

[0107] The causes of the warning include insufficient flexibility, limited channels, and voltage / overload risks.

[0108] The comprehensive early warning value / risk level, early warning cause, and "cross-provincial transaction capability indicator" recalculated after mutual assistance are included. (Risk ATC release value) / or its associated trading space tier boundaries (the dividing line between security / early warning / mutual aid zones), which can be output simultaneously if necessary. As a scenario quantity for real-time / predicted available transmission capacity, the list of available intra-provincial flexibility resources and available inter-provincial mutual assistance capacity can be called upon;

[0109] Channel limitations: When real-time / predictive Below the published value (Triggering mutual assistance), or when the “ATC insufficient risk quantification value (5)” exceeds the threshold / proportion to the maximum, the cause is channel restriction. Voltage / overload risk: when the “voltage limit exceedance risk indicator” or “overload risk indicator” exceeds the threshold / contributes to the maximum, the cause is voltage / overload risk. Insufficient flexibility: when flexibility indicators such as “probability” or “expected flexibility gap” exceed the threshold / contribute to the maximum, the cause is insufficient flexibility.

[0110] Available inter-provincial mutual assistance capacity .

[0111] Example 11:

[0112] A quantitative calculation method for the early warning level of power supply guarantee risk in the Southwest Power Grid based on the probability assessment of flexibility adequacy includes the following steps:

[0113] Step 1: Calculation of comprehensive early warning indicators based on risk assessment results

[0114] The power grid is a complex system affected by various factors and uncertainties. To accurately identify and quickly address its supply status, it is essential to select reasonable, quantifiable, and tiered early warning methods. Considering the characteristics of the Southwest China power grid—high proportion of renewable energy, inter-provincial mutual assistance, and large fluctuations in flexibility demand—this patent applies a quantitative early warning method to the early warning of power grid supply risks. By constructing a two-tiered quantitative early warning process at the provincial and regional levels, it achieves effective monitoring and tiered alerts for changes in the power grid's operating status, flexibility adequacy, and inter-provincial trading space.

[0115] Failure rate of power grid system components

[0116] The main components of a power system include wind turbines, conventional generators, transformers, and transmission lines. To calculate the failure rate of each component, historical failure data and corresponding weather data for the corresponding periods need to be collected. The IEEE 346 standard classifies weather conditions into three categories: normal weather, severe weather, and alternating weather. The failure rate of weather-related power system components over a year can be described using these three weather conditions as follows:

[0117] (1)

[0118] in: This indicates normal weather. Indicates severe weather. This indicates the component failure rate during alternating weather conditions. This refers to the annual operating hours of the component under normal conditions. Duration of normal weather (h); Duration of severe weather (h); Duration of alternating weather (h); The proportion of failures occurring during severe weather to the total number of failures throughout the year; The proportion of faults occurring under alternating weather conditions to the total number of faults throughout the year; This represents the average operating time of the component before it fails. The above formula means: first, divide the year into three typical weather periods; then, based on the duration of each weather period and the proportion of failures during that period, calculate the annual baseline failure rate. By weighting the components, we can obtain the component failure rate under different weather conditions.

[0119] Calculation of the probability of power grid accidents

[0120] For any element in a power system Let its probability of shutdown be... If the random number obtained from sampling this component is Then the component state corresponding to this sampling for

[0121] (2)

[0122] For containing A power system with 100 components, whose system state is represented by a single sample is as follows:

[0123] After obtaining the sampled state of the system, analysis methods such as power flow calculations can be used to determine whether the system is in a fault state. The fault states handled in this paper can include any one or more of the following: underload, overload, or voltage exceeding limits. When the number of samples is large enough, the frequency of occurrence of the fault state can approximate its probability of occurrence. If... If we represent an accident state, then its probability of occurrence is...

[0124] (3)

[0125] in, This represents the total number of samples. Accident status Number of times it appears.

[0126] Risk indicator calculation

[0127] Based on the power grid component failure probability and power grid accident occurrence probability model, the risk index can be expressed as:

[0128] 1. Loss of Load Risk Indicators

[0129] This is used to evaluate the risk of power system load loss due to electrical islanding caused by power system faults or the activation of automatic devices, and proposes an expected power system load loss index. In the formula, For the first The probability of an accident occurring. This indicates the severity of system load loss under this condition.

