Intervention method and system suitable for electric power spot transaction result abnormity

Abstract

The invention discloses an intervention method and system suitable for electric power spot transaction result abnormity. The method comprises the following steps: S101, establishing a unified and normalized data interface; s102, importing case data by using a spot case data management module; s103, an electric power spot market result abnormity analysis module carries out analysis; s104, performing data interaction between the auxiliary research decision-making tool and the electric power spot system; s105, performing intervention based on an optimal closed-loop correction theory; and S106, providing auxiliary decision-making information by the abnormity clearing auxiliary decision-making management and control module. According to the method, typical events of clearing abnormity in the electric power spot market are identified, positioned and analyzed, intelligent intervention aid decision reference information is provided, and a business closed loop of market clearing-correction decision adjustment in the environment of the electric power spot market is realized in an auxiliary manner.

Description

Technical Field

[0001] The present invention mainly relates to the field of electric power technology, and in particular to an intervention method and system suitable for abnormal results of electric power spot transactions. Background Art

[0002] At present, as more provinces are connected to the regional electricity spot market trial operation and will carry out electricity spot settlement trial operation in the next stage, due to the diverse provincial boundary conditions, complex coupling of various constraints, and fierce competition in provincial unified declarations, the transaction results may have multiple problems including drastic price changes, local supply and demand tensions, and network congestion.

[0003] The clearing results of the electricity spot market are affected by different types of market operation constraints. It is difficult and inefficient to manually troubleshoot the source of abnormalities when market transaction results are abnormal. Therefore, there is an urgent need for a system that can quickly locate the causes of abnormal clearing events in the electricity spot market and provide corresponding solutions to ensure the stable operation of the electricity market. Summary of the invention

[0004] In view of the technical problems existing in the prior art, the present invention provides an intervention method and system suitable for abnormal results of power spot transactions, which provides intelligent intervention auxiliary decision reference information and assists in realizing the business closed loop of "market clearing-correction decision adjustment" in the power spot market environment.

[0005] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0006] An intervention method applicable to abnormal results of power spot trading, comprising the steps of:

[0007] S101. Establish a unified and standardized data interface and design a unified market data management format;

[0008] S102, obtaining case data to be analyzed in the spot system through the spot case data management module; the case data includes all input and output data of the clearing link, which are divided into market model data, clearing parameter data, market boundary data and market result data;

[0009] S103, using the power spot market result abnormality analysis module to analyze the rationality of power price abnormality, cross-section limit violation, and unit output on the input data and clearing result data of the imported case, and discover and warn of possible abnormal situations;

[0010] S104. File scanning operations are performed between the clearing anomaly auxiliary research and decision-making tool and the power spot system at a fixed frequency, encrypted transmission and identity authentication are performed through the SFTP protocol, and specific file naming rules and content formats are used to ensure consistency and accuracy;

[0011] S105. For the problem of safety constraint exceeding the limit that still exists after the pre-clearance of the spot market, the clearing abnormality auxiliary decision-making control module adopts the optimal closed-loop correction theory, selects the period with a larger safety distance for correction, solves the unit output correction plan within the period of exceeding the limit, and recalculates the SCED model based on the adjusted clearing boundary conditions;

[0012] S106. Use the abnormal clearing auxiliary decision-making management and control module to provide non-market unit plan adjustment information as an auxiliary decision-making reference to assist market operators in adjusting the unit power generation plan.

[0013] Preferably, in step S105, the static safety domain is calculated, the static safety distance is calculated, the safety distance sensitivity is calculated, the effectiveness of eliminating safety over-limit is analyzed, the automatic correction auxiliary decision modeling of the power generation plan and the deduction of the section over-limit abnormality handling measures are carried out based on the optimal closed-loop correction theory.

[0014] Preferably, the calculation process of the static security domain is:

[0015] For power generation planning and real-time dispatching, the static safety domain is a collection of a large number of system operating points in the multidimensional space of generator output, taking into account active power balance, unit operating characteristic constraints, and grid security constraints. Using the DC power flow model, the static safety domain is expressed as formula (1):

[0016]

[0017] Where P G and P D represents the unit output and node load vector, P Lmax represents the line transmission limit vector; P Gmax and P Gmin are column vectors representing the maximum and minimum technical output of the unit respectively; G g represents the power transfer distribution factor (PTDF) matrix of the node where the generator is located to the line, G represents the transfer distribution factor matrix of all nodes to the line; P Gi represents the unit output of node i, P Dj represents the load demand of node j; M and N represent the collection of units and load nodes respectively.

[0018] Preferably, the calculation process of the static safety distance is:

[0019] For the safety domain space composed of the maximum and minimum technical output of the unit and the safety constraints, if the planned operating point of the t period is obtained by pre-clearing If the limit is exceeded, the distance from the point to the hyperplane formed by the i-th constraint boundary on the boundary of the safety region is expressed as:

[0020]

[0021] Where P G,t represents the unit output column vector corresponding to any point on the i-th constraint boundary of the safety domain within the t period; P D,t represents the column vector composed of the node loads in period t; P Lmax represents the line transmission quota column vector, P Lmax,i represents the limit of the ith line; G t represents the PTDF matrix of all nodes in period t; G g,t represents the PTDF matrix of the power generation node during period t; e i represents the unit column vector [0,…,1,0,…,0] T , there is only a non-zero element at the i-th position;

[0022] According to the model of formula (2), for point Calculate the distance to the hyperplane where each safety zone boundary constraint is located, expressed as: ||d 1,t ||,…,||d i,t ||,…,||d n,t ||, where n represents the number of effective constraints that form the security domain boundary, d i,t Represents the hyperplane and point where the i-th constraint is located The minimum value of the distance from the operating point to the hyperplane where each boundary of the safety domain space is located is the static safety distance of the operating point:

[0023] d tmin =||d tmin ||=min(||d 1,t ||,…,||d i,t ||,…,||d n,t ||) (3)

[0024] Where, d tmin Represents the planned point in period t The static safety distance value, d tmin is the static safety distance vector.

