A method, device and medium for processing power generation constraints based on redundant constraint filtering

Abstract

The present invention discloses a power generation constraint processing method, device, and medium based on redundant constraint filtering. The method obtains a power grid model and a set of expected faults, performs power flow analysis on a base state and each expected fault state according to the power grid model and power flow equation, and generates a first network security constraint. The method then performs redundant constraint filtering on the first network security constraint to obtain a second network security constraint, thereby reducing the set of key constraints that need to be analyzed. The method then performs sensitivity analysis on the second network security constraint and determines the second network security constraint as the first unit power generation constraint. The method then filters the first unit power generation constraint according to the unit output range to obtain a second unit power generation constraint, thereby reducing the number of power generation constraints. Based on the second unit power generation constraint, a power generation constraint linear programming model is constructed and solved to obtain the allowable power generation range of each unit. The present invention can reduce the scale of existing unit power generation analysis calculations and reduce the number of branches, thereby improving computational efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid security analysis and control, and in particular to a power generation constraint processing method, device, storage medium and terminal equipment based on redundant constraint filtering. Background Art

[0002] As living standards continue to improve, the demand for electricity is also increasing. Maintaining the safe operation of power systems has become a key concern. To ensure safe operation, the power grid must be able to withstand certain anticipated faults. Specifically, when a predicted fault occurs, some power equipment will be shut down, while the power flow to the remaining equipment will not exceed its short-term overload capacity. This allows the power system to continue operating safely, preventing cascading trips and allowing sufficient time for personnel to resolve the fault.

[0003] When a power grid fault occurs, if the grid structure is sufficiently robust, each unit can be freely arranged according to load needs. However, this is ideal. If the grid structure is not robust, to ensure the safe operation of the power system, requirements will be placed on the power generation of the unit equipment, including peak power and congestion power. Peak power requires that the unit must be turned on and maintain output above a certain value. The minimum output allowed for the unit is called peak power. Congestion power requires that the unit output not exceed a certain value, namely the maximum available output. The portion of the unit capacity that exceeds the maximum available power is called congestion power. Therefore, when a power grid fault occurs, every effort must be made to avoid congestion power. Congestion power analysis of the unit is a key method to avoid this. Existing congestion power analysis requires sensitivity analysis of the base state and the predicted state power flow. Due to the large scale of the predicted fault set and the large number of branches, performing sensitivity analysis on all branches in the grid individually would be extremely computationally intensive.

[0004] Therefore, there is an urgent need on the market for a strategy that can solve the problems of huge calculation scale and large number of branches in the existing unit power consumption analysis. Summary of the Invention

[0005] The present invention provides a power generation constraint processing method based on redundant constraint filtering, which can reduce the scale of existing unit power consumption analysis and calculation and reduce the number of branches.

[0006] An embodiment of the present invention provides a method for processing power generation constraints based on redundant constraint filtering, the steps of which include:

[0007] Acquire a power grid model and a set of anticipated faults, wherein the set of anticipated faults includes a base state and various anticipated fault states;

[0008] performing power flow analysis on the base state and each of the anticipated fault states according to the power grid model and the power flow equation, and generating a first network security constraint according to the analysis result;

[0009] Performing redundant constraint filtering on the first network security constraint to obtain a second network security constraint, so as to reduce a set of key constraints that need to be analyzed;

[0010] performing a sensitivity analysis on the second network security constraint, and determining the second network security constraint as a power generation constraint of the first unit according to the analysis result;

[0011] filtering the first unit power generation constraints according to the unit output range to obtain the second unit power generation constraints, thereby reducing the number of power generation constraints;

[0012] Constructing a power generation constraint linear programming model based on the power generation constraint of the second unit;

[0013] The power generation constraint linear programming model is solved according to the optimization algorithm to obtain the allowable power generation range of each unit.

[0014] As a preferred solution, the first network security constraint includes a base state power flow constraint and a fault state power flow constraint, specifically:

[0015]

[0016]

[0017] Among them, C is the expected fault set; represents the active power flow of branch j after the occurrence of the anticipated fault k; and Represent the base-state active power flow of branches i and j respectively; It represents the power flow transfer coefficient of the disconnected branch i to the non-disconnected branch j after the expected fault k occurs; represents the set of branches disconnected by the expected fault k; represents the set of operating branches after the expected fault k occurs, Indicates the short-time allowable current carrying capacity of branch j.

[0018] As a preferred solution, the step of filtering redundant constraints on the first network security constraint to obtain the second network security constraint to reduce the set of key constraints that need to be analyzed is specifically as follows:

[0019] Determine a branch coefficient, and select a branch to be monitored within the base state power flow constraint according to the branch coefficient and the base state branch active power flow to obtain a base state monitoring branch set;

[0020] Selecting a branch to be monitored in the fault state power flow constraint according to the branch coefficient and the short-time allowable current carrying capacity, to obtain a fault state monitoring branch set;

[0021] Obtaining a first network security-constrained monitoring branch set according to the base state monitoring branch set and the fault state monitoring branch set;

[0022] It is determined whether the short-term overload multiple is greater than 1. If it is greater than 1, the monitoring branch set of the first network security constraint is filtered to obtain a second network security constraint.