[0130] 2. Overload Risk Indicators

[0131] Line overload occurs when the transmitted power exceeds its maximum tolerance, causing equipment damage and partial load shedding. In severe cases, it can lead to power system disconnection or even collapse, resulting in significant economic losses and social impact. The overload risk index is defined as follows: In the formula, This indicates the severity of the overload under this condition.

[0132] 3. Voltage Over-Limit Risk Indicators

[0133] The voltage over-limit risk index reflects the likelihood and severity of line or system total voltage exceeding or falling below the rated value in a power system. It is defined as follows: In the formula, This indicates the severity of voltage exceedance under this condition.

[0134] The risk indicators of the above-mentioned influencing factors are used as elements to form a set of indicator vectors. .

[0135] Considering that some indicators in the system have different dimensions and large differences in value, it is necessary to standardize each indicator so that it can participate in unified evaluation and judgment.

[0136] The basic steps of standardization are:

[0137] 1) Determine the perceived scale of risk indicators and provide a set of perception scales. ,For example:

[0138] The indicator value is small, and the risk is very low. The indicator value is slightly high, but the risk is low. The indicator value is moderate, and the risk is average. The indicator value is too high, indicating a significant risk. A high indicator value indicates a high risk. If a risk indicator is not important, it can be set to 0.

[0139] 2) Next, construct the judgment matrix.

[0140] Establish a judgment matrix based on the above scale.

[0141] (4)

[0142] when At that time, Judgment matrix.

[0143] 3) Calculate the indicator weights

[0144] Perform eigenvalue analysis on the judgment matrix, find the eigenvector corresponding to the largest eigenvalue, and normalize it to obtain the weight vector. .

[0145] 4) Comprehensive Evaluation

[0146] By combining the indicator set with the weights, a comprehensive risk assessment value is obtained. In the formula, For index vectors, This is the weight vector.

[0147] 5) Early warning classification

[0148] Based on the position of the comprehensive risk assessment value I in each level range (e.g., Level IV) Level III [0.06, 0.3), Level II [0.3, 1), Level I This allows for the determination of the current risk level of the power system and the triggering of corresponding preventative measures.

[0149] Step 2: Adequacy Probability Assessment and Flexibility Measurement

[0150] Taking provincial power grids as the evaluation object, resources that can adjust output upwards or downwards in a time sequence are uniformly defined as flexibility resources, mainly including:

[0151] 1. The output of conventional generating units can be adjusted in the medium to long term;

[0152] 2. Available output of wind and solar power units affected by random factors such as wind speed and irradiance;

[0153] 3. Energy storage devices, peak-shaving hydropower, and other resources that can rapidly regulate demand;

[0154] 4. Demand response users with the ability to reduce or shift peak loads.

[0155] The available capacity of the above-mentioned resources is converted into equivalent flexible up / down power at a uniform time granularity (e.g., 15 min or 1 h), denoted as The superscript "+" indicates the available upward adjustment capacity, and "−" indicates the available downward adjustment capacity. The province's flexible supply capacity for that period is obtained by summing all resources within the same time period.

[0156]

[0157] (1) Scenario-based prediction of flexibility requirements

[0158] Considering that the actual operation of provincial power grids is affected by multiple factors such as load fluctuations, weather changes, distributed renewable energy grid connection, and changes in external transmission / reception plans, it is necessary to construct a scenario set covering various operating conditions, including "normal days—peak days—days with strong winds / high solar radiation—days with low water levels or water restrictions." For each scenario... Provide the flexibility requirements for this period. This demand can be composed of "baseline load forecast + new energy output forecast + reserve / ramp requirements", or it can be directly generated as a series of operating conditions using the "state enumeration / Monte Carlo sampling" method in reliability literature.

[0159] 1) Scenario assessment based on flexibility

[0160] For each scenario Compare supply capacity and demand during the same period: ,when This demonstrates sufficient flexibility in this scenario; when This indicates a lack of flexibility in the scenario, necessitating further quantitative adjustments to the early warning system.

[0161] 2) Calculation of the probability of sufficient flexibility

[0162] For a given time t, in total The number of times a power outage occurred in each scenario was counted. This allows us to obtain the empirical probability of power outage events.

[0163] Its statistical approach is consistent with the definition of probability in the report, which states that "the number of occurrences accounts for the proportion of the total number of occurrences".