[0025] Preferably, the calculation process of the safety distance sensitivity coefficient is:

[0026] The direction of the static safety distance vector is defined as the point P on the safety domain boundary that is closest to the planned operating point. G,t , pointing to the planned operation point This vector reveals the multidimensional unit output space that makes the point Adjust to the optimal adjustment direction within the safety range; therefore, the limit point The static safety distance vector dtmin The output of each unit is differentiated to obtain the safety distance sensitivity coefficient of the unit:

[0027]

[0028] In the formula, e j represents the unit column vector [0,…,1,0,…,0] T , there is a non-zero element only at the position of the jth unit; from a physical point of view, when E dt,j When it is a positive value, it means that the current planned operation point Based on the increase in the output of unit j, the planned operating point Closer to point P on the security domain G，t , which is conducive to shortening the over-limit safety distance; similarly, if it is a negative value, it means that reducing the output of unit j is conducive to shortening the over-limit safety distance; the size of the safety distance sensitivity coefficient reveals the global effect of the change in the unit output on reducing the active over-limit range.

[0029] Preferably, the process of analyzing the effectiveness of eliminating safety violations is as follows:

[0030] In order to minimize the number of units to be corrected, the safety distance sensitivity and adjustment capability of the units should be considered at the same time to obtain the effectiveness ranking of the units in eliminating safety violations; units with positive safety distance sensitivity should be preferentially selected to be included in the set of increased output, and units with negative safety distance sensitivity should be included in the set of reduced output; the adjustment capability of the units is limited by the maximum and minimum technical outputs, as well as the climbing capability in adjacent periods, and the adjustment capability of the increased output units It is expressed as:

[0031]

[0032] Similarly, the adjustment capability of the reduced output unit It is expressed as:

[0033]

[0034] Where P Gi,max and P Gj,min They represent the maximum technical output of unit i and the minimum technical output of unit j respectively; and They represent the planned output of unit i and unit j before correction in period t respectively; and They represent the connection output of unit i in time periods t-1 and t+1 before correction of time period t. According to the multi-time period connection strategy, if the safety distance of the adjacent time period exceeds the limit greater than that of time period t, then and It means that after the correction at time periods t-1 and t+1, the new planned output of unit i is obtained; similarly, and They respectively represent the correction connection output points of unit j in adjacent time periods; and Respectively represent the climbing capabilities of units i and j; and They respectively represent the maximum increased power generated by the increased output unit subject to the unit output limit, the climbing capacity constraint limit of the previous period and the next period; and They respectively represent the maximum power reduction caused by the output limit of the unit, the climbing capacity constraint limit of the previous period and the next period;

[0035] For the increased output unit, its contribution to eliminating the safety zone crossing within the t period is:

[0036] (7)

[0037] For the reduced output unit, its contribution to eliminating the safety zone crossing within the t period is:

[0038] (8)

[0039] In the formula, E dt,i and E dt,j Respectively represent the safety distance sensitivity values ​​of unit i and unit j in time period t; according to and The values ​​are used to arrange the units with increased output and units with reduced output in descending order, which serves as the basis for subsequent correction decision modeling.

[0040] Preferably, the process of automatic correction auxiliary decision modeling of power generation plan is:

[0041] The sequence of the increased and decreased output units in each over-limit period is calculated by equations (5)-(8). The increased and decreased output units with the same ranking form an adjustment pair. The adjustment pairs with the higher ranking are first included in the linear correction decision model in order, as shown in equations (9)-(17);

[0042] If the model has no solution, a new adjustment pair is included in the sequence for solution; if the distance that exceeds the safety zone boundary has not been eliminated, the adjustment capacity of the original unit that increases or reduces the output has been exhausted. At this time, the unit with a safety distance sensitivity coefficient of 0 is selected for reverse pairing to form a new unit adjustment pair; if the adjustment capacity of the unit with a sensitivity of 0 is also exhausted, the unit with a smaller positive sensitivity coefficient is selected as the object of increasing the output, and the unit with a larger negative sensitivity coefficient is selected as the object of reducing the output. The linear correction decision model aims to minimize the adjustment amount;

[0043]

[0044] Where M t and N t They represent the sets of units with increased and reduced outputs formed by adjusting the selected units in the time period t; L kbase,t L represents the active power component caused by non-correction decision-making units and loads on line k during period t; kmax G represents the active transmission limit of line k; i and G j They respectively represent the active sensitivity of the unit i with increased output and the unit j with reduced output to the line k; Formula (8) represents the power balance constraint within the time period; Formulas (9)-(12) represent the output connection between time period t and the adjacent time period, which should meet the climbing capacity constraint; Formulas (13)-(14) represent that the unit correction output should be within the range of maximum and minimum technical outputs; Formula (15) represents the active power flow constraint.

[0045] Preferably, the specific process of step S104 is:

[0046] S1041. After the electricity spot system completes the release of the spot day case clearing every day, it sends the algorithm data package file to the designated directory of the spot file server; the data package file includes the algorithm input and output information of the electricity spot transaction;

[0047] S1042. The clearing anomaly auxiliary research decision-making tool scans and reads the latest clearing complete algorithm data file from the specified directory of the spot file server at a fixed time every day to provide basic data for anomaly analysis and closed-loop correction calculation;

[0048] S1043. After reading these data, the abnormality-clearing auxiliary research decision-making tool will perform abnormality-clearing analysis and closed-loop correction calculations to find abnormal situations and make corrections. After completing the closed-loop correction calculations, the system will send the intervention results to the designated directory of the abnormality-clearing auxiliary research decision-making tool file server;

[0049] The S10414 electricity spot system will scan and read the latest non-market unit plan data file from the designated directory of the clearing anomaly auxiliary research decision-making tool file server at a fixed time every day; the data file contains the intervention results, that is, the new non-market unit plan data file. After reading this data, the electricity spot system will display the results in the system and allow the user to operate whether to use the new non-market unit plan as input for re-clearing.

[0050] Preferably, in step S105, if there is still a safety constraint violation after the spot market is pre-cleared, the decision-making process for implementing power generation plan correction is as follows:

[0051] S1051. First, based on the pre-clearing results of the day-ahead spot market, all time periods with active power exceeding the limit and the corresponding exceeding-limit sections of each time period are screened;

[0052] S1052, respectively calculating the minimum distance between the planned operation point obtained by pre-clearing and the static safety region of each time period in each time period that exceeds the limit, and arranging each intervention time period in descending order;

[0053] S1053. Prioritize the time period with a larger safety distance for correction. Based on the operation point obtained by pre-clearing in this time period, calculate the sensitivity coefficient of each unit to the static safety distance. Consider the ramping of the unit before and after the time period and the maximum and minimum technical output limits, calculate the effectiveness of the unit's adjustment to the safety domain limit in each time period, and determine the increase and decrease output set of the time period.