[0023] As a preferred solution, the step of performing a sensitivity analysis on the second network security constraint and determining the second network security constraint as the power generation constraint of the first unit according to the analysis result is specifically:

[0024] Linearizing the tidal current equation to obtain a linearized tidal current equation;

[0025] Perform Taylor series expansion on the second network safety constraint branch power flow and filter out higher-order terms above the second order to obtain the Taylor series expansion of the second network safety constraint branch power flow;

[0026] Obtaining a sensitivity matrix according to the linearized power flow equation and the Taylor series expansion;

[0027] According to the sensitivity matrix, the second network security constraint is determined as the first unit power generation constraint.

[0028] As a preferred solution, after the step of performing a sensitivity analysis on the second network security constraint and determining the second network security constraint as the power generation constraint of the first unit according to the analysis result, the method further includes:

[0029] It is determined whether the absolute value of the unit sensitivity of the power generation constraint of the first unit is less than a set threshold. If it is less than the set threshold, the unit is filtered.

[0030] As a preferred solution, the step of filtering the first unit power generation constraints according to the unit output range to obtain the second unit power generation constraints to reduce the number of power generation constraints is specifically:

[0031] Obtaining a monitoring branch set of the first unit's power generation constraint according to the first unit's power generation constraint and the active power flow of the equipment group;

[0032] The monitoring branch set of the first unit power generation constraint is filtered according to the unit output range to obtain the second unit power generation constraint.

[0033] As a preferred solution, the power generation constraint linear programming model is specifically as follows:

[0034] max w

[0035]

[0036] in, and They represent the maximum available output, peak power and capacity of unit g respectively; w represents the minimum adjustment freedom of the unit.

[0037] Accordingly, another embodiment of the present invention further provides a power generation constraint processing device based on redundant constraint filtering, comprising: an information acquisition module, a power flow analysis module, a redundant filtering module, a sensitivity analysis module, a filtering module, a model building module, and a model solving module;

[0038] The information acquisition module is used to obtain a power grid model and a predicted fault set, wherein the predicted fault set includes a base state and each predicted fault state;

[0039] The power flow analysis module is used to perform power flow analysis on the base state and each of the anticipated fault states according to the power grid model and the power flow equation, and generate a first network security constraint according to the analysis result;

[0040] The redundancy filtering module is used to perform redundant constraint filtering on the first network security constraint to obtain a second network security constraint, so as to reduce the key constraint set that needs to be analyzed;

[0041] The sensitivity analysis module is configured to perform a sensitivity analysis on the second network security constraint, and determine the second network security constraint as the power generation constraint of the first unit according to the analysis result;

[0042] The filtering module is used to filter the first unit power generation constraints according to the unit output range to obtain the second unit power generation constraints, so as to reduce the number of power generation constraints;

[0043] The model building module is used to build a power generation constraint linear programming model according to the power generation constraint of the second unit;

[0044] The solving module is used to solve the power generation constraint linear programming model according to the optimization algorithm to obtain the allowable power generation range of each unit.

[0045] As a preferred solution, the first network security constraint includes a base state power flow constraint and a fault state power flow constraint, specifically:

[0046]

[0047]

[0048] Among them, C is the expected fault set; represents the active power flow of branch j after the occurrence of the anticipated fault k; and Represent the base-state active power flow of branches i and j respectively; It represents the power flow transfer coefficient of the disconnected branch i to the non-disconnected branch j after the expected fault k occurs; represents the set of branches disconnected by the expected fault k; represents the set of operating branches after the expected fault k occurs, Indicates the short-time allowable current carrying capacity of branch j.

[0049] As a preferred solution, the redundant filtering module includes: a base state monitoring unit, a fault state monitoring unit, a network security constraint monitoring unit and a filtering unit;

[0050] The base state monitoring unit is used to determine a branch coefficient, and select a branch to be monitored in the base state power flow constraint according to the branch coefficient and the base state branch active power flow, to obtain a base state monitoring branch set;

[0051] The fault state monitoring unit is used to select a branch to be monitored in the fault state power flow constraint according to the branch coefficient and the short-time allowable current carrying capacity, and obtain a fault state monitoring branch set;

[0052] The network security constraint monitoring unit is configured to obtain a monitoring branch set of a first network security constraint according to the base state monitoring branch set and the fault state monitoring branch set;

[0053] The filtering unit is used to determine whether the short-term overload multiple is greater than 1. If it is greater than 1, the monitoring branch set of the first network security constraint is filtered to obtain a second network security constraint.