[0164] In terms of spatial scale, and The probabilities of power shortage events correspond to the provincial and regional levels, respectively: This is a quantitative probability of power shortage risk obtained by taking a single provincial power grid as the object, based on a comparison of flexible supply and demand and a confidence level assessment within the province; while After completing the provincial assessment, the role of inter-provincial mutual assistance and cross-provincial trading space (feasible area of ​​interconnection line channels) in alleviating power shortages is further explicitly considered. The assessment determines whether each province can meet the supply guarantee requirements after mutual assistance, thereby quantifying the probability of power shortage risk at the regional power grid level.

[0165] To demonstrate the severity, the "unmet flexibility capacity" can be provided for each deficiency scenario: Multiplying this by the probability yields the "expected flexibility gap" metric. This quantity can be used directly when making early warning classifications later.

[0166] (2) The sufficiency of the regional / interconnection system side is equivalent to the inter-provincial mutual assistance capacity.

[0167] In view of the characteristics of the Southwest Power Grid, which includes DC transmission, inter-provincial transmission, and large load areas at the receiving end, and in accordance with the AC / DC hybrid system adequacy assessment framework, the inter-provincial interconnection lines, DC channels, and important substations at the receiving end are unified into a network model that can calculate power flow, and several "regional key sections" or "inter-provincial transaction sections" are identified.

[0168] In this network, the maximum transmittable power of DC or inter-provincial lines is not a fixed value; it is affected by multiple factors, including the line's rated capacity, terminal voltage / reactive power constraints, and the simultaneous operation mode of the channels. Following the approach of "ATC Probability / Risk ATC Description of Section Trading Space," a set of randomized available transmission capacities is provided for each critical section. The distribution of these components was then characterized; combined with the flexible capacity for mutual assistance reported by each province, the "mutual assistance capacity boundary" of that province at this cross section was obtained. This unifies "how much the channel can deliver" and "how much the province can contribute" into a single random quantity.

[0169] (3) Scene sampling and accident probability determination

[0170] Scenario sampling was also performed on the regional network, with each scenario including: intra-provincial load, renewable energy output in each province, planned inter-provincial power, actual available capacity of key channels, and fault status of some equipment. If it exists

[0171] This indicates that in this scenario, "regional-level mutual assistance cannot compensate for the provincial-level flexibility gap," and is denoted as a regional insufficiency scenario. Accumulating the number of all regional insufficiency scenarios yields the probability of insufficient regional flexibility, written in the same way as in the previous section. This step is consistent with the logic in Wang Longjun's literature that "with a sampled state of the system, power flow calculations can be used to determine whether it is in an accident state."

[0172] (3) Indicator output

[0173] The final output includes three categories of quantities, which can be directly used in the subsequent "early warning level quantification":

[0174] 1. Probability of insufficient flexibility at the provincial level ;

[0175] 2. The probability of insufficiency at the regional / interconnection level after considering mutual assistance. ;

[0176] 3. Three operational risk quantification indicator vectors ,in The original "expected underload" can be replaced by "expected flexibility gap". The other two are still severe measures of overload and voltage overrun, which are consistent with the weighted and graded algorithm.

[0177] In summary, the model combines the randomness of wind power and demand response at the provincial level into flexible supply, and then compares the probability with scenario-based demand. At the same time, the regional transmission capacity is randomized into ATC, and then combined with the flexibility available to each province to form a mutual support capacity, thus forming a probabilistic assessment model based on the adequacy of flexibility.

[0178] Step 3: Cross-provincial transaction space and mutual assistance triggers

[0179] After completing the probabilistic assessment of the flexibility adequacy of provincial power grids, this invention further introduces a cross-provincial trading space partitioning method based on expected quantiles in order to characterize the tradability of cross-provincial channels in the Southwest region under different operating scenarios.

[0180] (1) Definition of cross-sectional capacity and available transmission capacity

[0181] In a given scenario Next, for key sections or inter-provincial corridors selected in the Southwest region, calculate their total transmission capacity.

[0182] After deducting safety margin, reserve usage, and contracted electricity volume, the available transmission capacity in this scenario can be obtained. ,in, For transmission reliability margin, This is the amount of reserve space available for mutual assistance. This refers to the transmission volume under existing contracts.

[0183] (2) Risk ATC based on expected quantiles (ERATC)

[0184] To avoid channel blockage caused by extreme scenarios, this invention uses random sample sequences. Sort the data and take the quantile position as the release metric, defined as follows: ,in, It is the inverse function of the empirical distribution function of the sample. For the desired quantile parameter, the preferred one is... When releasing information about cross-provincial transaction space to the public, it should be based on... This approach, which uses the maximum trading volume that the channel can handle in this time period and at a given confidence level, is consistent with the "risk ATC release index based on expected quantiles" in the literature.