[0054] S1054, solving the unit output correction plan within the limit-crossing period. If the model has no solution, it is necessary to adjust the start and stop states of the unit to meet the requirements of the safety constraints;

[0055] S1055, check whether there are still active power over-limits in other time periods that have not been processed. If yes, recalculate the static safety distance of the adjacent time periods, and then return to step S1053 to continue adjustment. If no, end;

[0056] S1056. After the intervention is completed, the SCED model is recalculated based on the adjusted clearing boundary conditions. If the requirements of the power grid security constraints are still met, the results of the recalculated SCED will be published.

[0057] The present invention also discloses an intervention system suitable for abnormal results of power spot transactions, including a spot case data management module, a power spot market result abnormal analysis module and a clearing abnormality auxiliary management and control module;

[0058] The spot case data management module is used to establish a unified and standardized data interface to obtain case data;

[0059] The power spot market result abnormality analysis module is used to build an abnormality analysis model to identify, locate and analyze abnormal clearing events;

[0060] The clearing anomaly auxiliary control module is used to combine the clearing anomaly analysis library, select typical scenarios where various abnormal events occur, and provide targeted response strategies and processing plans based on the optimal closed-loop correction theory.

[0061] Compared with the prior art, the advantages of the present invention are:

[0062] The present invention adopts a system architecture in which a spot case data management module, an abnormal analysis module for power spot market results and an abnormal clearing decision-making control module are interconnected to identify, locate and analyze abnormal clearing events of typical abnormal power spot market clearing events, and provide intelligent intervention decision-making reference information to assist in realizing the business closed loop of "market clearing-correction decision adjustment" in the power spot market environment.

[0063] The present invention firstly establishes a unified and standardized data interface through the spot case data management module to realize the efficient import of various data. After the market is successfully cleared, based on the input data of the spot case data management module, the power spot market result abnormality analysis module performs rationality analysis on the input data of the imported case and the clearing result data in terms of abnormal electricity prices, section exceeding the limit, unit output, etc., discovers and warns of possible abnormal situations, which serve as the pre-input of the clearing abnormality auxiliary management and control module; for the section exceeding the limit problem that still exists after the market is successfully cleared, the spot market operation personnel can start the clearing abnormality auxiliary management and control module of the clearing abnormality auxiliary research and decision-making tool. The decision-making tool for assisting the research on clearing anomalies first exchanges data with the power spot system through a transit file server and transfers files through the SFTP protocol. Then, based on the optimal closed-loop correction theory, it calculates the static safety domain, the static safety distance, the safety distance sensitivity, the effectiveness of eliminating safety over-limits, the automatic correction of power generation plans, the auxiliary decision modeling, and the deduction of section over-limit abnormality handling measures, etc., thereby providing non-market unit plan adjustment information as an auxiliary decision-making reference and assisting market operators in adjusting unit power generation plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 The present invention is a flow chart of an embodiment of the intervention method applicable to abnormal results of power spot trading.

[0065] Figure 2 It is a structural diagram of an embodiment of the intervention system applicable to abnormal results of power spot trading of the present invention.

[0066] Figure 3 It is a structural diagram of an abnormality clearing auxiliary control module in an embodiment of the present invention.

[0067] Figure 4 The present invention is a data interaction flow chart applicable to an intervention system for abnormal results of spot power transactions.

[0068] Figure 5 This is a flow chart of auxiliary decision-making for power generation plan correction in the present invention. DETAILED DESCRIPTION

[0069] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0070] like Figure 1 As shown, the intervention method applicable to abnormal results of power spot trading according to the embodiment of the present invention comprises the following steps:

[0071] S101. Establish a unified and standardized data interface: design a unified market data management format to achieve efficient import of various types of data;

[0072] S102. Import case data using the spot case data management module. Obtain the cases that need to be analyzed in the spot system through the spot case data management module. These case data include all input and output data of the clearing link to meet the data requirements of other modules for clearing abnormality analysis and auxiliary management and control. They are specifically divided into market model data, clearing parameter data, market boundary data, and market result data;

[0073] S103, the power spot market results abnormality analysis module performs analysis. The power spot market results abnormality analysis module performs rationality analysis on the input data and clearing result data of the imported cases in terms of abnormal electricity prices, cross-section limits, unit output, etc., and discovers and warns of possible abnormal situations;

[0074] S104. Data interaction between the auxiliary research and decision-making tool and the power spot system. The abnormality-clearing auxiliary research and decision-making tool and the power spot system perform file scanning operations at a fixed frequency, use the SFTP protocol for encrypted transmission and identity authentication, and use specific file naming rules and content formats to ensure consistency and accuracy;

[0075] S105. Intervene based on the optimal closed-loop correction theory. For the problem of safety constraint exceeding the limit that still exists after the pre-clearance of the spot market, the clearing abnormality auxiliary decision-making control module adopts the optimal closed-loop correction theory, selects the period with a larger safety distance for correction, solves the unit output correction plan within the period of exceeding the limit, and recalculates the SCED model based on the adjusted clearing boundary conditions;

[0076] S106. The abnormality clearing auxiliary decision-making control module provides auxiliary decision-making information. The abnormality clearing auxiliary decision-making control module provides non-market unit plan adjustment information as an auxiliary decision-making reference to assist market operators in adjusting the unit power generation plan.

[0077] In step S105, based on the optimal closed-loop correction theory, the static safety region is calculated, the static safety distance is calculated, the safety distance sensitivity is calculated, the effectiveness of eliminating safety over-limit is analyzed, the automatic correction auxiliary decision modeling of the power generation plan and the section over-limit abnormality treatment measures are deduced, specifically:

[0078] (1) Calculation of static security domain

[0079] For the over-limit results of the AC safety check output, it is necessary to combine the size of the AC power flow sensitivity coefficient, take the market-oriented units as decision variables, modify or add constraints in the SCUC / SCED model, and recalculate the market clearing results. The upper limit of the number of iterations is generally set to 3 times. If the safety check over-limit situation cannot be eliminated after reaching the upper limit of the number of iterations, it is necessary to intervene in the clearing results. The scope of intervention currently mainly considers the adjustment of non-market-oriented units. After the above processing, a power generation plan that meets the grid security constraints is formed, and then the node electricity price is recalculated, and the day-ahead market clearing results are released.