[0054] As a preferred solution, the sensitivity analysis module includes: a linearization unit, a Taylor series expansion unit, a matrix acquisition unit and a unit power generation constraint generation unit.

[0055] The linearization unit is used to linearize the power flow equation to obtain a linearized power flow equation;

[0056] The Taylor series expansion unit is used to perform Taylor series expansion on the second network security constraint branch power flow and filter out higher-order terms of the second order and above to obtain a Taylor series expansion of the second network security constraint branch power flow;

[0057] The matrix acquisition unit is used to obtain a sensitivity matrix according to the linearized power flow equation and the Taylor series expansion;

[0058] The unit power generation constraint generating unit is configured to determine the second network security constraint as the first unit power generation constraint according to the sensitivity matrix.

[0059] As a preferred solution, the sensitivity analysis module is further specifically used to determine whether the absolute value of the unit sensitivity of the power generation constraint of the first unit is less than a set threshold. If it is less than the set threshold, the unit is filtered.

[0060] As a preferred solution, the filtering module includes: a unit power generation constraint monitoring unit and a filtering unit;

[0061] The unit power generation constraint monitoring unit is used to obtain a monitoring branch set of the first unit power generation constraint according to the first unit power generation constraint and the active power flow of the equipment group;

[0062] The filtering unit is used to filter the monitoring branch set of the first unit power generation constraint according to the unit output range to obtain the second unit power generation constraint.

[0063] As a preferred solution, the power generation constraint linear programming model is specifically as follows:

[0064] max w

[0065]

[0066] in, and They represent the maximum available output, peak power and capacity of unit g respectively; w represents the minimum adjustment freedom of the unit.

[0067] An embodiment of the present invention also provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute a power generation constraint processing method based on redundant constraint filtering as described in any one of the above items.

[0068] An embodiment of the present invention also provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when executing the computer program, the processor implements a power generation constraint processing method based on redundant constraint filtering as described in any one of the above items.

[0069] Compared with the prior art, the embodiment of the present invention provides a power generation constraint processing method based on redundant constraint filtering, which has the following beneficial effects: by performing power flow analysis on the base state and each expected fault state to generate a first network security constraint, the power flow analysis results before and after the expected fault can be combined to form a new network security constraint, preparing for subsequent redundant constraint filtering; by redundantly filtering the first network security constraint to obtain a second network security constraint, the number of branches required for calculation and the calculation scale can be reduced, thereby improving calculation efficiency; by converting the second network security constraint into the first unit power generation constraint, the unit power generation constraint can be subsequently filtered by the unit output range conditions, and it also prepares for the subsequent solution of the minimum adjustment freedom of the unit to be maximized; by filtering the first unit power generation constraint according to the unit output range to obtain the second unit power generation constraint, the number of branches involved in the sensitivity analysis can be reduced, and sensitivity analysis is only performed on a small number of key branches, reducing the calculation scale and improving calculation efficiency. By constructing and solving the model, the power congestion of all units can be obtained, thereby obtaining the allowable power generation range of each unit in the power grid, so that the arrangement of the power grid operation mode can reduce network congestion, avoid power congestion of units, and improve the reliability of the safe operation of the power system. The present invention filters the fault-state branch flow constraints and adds only the constraints that are likely to work into the optimization model, thereby reducing the number of fault-state constraints in the power congestion analysis problem, reducing the scale of the existing unit power congestion analysis calculation and the number of branches, and improving calculation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 Schematic diagram of a flow chart of a method for processing power generation constraints based on redundant constraint filtering according to an embodiment of the present invention;

[0071] Figure 2 The figure is a structural diagram of a power generation constraint processing device based on redundant constraint filtering according to an embodiment of the present invention.

[0072] The instruction manual is attached Figure 2 The reference numerals are as follows: information acquisition module 21 , power flow analysis module 22 , redundancy filtering module 23 , sensitivity analysis module 24 , filtering module 25 , model building module 26 and model solving module 27 . DETAILED DESCRIPTION

[0073] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0074] Example 1

[0075] Please refer to Figure 1 , a power generation constraint processing method based on redundant constraint filtering provided by an embodiment of the present invention, the steps of which include:

[0076] A power grid model and a set of anticipated faults are obtained, wherein the set of anticipated faults includes a base state and various anticipated fault states.

[0077] Specifically, the power grid model and the expected fault set are obtained. The power grid model includes information such as the total load, the total installed capacity of the units, and various types of units. The expected fault set is measurement data, including the base state and various expected fault states. By obtaining the expected state fault set of the power grid model, preparations are made for subsequent power flow analysis.

[0078] According to the power grid model and the power flow equation, power flow analysis is performed on the base state and each of the anticipated fault states, and a first network security constraint is generated according to the analysis result.