[0185] (3) Mutual assistance triggering criteria and allocation rules

[0186] When the available transmission capacity is obtained from real-time or short-term forecasts When it is lower than the aforementioned release value, it is satisfied.

[0187] It is believed that there is a shortage of inter-provincial trading space, necessitating the triggering of mutual assistance allocation rules. These mutual assistance allocation rules include:

[0188] According to the gap Calculate the minimum power required for mutual assistance during this period;

[0189] The mutual aid capabilities reported by various provinces .

[0190] The preferred approach is to allocate resources proportionally based on a weighted vector composed of three factors: "provincial flexibility surplus / route constraints / provincial early warning level." This ensures that provinces with low early warning levels and ample flexibility first undertake the mutual assistance task, and then other provinces supplement the task.

[0191] The formal wording, "When ATC falls below the predetermined value and a shortage occurs, the mutual aid allocation rule needs to be triggered; insufficient ATC will cause the contract to fail to be completed, and a reasonable indicator needs to be issued," is consistent with Ma Zeyang's statement that "insufficient ATC will cause the transaction to fail to be completed, and a risk ATC needs to be issued."

[0192] (3) Hierarchical division of cross-provincial transaction space

[0193] To facilitate scheduling and market use, this invention will The corresponding trading space is divided into three layers:

[0194] First layer: This is a safe trading zone;

[0195] Second layer: This is a warning trading zone;

[0196] Third layer: This is a mutual aid trading zone, and the mutual aid allocation rules from the previous step need to be implemented.

[0197] The question of "how much the channel can deliver" and "when to activate mutual assistance" are linked together by a unified, probabilistic release indicator.

[0198] Step 4: Quantification and Dynamic Update of Early Warning Levels

[0199] After obtaining the probability of insufficient provincial flexibility, the probability of insufficient regional mutual assistance, and the risk ATC of the channel, this invention uses a quantitative grading method to give the early warning level of power grid supply guarantee risk.

[0200] (1) Construction of quantitative indicator set

[0201] Construct a comprehensive risk index vector ,in: This represents the expected flexibility gap obtained in the previous section; , , These are risk indicators for underload, overload, and voltage exceeding limits.

[0202] This is a quantified value of the risk caused by insufficient ATC at the channel level, which can be calculated as follows:

[0203] Normalization is performed when Time to take .

[0204] (2) Determination of weights

[0205] The analytic hierarchy process (AHP) is used to construct a judgment matrix (4). Based on four dimensions—flexibility, load, channel, and inter-provincial mutual assistance—the relative importance of each dimension to the final supply guarantee risk is evaluated, resulting in a normalized weight vector. .

[0206] (3) Calculation of comprehensive early warning value

[0207] By combining the indicator vector and the weight vector, the comprehensive risk / warning value for the current period is obtained. The larger this value, the more frequent the provincial flexibility gap, the more severe the line or voltage limitations, the more easily the channel is blocked, and the more difficult it is to achieve inter-provincial mutual assistance.

[0208] (3) Calculation of comprehensive early warning value

[0209] The design of the four-color interval in the quantitative evaluation method for China Southern Power Grid will incorporate the comprehensive value. Compare with the preset interval:

[0210] Blue Alert: The power grid is in a normal or controllable state;

[0211] Yellow alert: The power grid operation has a certain degree of flexibility or channel constraints, which needs to be paid attention to;

[0212] Orange alert: The power grid's supply capacity is significantly limited, requiring advance arrangements for inter-provincial mutual assistance or intra-provincial start-up and shutdown.

[0213] Red Alert: The power grid faces high risks in ensuring power supply, necessitating the implementation of emergency and load management measures.

[0214] The interval values ​​can be readjusted based on operational experience or historical data. The present invention uses the above-mentioned interval as a feasible embodiment.

[0215] (3) Dynamic update mechanism

[0216] Considering that the wind and solar power output, water inflow conditions, and inter-provincial trading plans of the Southwest Power Grid all exhibit changes on hourly or even shorter timescales, this invention sets the rolling update cycle for early warning as follows: (Preferred) or At each update moment. Perform the following steps:

[0217] 1) Regenerate or modify the scene set to obtain a new one. ;

[0218] 2) According to the predetermined weights Calculate the new composite value. .

[0219] 3) If a jump occurs in the warning level compared to other levels, a new warning level will be issued to both the provincial and regional dispatch centers simultaneously.