[0080] By applying the theory of security domain, relevant constraints can be effectively identified. The definition of the static security region (Steady-state Security Region SSR) in the current academic community refers to: a set of operating points that satisfy the power flow equation and the power grid operation constraints. For power generation planning and real-time scheduling, the static security region is a set of a large number of system operating points in the multidimensional space of the generator unit output, which takes into account the active power balance, unit operation characteristic constraints, and power grid safety constraints. Using the DC power flow model, the static security region can be expressed as formula (1):

[0081]

[0082] Where P G and P D represents the unit output and node load vector, P Lmax represents the line transmission quota vector; P Gmax and P Gmin are column vectors representing the maximum and minimum technical output of the unit respectively; G g represents the power transfer distribution factor (PTDF) matrix of the node where the generator is located to the line, G represents the transfer distribution factor matrix of all nodes to the line; P Gi represents the unit output of node i, P Dj represents the load demand of node j; M and N represent the collection of units and load nodes respectively.

[0083] From a physical perspective, the static safety domain can be explained as follows: the spatial dimension of the system operating point is the number of decision-making units for power generation planning / dispatching control, and all the constraints that need to be met constitute a closed / semi-closed space, which is the static safety domain. When the planning point or operating point is within this area, it means that it meets the requirements of the power grid security constraints; if it is outside the area, the planning point / operating point needs to be adjusted to at least the surface of the security domain space to meet the requirements of the power grid security constraints.

[0084] In the intervention link of spot market clearing, if there is a grid safety constraint exceeding the limit, it is necessary to manually adjust the non-market units to meet the requirements of the safety constraint. The basic principle of the adjustment is to minimize the number of adjusted units or the amount of adjusted electricity. The currently widely used sensitivity-based method actually only considers the optimal adjustment direction of the current planned operation point for the safety constraint exceeding the limit. If there are multiple constraint exceeding limits, the adjustment direction is not necessarily the direction that minimizes the number of adjusted units and the amount of adjusted electricity. Instead, the direction from the plan point to the nearest point on the static safety domain should be selected as the optimal direction of correction. In addition, unlike the active power correction of real-time scheduling, the spot market clearing needs to determine the power generation plan for multiple periods. If there is a continuous safety constraint exceeding the limit for multiple periods, the connection of correction measures between consecutive periods also needs to be considered.

[0085] In the optimal closed-loop correction link of spot market clearing, it is only necessary to feedback the over-limit conditions and then clear again in multiple iterations. When multiple over-limit constraints appear at the same time, the optimization process of the SCUC and SCED models will enable the plan point to be adjusted in a direction that is conducive to the optimal goal. Therefore, what needs to be improved in the optimal closed-loop correction link is: how to feedback the over-limit constraints while also feedback the constraints that may appear in the adjustment process based on the current operating point, thereby improving the efficiency of closed-loop correction.

[0086] In a two-dimensional (or multi-dimensional) space, two conflicting constraints will form an intersection (or curve), and this intersection may become the vertex of the safety domain (because not all constraints are valid for forming a safety domain, therefore, it is only necessary to find the constraints involving the "closest" points on the boundary of the safety domain based on the current planned operation point (the point obtained by pre-clearing).

[0087] (2) Calculation of static safety distance

[0088] For the safety domain space composed of the maximum and minimum technical output of the unit and the safety constraints, if the planned operating point of period t is obtained by pre-clearing If the limit is exceeded, the distance from the point to the hyperplane formed by the i-th constraint boundary on the boundary of the safety region can be expressed as:

[0089]

[0090] Where P G,t represents the unit output column vector corresponding to any point on the i-th constraint boundary of the safety domain within the t period; P D,t represents the column vector composed of the node loads in period t; P Lmax represents the line transmission quota column vector, P Lmax,i represents the limit of the ith line; G trepresents the PTDF matrix of all nodes in period t; G g,t represents the PTDF matrix of the power generation node during period t; e i represents the unit column vector [0,…,1,0,…,0] T , there is only a non-zero element at the i-th position.

[0091] According to the model of formula (2), for point The distance to each hyperplane where the safety zone boundary constraint is located is calculated respectively, which can be expressed as: ||d 1,t ||,…,||d i,t ||,…,||d n,t ||, where n represents the number of effective constraints that form the security domain boundary, d i,t Represents the hyperplane and point where the i-th constraint is located The minimum value of the distance from the operating point to the hyperplane where each boundary of the safety domain space is located is the static safety distance of the operating point:

[0092] d tmin =||d tmin ||=min(||d 1,t ||,…,||d i,t ||,…,||d n,t ||) (3)

[0093] Where, d tmin Represents the planned point in period t The static safety distance value, d tmin is the static safety distance vector.

[0094] (3) Calculation of safety distance sensitivity

[0095] The direction of the static safety distance vector is defined as the point P on the safety domain boundary that is closest to the planned operating point. G,t , pointing to the planned operation point This vector reveals the multidimensional unit output space that makes the point Adjust to the optimal adjustment direction within the safety range. The static safety distance vector d tmin The output of each unit is differentiated to obtain the safety distance sensitivity coefficient of the unit:

[0096]

[0097] In the formula, e j represents the unit column vector [0,…,1,0,…,0] T , there is a non-zero element only at the position of the jth unit. From a physical point of view, when E dt,jWhen it is a positive value, it means that the current planned operation point Based on the increase in the output of unit j, the planned operating point Closer to point P on the security domain G,t , which is conducive to shortening the over-limit safety distance; similarly, if it is a negative value, it means that reducing the output of unit j is conducive to shortening the over-limit safety distance. The size of the safety distance sensitivity coefficient reveals the global effect of the change in unit output on reducing the active over-limit amplitude.

[0098] (4) Effectiveness analysis of eliminating safety violations

[0099] In order to minimize the number of units to be corrected, the unit's safety distance sensitivity and adjustment capability should be considered at the same time to obtain the effectiveness ranking of the units in eliminating safety violations. Units with positive safety distance sensitivity are preferentially selected to be included in the set of increased output, and units with negative safety distance sensitivity are included in the set of reduced output. The adjustment capability of the unit is limited by the maximum and minimum technical outputs, as well as the climbing capability in adjacent periods. The adjustment capability of the increased output unit It can be expressed as:

[0100]

[0101] Similarly, the adjustment capability of the reduced output unit It can be expressed as:

[0102]

[0103] Where P Gi,max and P Gj,min They represent the maximum technical output of unit i and the minimum technical output of unit j respectively; and They represent the planned output of unit i and unit j before correction in period t respectively; and They represent the connection output of unit i in time periods t-1 and t+1 before correction of time period t. According to the multi-time period connection strategy, if the safety distance of the adjacent time period exceeds the limit greater than that of time period t, then and It means that after the correction at time periods t-1 and t+1, the new planned output of unit i is obtained; similarly, and They respectively represent the correction connection output points of unit j in adjacent time periods; and Respectively represent the climbing capabilities of units i and j; and They respectively represent the maximum increased power generated by the increased output unit subject to the unit output limit, the climbing capacity constraint limit of the previous period and the next period; and They respectively represent the maximum power reduction caused by the unit output limit, the climbing capacity constraint limit of the previous period and the next period.

[0104] For the increased output unit, its contribution to eliminating the safety zone crossing within the t period is:

[0105]

[0106] For the reduced output unit, its contribution to eliminating the safety zone crossing within the t period is:

[0107]

[0108] In the formula, E dt,i and E dt,j They represent the safety distance sensitivity values ​​of unit i and unit j in time period t respectively. and The values ​​are used to arrange the units with increased output and units with reduced output in descending order, which serves as the basis for subsequent correction decision modeling.

[0109] (5) Modeling and solution process of automatic correction decision-making for power generation plan

[0110] The preparation and adjustment of power generation plans need to ensure the balance of system power. If some pre-corrections are based only on the sensitivity without considering the balance of the adjusted power, the power imbalance caused by the correction will be borne by the market-oriented units or the generators at the balancing nodes. Therefore, referring to the practices in existing literature, this report also optimizes the correction power of non-market-oriented units according to the principle of "equal amount reverse pairing". The sequence of the increased and reduced output units in each over-limit period is calculated by equations (5)-(8). The increased and reduced output units with the same ranking form an adjustment pair. The adjustment pairs with the higher ranking are first included in the linear correction decision model in order, as shown in equations (9)-(17).

[0111] If the model has no solution, new adjustment pairs are included in the sequence for solution; if the distance that exceeds the safety zone boundary has not been eliminated, the adjustment capacity of the original unit that increases or reduces output has been exhausted. At this time, the unit with a safety distance sensitivity coefficient of 0 can be selected for reverse pairing to form a new unit adjustment pair; if the adjustment capacity of the unit with a sensitivity of 0 is also exhausted, the unit with a smaller positive sensitivity coefficient is selected as the object of increasing output, and the unit with a larger negative sensitivity coefficient is selected as the object of reducing output. The linear correction decision model aims to minimize the adjustment amount.

[0112]

[0113] Where M t and N tThey represent the sets of units with increased and reduced outputs formed by adjusting the selected units in the time period t; L kbase,t L represents the active power component caused by non-correction decision-making units and loads on line k during period t; kmax G represents the active transmission limit of line k; i and G j They represent the active sensitivity of the unit i with increased output and the unit j with reduced output to the line k respectively. Formula (8) represents the power balance constraint within the time period; Formulas (9)-(12) represent the output connection between time period t and the adjacent time period, which should meet the climbing capacity constraint; Formulas (13)-(14) represent that the unit correction output should be within the range of maximum and minimum technical outputs; Formula (15) represents the active power flow constraint.

[0114] (6) Deducing treatment measures for cross-section abnormalities

[0115] (6.1) Manual intervention correction deduction

[0116] At present, manual intervention is mainly carried out on non-market-oriented units. The units with planned output are selected based on the experience of the dispatchers, and the unit output and reactive power output during the out-of-limit period are directly adjusted.

[0117] The basic principle is to minimize the number of units to be adjusted. The commonly used method is to make adjustments based on the sensitivity coefficient of the over-limit section. When the regulating pressure of the balancing unit is large, the principle of reverse equal pairing adjustment can be adopted. Based on the principle of priority adjustment of the unit with a large sensitivity coefficient, it can only be guaranteed that the adjustment measures are the most effective measures to eliminate the over-limit section, but it cannot be guaranteed that such adjustments can still meet other related constraints.

[0118] In addition, the preparation and adjustment of power generation plans need to ensure the balance of system power. If manual intervention correction is based only on the sensitivity without considering the balance of power adjustment, the power imbalance caused by the correction will be borne by the market-oriented units or generators at the balancing nodes.

[0119] (6.2) Application of optimal closed-loop correction theory

[0120] The above purely manual method cannot evaluate the degree to which the current operating point meets all safety constraints from a global perspective, and may cause multiple corrections, resulting in a large number of adjusted units and insufficient targeting.

[0121] The optimal closed-loop correction for spot market clearing aims to accurately feedback the possible grid security constraints in the clearing calculation process to improve the efficiency of the clearing calculation and avoid manual intervention. The optimal closed-loop correction still follows the goal of minimizing costs (maximizing social net benefits) and is achieved by adding or changing constraints and resolving the SCUC and SCED models.

[0122] If, in the multiple iterations of closed-loop correction, for active over-limit situations, not only the over-limit constraints in the current pre-clearing results are considered, but also the grid security constraints that may reach the limit are fed back (such as seesaw sections), the pertinence of the optimal closed-loop correction can be enhanced and the number of iterations can be reduced; for voltage over-limit situations, after considering the reactive power regulation capacity available at a given node, if there is still a gap, the start-stop state is adjusted according to the unit's ability to provide reactive power support to the over-limit node, which can enhance the reliability of the power generation plan. Therefore, based on the unit's planned operating point obtained by pre-clearing, it is proposed to use the method of identifying relevant constraints in the over-limit section adjustment optimization process to feedback the active over-limit situation. Specifically, not only the current active over-limit sections are fed back, but also the section constraints with strong constraints can be prompted and output, and the dispatcher selects the constraints for batch feedback, which reduces the number of subsequent closed-loop optimizations and improves the efficiency of the optimal closed-loop correction.

[0123] The business process steps are as follows:

[0124] (1) Assess the severity of safety violations

[0125] Select the case data to be analyzed and load the complete case input and output data from the spot case data management link. Further, evaluate the severity of safety limit violations to set optimization goals, including non-spot unit optimization settings and section optimization settings.

[0126] (2) Optimal correction calculation of non-spot unit output

[0127] According to the selected optimized non-spot unit list and section optimization list, the optimal correction calculation program is executed, including data reading, data verification, SCUC modeling, SCUC execution end, SCED modeling, SCED execution end, SSD sensitivity calculation, unit output correction in each period, execution result analysis, and result output. With the goal of minimizing the adjustment amount of non-spot units, the clearing boundary conditions that meet the safety constraints are obtained, and the warehousing algorithm outputs the results.