[0220] Step 5: Application, dissemination, and coordinated dispatch of early warning results

[0221] This invention encapsulates the probability of insufficient provincial flexibility, the residual risk of regional / interconnected systems after mutual assistance, the cross-provincial transaction capability indicators obtained from the expected quantiles of key sections, and the corresponding comprehensive early warning levels in a unified manner, forming an early warning output dataset for scheduling, market and operation management.

[0222] The output dataset includes at least: the warning level for the current period, a breakdown of the warning causes (insufficient flexibility, channel limitation, voltage / overload risk), a list of available provincial flexibility resources, and suggested cross-provincial capacity for mutual assistance. The system automatically pushes this dataset to the provincial dispatch center and the Southwest Regional Dispatch Platform at predetermined intervals or when a warning level transitions, achieving synchronized dissemination of warning information.

[0223] Based on this, the dispatching terminal can trigger control or operational strategies such as start-up and shutdown, backup adjustment, demand response activation, inter-provincial mutual assistance, and temporary transaction limit adjustment, thereby forming a closed loop between the quantitative early warning results generated by this invention and the actual operation control, ensuring that supply risks are timely dispatched and regulated.

[0224] In summary, this invention proposes a method for quantifying the supply capacity of provincial power grids based on the probability of flexibility adequacy. By uniformly modeling and aggregating the capabilities of conventional generating units, wind and solar power, energy storage devices, and demand response resources, and combining panoramic scenario prediction oriented towards load-new energy-reserve constraints, the method determines the difference between flexibility supply and flexibility demand in each time period. This transforms the qualitative judgment of "whether it can keep up" into a calculable probability of insufficient flexibility, thereby forming a basic quantity of supply risk at the provincial level.

[0225] This invention constructs a cross-provincial transaction space characterization and mutual assistance triggering mechanism for the Southwest region. Based on the transmission capacity, safety margin, reserve occupancy, and existing contracted power volume of key sections / inter-provincial channels, it introduces a scenario-based description of available transmission capacity and a risk ATC release index based on expected quantiles. When the real-time available capacity is lower than the released value, mutual assistance sharing is automatically triggered according to the mutual assistance capacity reported by each province and line constraints, achieving the technical effect of incorporating "inter-provincial mutual assistance capacity within the region" into the same quantitative calculation framework.

[0226] This invention assembles multiple quantitative results, such as the expected value of flexibility gap, risk of load shedding, risk of overload, risk of voltage exceeding limits, and risk of channel congestion, into a unified comprehensive risk index vector. It uses a hierarchical weight determination method to generate a weight vector and obtains a single quantitative value of supply guarantee risk through weighted summation. This value is then mapped to a graded early warning interval (such as blue, yellow, orange, and red) to achieve early warning output at the provincial and regional levels under the same caliber.

[0227] This invention specifies a rolling update and synchronous release mechanism for the above-mentioned assessment and grading process. With a fixed time step or change in the operating scenario as the trigger condition, the scenario is regenerated, the ATC is recalculated, the comprehensive value is recalculated, and the early warning results are issued to ensure the timeliness of the early warning and the consistency of cross-provincial collaboration.

Claims

1. A method for quantitatively calculating the early warning level of supply guarantee risk in the Southwest Power Grid based on probability assessment of flexibility adequacy, characterized in that, Includes the following steps: Step 1) Calculate the power grid supply guarantee risk indicators based on the power grid component failure probability model and the power grid accident occurrence probability model, thereby constructing a power grid supply guarantee risk indicator set; Step 2) Conduct a probability assessment of the adequacy of the power grid and a measurement of its flexibility, and calculate the expected flexibility gap index and the probability of insufficient flexibility; Step 3) Based on the expected quantile, divide the cross-provincial trading space and calculate the quantitative value of risk caused by insufficient ATC at the channel level; Step 4) Write the expected flexibility gap index and the risk quantification value caused by insufficient ATC at the channel level into the power grid supply guarantee risk index set, and standardize the updated power grid supply guarantee risk index set to obtain the power grid supply guarantee risk level. Step 5) Based on the power grid supply risk level, the probability of insufficient flexibility, and the updated power grid supply risk indicator set, output an early warning output dataset for dispatching, market and operation management.

2. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... The failure probability model for power grid components is shown below: （1） in: This indicates normal weather. Indicates severe weather. This indicates the component failure rate during alternating weather conditions. This refers to the annual operating hours of the component under normal conditions. This is the duration of normal weather. For the duration of severe weather; Duration of alternating weather; The proportion of failures occurring during severe weather to the total number of failures throughout the year; The proportion of faults occurring under alternating weather conditions to the total number of faults throughout the year; This is the average operating time of the component before it fails. Failure rate of power system components related to weather.

3. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... The probability model for power grid accidents is shown below: （2） （3） In the formula, For inclusion The system state obtained by sampling the power system of each component; This represents the total number of samples. Accident status Number of times it appears; For any element in a power system The probability of service interruption; For components Random numbers obtained from sampling; This refers to the component state corresponding to this sampling.

4. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... Power grid supply risk indicators include load shedding risk indicators, overload risk indicators, and voltage over-limit risk indicators; Among them, the risk index of load loss ; For the first The probability of an accident occurring. This indicates the severity of system load loss under this condition; Overload risk indicators ; This indicates the severity of the overload under this condition; Voltage over-limit risk indicators ; This indicates the severity of voltage exceedance under this condition.

5. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... The expected flexibility gap indicators are shown below: （4） In the formula, For the scene The probability of occurrence; ; Representing a scene The unmet flexibility capacity in the next time period t; Unmet flexibility capacity ; The flexibility requirement for time period t; The ability to provide flexible supply for time period t; The power can be adjusted up or down for equivalent flexibility.

6. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... The inter-provincial trading space includes a safe trading zone, an early warning trading zone, and a mutual assistance trading zone; The safe trading zone, early warning trading zone, and mutual assistance trading zone are divided according to the cross-provincial trading volume Q of the channel in time period t; Among them, the secure trading zone meets the requirements. ; This represents the maximum transaction volume that can be accommodated at a given confidence level. It is the inverse function of the empirical distribution function of the sample. Desired quantile parameters; available transmission capacity ; For transmission reliability margin, This is the amount of reserve space available for mutual assistance. For existing contract transmission volume; Early warning trading zone meets ; Mutual aid trading zone meets ; When the available transmission capacity is obtained from real-time or short-term forecasts Less than the release index At that time, the mutual assistance allocation or quota adjustment mechanism will be based on the gap in the channel trading space. trigger.

7. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... Quantitative value of risk caused by insufficient ATC at the channel level As shown below: （5） In the formula, when hour, ; Available transmission capacity is obtained from real-time or short-term forecasts.

8. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... Step 4, the standardization process for the updated power grid supply guarantee risk indicator set, includes: Step 4.1) Set the perception scale for risk indicators and the range of risk levels; Step 4.2) Establish a judgment matrix based on the perceptual scale, that is: （6） Step 4.3) Perform eigenvalue analysis on the judgment matrix, find the eigenvector corresponding to the largest eigenvalue, and normalize it to obtain the weight vector. ; Step 4.4) Combine the risk indicators and weights to obtain the comprehensive risk assessment value. ; For risk indicator vectors, This is the weight vector; Step 4.5) Calculate the comprehensive risk assessment value Match the risk level range to determine the current risk level of the power system; The risk levels are divided into four levels. Level 1 risk level means that the power grid is in a normal or controllable state; Level 2 risk level means that the power grid operation has flexibility or channel constraints; Level 3 risk level means that the power grid's supply capacity is limited and inter-provincial mutual assistance or intra-provincial start-up and shutdown need to be arranged in advance; Level 4 risk level means that the power grid supply risk is high and emergency and load management measures need to be activated.

9. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... Steps 1-4 are executed periodically. When the risk level changes, a new warning level is issued to both the provincial and regional dispatch centers simultaneously, and step 5 is executed.

10. The method for quantitatively calculating the risk warning level of the Southwest Power Grid based on the probability assessment of flexibility adequacy, as described in claim 1, is characterized in that... In step 5, the early warning output dataset for scheduling, market and operation management includes the power grid supply risk level, the probability of insufficient flexibility, the updated power grid supply risk indicator set, and the remaining risk of the regional / interconnected system after mutual assistance. The causes of the warning include insufficient flexibility, limited channels, and voltage / overload risks. Among them, real-time / predictive Less than When the risk quantification value caused by insufficient ATC at the channel level exceeds the threshold or accounts for the largest proportion, the warning cause is channel restriction; When the voltage over-limit risk indicator or overload risk indicator exceeds the threshold / contributes the most, the warning is issued because of voltage / overload risk. When flexibility-related indicators exceed the threshold or have the greatest contribution, the warning is triggered by insufficient flexibility. Available inter-provincial mutual assistance capacity .

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