[0128] (3) Output intervention decision-making assistance results

[0129] According to the algorithm output results, the eliminated sections and the optimized non-spot unit planned power are summarized and counted. It supports displaying the output plans of all non-spot units before and after correction; it supports counting the number and time periods of over-limit, overloaded, and normal sections before and after correction; it supports filtering the records of over-limit sections before correction and sections that cannot eliminate over-limit after correction.

[0130] like Figure 4As shown, in step S104, the abnormality clearing auxiliary research decision-making tool and the power spot system interact with each other through the transfer file server, and transfer files through the SFTP protocol. The specific interaction process is as follows:

[0131] S1041. After the electricity spot system completes the release of spot day-ahead cases every day, it will send the algorithm data package files to the designated directory of the spot file server. These data package files include the algorithm input and output information of the electricity spot transaction;

[0132] S1042, the clearing anomaly auxiliary research and decision-making tool will scan and read the latest clearing complete algorithm data file from the specified directory of the spot file server at a fixed time every day, providing basic data for anomaly analysis and closed-loop correction calculation;

[0133] S1043. After reading these data, the clearing anomaly auxiliary research and decision-making tool will perform clearing anomaly analysis and closed-loop correction calculations to find out the abnormal situation and make corrections. After completing the closed-loop correction calculations, the system will send the intervention results (i.e., the non-market unit plan data file) to the specified directory of the clearing anomaly auxiliary research and decision-making tool file server;

[0134] S1044. The electricity spot system will scan and read the latest non-market unit plan data files from the designated directory of the clearing anomaly auxiliary research decision-making tool file server at a fixed time every day. These data files contain the intervention results, i.e., the new non-market unit plan data files. After reading these data, the electricity spot system will display the results in the system and allow the user to decide whether to use the new non-market unit plan as input for re-clearing.

[0135] like Figure 5 As shown, in step S105, if there is still a safety constraint violation after the spot market is pre-cleared, the decision-making process steps for implementing power generation plan correction are as follows:

[0136] S1051. First, based on the pre-clearing results of the day-ahead spot market, all time periods with active power exceeding the limit and the corresponding exceeding-limit sections of each time period are screened;

[0137] S1052, respectively calculating the minimum distance between the planned operation point obtained by pre-clearing and the static safety region of each time period in each time period that exceeds the limit, and arranging each intervention time period in descending order;

[0138] S1053. Prioritize the time period with a larger safety distance for correction. Based on the operating point obtained by pre-clearing in this time period, calculate the sensitivity coefficient of each unit to the static safety distance. Consider the restrictions of the unit's previous and subsequent time periods, such as ramping, maximum and minimum technical output, calculate the effectiveness of the unit's adjustment to the safety domain limit in each time period, and determine the set of increased and reduced outputs in this time period.

[0139] S1054, solving the unit output correction plan within the limit-crossing period. If the model has no solution, it is necessary to adjust the start and stop states of the unit to meet the requirements of the safety constraints;

[0140] S1055, check whether there are still active power over-limits in other time periods that have not been processed. If yes, recalculate the static safety distance of the adjacent time periods, and then return to step S1053 to continue adjustment. If no, end;

[0141] S1056. After the intervention is completed, the SCED model is recalculated based on the adjusted clearing boundary conditions. If the requirements of the power grid security constraints are still met, the results of the recalculated SCED will be published.

[0142] like Figure 2 As shown, the embodiment of the present invention also provides an intervention system for abnormal results of power spot trading, including a spot case data management module, a power spot market result abnormal analysis module, and a clearing abnormality auxiliary decision-making control module;

[0143] Spot case data management module, used to obtain case data;

[0144] The power spot market result abnormal analysis module is used to study and propose corresponding abnormal analysis models to identify, locate and analyze abnormal clearing events;

[0145] The clearing anomaly auxiliary management and control module is used to combine the clearing anomaly analysis library, select typical scenarios of various abnormal events, and provide targeted response strategies and processing plans based on the optimal closed-loop correction theory. It can help market operators monitor, diagnose and handle abnormal events to ensure the stable operation of the market.

[0146] The present invention adopts a system architecture in which a spot case data management module, an abnormal analysis module for power spot market results and an abnormal clearing decision-making control module are interconnected to identify, locate and analyze abnormal clearing events of typical abnormal power spot market clearing events, and provide intelligent intervention decision-making reference information to assist in realizing the business closed loop of "market clearing-correction decision adjustment" in the power spot market environment.

[0147] Specifically, first, a unified and standardized data interface is established through the spot case data management module to realize the efficient import of various types of data. After the market is successfully cleared, based on the input data of the spot case data management module, the power spot market result anomaly analysis module is used to analyze the rationality of the input data of the imported case and the clearing result data in terms of abnormal electricity prices, section exceeding the limit, unit output, etc., to discover and warn of possible abnormal situations as the pre-input of the clearing anomaly auxiliary management and control module; for the section exceeding the limit problem that still exists after the market is successfully cleared, the spot market operation personnel can start the clearing anomaly auxiliary management and control module of the clearing anomaly auxiliary research and decision-making tool. The decision-making tool for assisting the research on clearing anomalies first exchanges data with the power spot system through a transit file server and transfers files through the SFTP protocol. Then, based on the optimal closed-loop correction theory, it calculates the static safety domain, the static safety distance, the safety distance sensitivity, the effectiveness of eliminating safety over-limits, the automatic correction of power generation plans, the auxiliary decision modeling, and the deduction of section over-limit abnormality handling measures, etc., thereby providing non-market unit plan adjustment information as an auxiliary decision-making reference and assisting market operators in adjusting unit power generation plans.

[0148] Figure 3 The module diagram of the auxiliary control module for clearing abnormality in an embodiment of the present invention is shown, which specifically includes:

[0149] (1) Case input

[0150] Case input refers to the raw data used for data analysis, which comes from the spot case algorithm package. These raw data will be integrated into the algorithm calibration during the calibration calculation process. The quality and completeness of case input has a crucial impact on the results of calibration analysis;

[0151] (2) Optimization goal

[0152] Optimization target refers to the optimization of the specified unit, section and other target settings during the correction calculation process. During the correction calculation process, it is necessary to formulate appropriate optimization targets based on actual needs and goals for subsequent optimization and evaluation;

[0153] (3) Correction and optimization results

[0154] Correction optimization results refer to the adjustment and correction of case input data during the correction calculation process in order to achieve better clearing results.

[0155] The main purpose of the present invention is to solve the problem that there is an urgent need for a system that can quickly locate the cause and provide corresponding solutions for abnormal clearing events in the power spot market to ensure the stable operation of the power market. Through this system, key models and strategies suitable for abnormal clearing analysis in the power spot trading market can be proposed in a targeted manner, reducing the analytical workload of market operators and promoting the construction of the power spot market.

[0156] The present invention also discloses a computer program product, including a computer program, which executes the steps of the above method when executed by a processor. The present invention further discloses a computer-readable storage medium, which stores a computer program, which executes the steps of the above method when executed by a processor. The present invention also discloses a computer device, including a memory and a processor connected to each other, the memory stores a computer program, and the computer program executes the steps of the above method when executed by the processor.

[0157] The present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiment when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable storage media include: any entity or device that can carry computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. The memory is used to store computer programs and / or modules, and the processor implements various functions by running or executing computer programs and / or modules stored in the memory, and calling data stored in the memory. The memory may include high-speed random access memory and may also include non-volatile memory, such as a hard disk, an internal memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0158] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A method for intervening in abnormal results of spot power trading, characterized in that: Includes steps: S101. Establish a unified and standardized data interface and design a unified market data management format; S102, obtaining case data to be analyzed in the spot system through the spot case data management module; the case data includes all input and output data of the clearing link, which are divided into market model data, clearing parameter data, market boundary data and market result data; S103, using the power spot market result abnormality analysis module to analyze the rationality of power price abnormality, cross-section limit violation, and unit output on the input data and clearing result data of the imported case, and discover and warn of possible abnormal situations; S104. File scanning operations are performed between the clearing anomaly auxiliary research and decision-making tool and the power spot system at a fixed frequency, encrypted transmission and identity authentication are performed through the SFTP protocol, and specific file naming rules and content formats are used to ensure consistency and accuracy; S105. For the problem of safety constraint exceeding the limit that still exists after the pre-clearance of the spot market, the clearing abnormality auxiliary decision-making control module adopts the optimal closed-loop correction theory, selects the period with a larger safety distance for correction, solves the unit output correction plan within the period of exceeding the limit, and recalculates the SCED model based on the adjusted clearing boundary conditions; S106. Use the abnormal clearing auxiliary decision-making management and control module to provide non-market unit plan adjustment information as an auxiliary decision-making reference to assist market operators in adjusting the unit power generation plan.

2. The intervention method applicable to abnormal results of power spot trading according to claim 1 is characterized in that: In step S105, based on the optimal closed-loop correction theory, the static safety domain is calculated, the static safety distance is calculated, the safety distance sensitivity is calculated, the effectiveness of eliminating safety over-limit is analyzed, the automatic correction auxiliary decision modeling of the power generation plan and the deduction of the section over-limit abnormality handling measures are carried out.

3. The intervention method applicable to abnormal results of power spot trading according to claim 2 is characterized in that: The calculation process of the static security domain is: For power generation planning and real-time dispatching, the static safety domain is a collection of a large number of system operating points in the multidimensional space of generator output, taking into account active power balance, unit operating characteristic constraints, and grid security constraints. Using the DC power flow model, the static safety domain is expressed as formula (1): Where P G and P D represents the unit output and node load vector, P Lmax represents the line transmission limit vector; P Gmax and P Gmin are column vectors representing the maximum and minimum technical output of the unit respectively; G g represents the power transfer distribution factor (PTDF) matrix of the node where the generator is located to the line, G represents the transfer distribution factor matrix of all nodes to the line; P Gi represents the unit output of node i, P Dj represents the load demand of node j; M and N represent the collection of units and load nodes respectively.

4. The intervention method applicable to abnormal results of power spot trading according to claim 2 is characterized in that: The calculation process of the static safety distance is: For the safety domain space composed of the maximum and minimum technical output of the unit and the safety constraints, if the planned operating point of the t period is obtained by pre-clearing If the limit is exceeded, the distance from the point to the hyperplane formed by the i-th constraint boundary on the boundary of the safety region is expressed as: Where P G,t represents the unit output column vector corresponding to any point on the i-th constraint boundary of the safety domain within the t period; P D,t represents the column vector composed of the node loads in period t; P Lmax represents the line transmission quota column vector, P Lmax,i represents the limit of the ith line; G t G represents the PTDF matrix of all nodes in period t; g,t represents the PTDF matrix of the power generation node during period t; e i represents the unit column vector [0,…,1,0,…,0] T , there is only a non-zero element at the i-th position; According to the model of formula (2), for point Calculate the distance to the hyperplane where each safety zone boundary constraint is located, expressed as: ||d 1,t ||,…,||d i,t ||,…,||d n,t ||, where n represents the number of effective constraints that form the security domain boundary, d i,t Represents the hyperplane and point where the i-th constraint is located The minimum value of the distance from the operating point to the hyperplane where each boundary of the safety domain space is located is the static safety distance of the operating point: the t min =||d t min ||=min(||d 1,t ||,…,||d i,t ||,…,||d n,t ||) (3) Where, d t min Represents the planned point in period t The static safety distance value, d t min is the static safety distance vector.

5. The intervention method applicable to abnormal results of power spot trading according to claim 2, characterized in that: The calculation process of the safety distance sensitivity coefficient is: The direction of the static safety distance vector is defined as the point P on the safety domain boundary that is closest to the planned operating point. G,t , pointing to the planned operation point This vector reveals the multidimensional unit output space that makes the point Adjust to the optimal adjustment direction within the safety range; therefore, the limit point The static safety distance vector d tmin The output of each unit is differentiated to obtain the safety distance sensitivity coefficient of the unit: In the formula, e j represents the unit column vector [0,…,1,0,…,0] T , there are non-zero elements only at the position of the jth unit; From a physical point of view, when E dt,j When it is a positive value, it means that the current planned operation point Based on the increase in the output of unit j, the planned operating point Closer to point P on the security domain G,t , which is conducive to shortening the over-limit safety distance; similarly, if it is a negative value, it means that reducing the output of unit j is conducive to shortening the over-limit safety distance; the size of the safety distance sensitivity coefficient reveals the global effect of the change in the unit output on reducing the active over-limit amplitude.

6. The intervention method applicable to abnormal results of power spot trading according to claim 2, characterized in that: The process of effectiveness analysis for eliminating safety over-limit is as follows: In order to minimize the number of units to be corrected, the safety distance sensitivity and adjustment capability of the units should be considered at the same time to obtain the effectiveness ranking of the units in eliminating safety violations; units with positive safety distance sensitivity should be preferentially selected to be included in the set of increased output, and units with negative safety distance sensitivity should be included in the set of reduced output; the adjustment capability of the units is limited by the maximum and minimum technical outputs, as well as the climbing capability in adjacent periods, and the adjustment capability of the increased output units It is expressed as: Similarly, the adjustment capability of the reduced output unit It is expressed as: Where P Gi,max and P Gj,min They represent the maximum technical output of unit i and the minimum technical output of unit j respectively; and They represent the planned output of unit i and unit j before correction in period t respectively; and They represent the connection output of unit i in time periods t-1 and t+1 before correction of time period t. According to the multi-time period connection strategy, if the safety distance of the adjacent time period exceeds the limit greater than that of time period t, then and It means that after the correction at time periods t-1 and t+1, the new planned output of unit i is obtained; similarly, and They respectively represent the correction connection output points of unit j in adjacent time periods; and Respectively represent the climbing capabilities of units i and j; and They respectively represent the maximum increased power generated by the increased output unit subject to the unit output limit, the climbing capacity constraint limit of the previous period and the next period; and They respectively represent the maximum power reduction caused by the output limit of the unit, the climbing capacity constraint limit of the previous period and the next period; For the increased output unit, its contribution to eliminating the safety zone crossing within the t period is: For the reduced output unit, its contribution to eliminating the safety zone crossing within the t period is: In the formula, E dt,i and E dt,j Respectively represent the safety distance sensitivity values ​​of unit i and unit j in time period t; according to and The values ​​are used to arrange the units with increased output and units with reduced output in descending order, which serves as the basis for subsequent correction decision modeling.

7. The intervention method applicable to abnormal results of power spot trading according to claim 6, characterized in that: The process of automatic correction auxiliary decision modeling of power generation plan is as follows: The sequence of the increased and decreased output units in each over-limit period is calculated by equations (5)-(8). The increased and decreased output units with the same ranking form an adjustment pair. The adjustment pairs with the higher ranking are first included in the linear correction decision model in order, as shown in equations (9)-(17); If the model has no solution, a new adjustment pair is included in the sequence for solution; if the distance that exceeds the safety zone boundary has not been eliminated, the adjustment capacity of the original unit that increases or reduces the output has been exhausted. At this time, the unit with a safety distance sensitivity coefficient of 0 is selected for reverse pairing to form a new unit adjustment pair; if the adjustment capacity of the unit with a sensitivity of 0 is also exhausted, the unit with a smaller positive sensitivity coefficient is selected as the object of increasing the output, and the unit with a larger negative sensitivity coefficient is selected as the object of reducing the output. The linear correction decision model aims to minimize the adjustment amount; Where M t and N t They represent the sets of units with increased and reduced outputs formed by adjusting the selected units in the time period t; L kbase,t represents the active component caused by non-correction decision-making units and loads on line k during period t; L kmax G represents the active transmission limit of line k; i and G j They respectively represent the active sensitivity of the unit i with increased output and the unit j with reduced output to the line k; Formula (8) represents the power balance constraint within the time period; Formulas (9)-(12) represent the output connection between time period t and the adjacent time period, which should meet the climbing capacity constraint; Formulas (13)-(14) represent that the unit correction output should be within the range of maximum and minimum technical outputs; Formula (15) represents the active power flow constraint.

8. The intervention method for abnormal results of power spot trading according to any one of claims 1 to 7, characterized in that: The specific process of step S104 is: S1041. After the electricity spot system completes the release of the spot day case clearing every day, it sends the algorithm data package file to the designated directory of the spot file server; the data package file includes the algorithm input and output information of the electricity spot transaction; S1042. The clearing anomaly auxiliary research decision-making tool scans and reads the latest clearing complete algorithm data file from the specified directory of the spot file server at a fixed time every day to provide basic data for anomaly analysis and closed-loop correction calculation; S1043. After reading these data, the abnormality-clearing auxiliary research decision-making tool will perform abnormality-clearing analysis and closed-loop correction calculations to find abnormal situations and make corrections. After completing the closed-loop correction calculations, the system will send the intervention results to the designated directory of the abnormality-clearing auxiliary research decision-making tool file server; The S10414 power spot system will scan and read the latest non-market unit plan data files from the specified directory of the clearing anomaly auxiliary research and decision-making tool file server at a fixed time every day; The data file contains the intervention results, that is, the new non-market unit plan data file. After reading this data, the electricity spot system will display the results in the system and allow the user to operate whether to use the new non-market unit plan as input for re-clearing.

9. The intervention method for abnormal results of power spot trading according to any one of claims 1 to 7, characterized in that: In step S105, if there is still a safety constraint violation after the spot market is pre-cleared, the decision-making process for implementing power generation plan correction is as follows: S1051. First, based on the pre-clearing results of the day-ahead spot market, all time periods with active power exceeding the limit and the corresponding exceeding-limit sections of each time period are screened; S1052, respectively calculating the minimum distance between the planned operation point obtained by pre-clearing and the static safety region of each time period in each time period that exceeds the limit, and arranging each intervention time period in descending order; S1053. Prioritize the time period with a larger safety distance for correction. Based on the operation point obtained by pre-clearing in this time period, calculate the sensitivity coefficient of each unit to the static safety distance. Consider the ramping of the unit before and after the time period and the maximum and minimum technical output limits, calculate the effectiveness of the unit's adjustment to the safety domain limit in each time period, and determine the increase and decrease output set of the time period. S1054, solving the unit output correction plan within the limit-crossing period. If the model has no solution, it is necessary to adjust the start and stop states of the unit to meet the requirements of the safety constraints; S1055, check whether there are still active power over-limits in other time periods that have not been processed. If yes, recalculate the static safety distance of the adjacent time periods, and then return to step S1053 to continue adjustment. If no, end; S1056. After the intervention is completed, the SCED model is recalculated based on the adjusted clearing boundary conditions. If the requirements of the power grid security constraints are still met, the results of the recalculated SCED will be published.

10. An intervention system for abnormal results of power spot trading, characterized in that: It includes spot case data management module, power spot market result abnormality analysis module and clearing abnormality auxiliary control module; The spot case data management module is used to establish a unified and standardized data interface to obtain case data; The power spot market result abnormality analysis module is used to build an abnormality analysis model to identify, locate and analyze abnormal clearing events; The clearing anomaly auxiliary control module is used to combine the clearing anomaly analysis library, select typical scenarios where various abnormal events occur, and provide targeted response strategies and processing plans based on the optimal closed-loop correction theory.

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