[0079] Specifically, after obtaining the total load of the power grid, the total installed capacity of the generating units, various types of generating units, and measurement data, the base state flow calculation and the flow calculation of each expected fault state are performed on the above data according to the flow equation to obtain the flow transfer relationship. Then, based on the flow transfer relationship, a network security constraint is generated, namely the first network security constraint. By generating the network security constraint, the flow analysis results before and after the expected fault can be combined to form a new network security constraint, preparing for the subsequent redundant constraint filtering.

[0080] Redundant constraints are filtered out of the first network security constraints to obtain second network security constraints, so as to reduce the key constraint sets that need to be analyzed.

[0081] Specifically, after obtaining the network security constraint generated by the power flow transfer relationship, redundancy filtering is performed on it, filtering out some key constraint sets that do not need to be analyzed, retaining the remaining key constraint sets that need to be analyzed, and then obtaining the network security constraint after redundant filtering, that is, the second network security constraint; by performing redundant filtering on the network security constraint, the number of branches that need to be calculated and the calculation scale can be reduced, thereby improving calculation efficiency.

[0082] A sensitivity analysis is performed on the second network security constraint, and according to the analysis result, the second network security constraint is determined as the power generation constraint of the first unit.

[0083] Specifically, after obtaining the redundantly filtered network security constraints, a sensitivity analysis is performed on them. Based on the sensitivity analysis results, the network security constraints can be described as the unit power generation constraints, that is, the first unit power generation constraints. By converting the network security constraints into unit power generation constraints, the unit power generation constraints can be filtered using the unit output range conditions to reduce the number of power generation constraints that need to be analyzed, and also prepare for the subsequent solution to maximize the minimum adjustment freedom of the unit.

[0084] The first unit power generation constraints are filtered according to the unit output range to obtain the second unit power generation constraints, so as to reduce the number of power generation constraints.

[0085] Specifically, after converting network security constraints into unit power generation constraints, these constraints are filtered based on the unit's output range. Constraints that do not meet the unit's output range are filtered out, while those that do meet the unit's output range are retained, resulting in the filtered unit power generation constraints. By filtering unit power generation constraints based on the unit's output range, the number of branches involved in the sensitivity analysis can be reduced, allowing sensitivity analysis to be performed on only a few critical branches, thereby reducing the computational scale and improving computational efficiency.

[0086] According to the power generation constraints of the second unit, a power generation constraint linear programming model is constructed.

[0087] Specifically, according to the power generation constraints of the units obtained after filtering, a power generation constraint linear programming model is constructed to obtain the minimum adjustment freedom of each unit. and They represent the maximum available output, peak power and capacity of unit g respectively; w represents the minimum adjustment freedom of the unit, and its Lagrange multiplier can determine which units' adjustment freedom is equal to the minimum adjustment freedom w, and lock the maximum available output and peak power of the units whose adjustment freedom is equal to the minimum adjustment freedom. By solving the model, the allowable power generation range of each unit is obtained.

[0088] The power generation constraint linear programming model is solved according to the optimization algorithm to obtain the allowable power generation range of each unit.

[0089] Specifically, after constructing a power generation constraint linear programming model, the model is solved according to the optimization algorithm to obtain the power congestion situation of all units, thereby obtaining the allowable power generation range of each unit in the power grid. The arrangement of the power grid operation mode can reduce network congestion, avoid unit power congestion, and improve the reliability of the safe operation of the power system.

[0090] In an embodiment of the present invention, a method for processing power generation constraints based on redundant constraint filtering is provided. The method has the following advantages: by performing power flow analysis on the base state and each expected fault state to generate a first network security constraint, the power flow analysis results before and after the expected fault can be combined to form a new network security constraint, preparing for subsequent redundant constraint filtering; by performing redundant filtering on the first network security constraint to obtain a second network security constraint, the number of branches required for calculation and the calculation scale can be reduced, thereby improving calculation efficiency; by converting the second network security constraint into the first unit power generation constraint, the unit power generation constraint can be subsequently filtered using the unit output range conditions, while also preparing for the subsequent solution of the maximum minimum adjustment freedom of the unit; by filtering the first unit power generation constraint according to the unit output range to obtain the second unit power generation constraint, the number of branches involved in sensitivity analysis can be reduced, and sensitivity analysis can be performed on only a small number of key branches, thereby reducing the calculation scale and improving calculation efficiency. By constructing and solving the model, the power congestion of all units can be obtained, thereby obtaining the allowable power generation range of each unit in the power grid, so that the arrangement of the power grid operation mode can reduce network congestion, avoid power congestion of units, and improve the reliability of safe operation of the power system. The present invention filters the fault-state branch flow constraints and adds only the constraints that are likely to work into the optimization model, thereby reducing the number of fault-state constraints in the power congestion analysis problem, reducing the scale of the existing unit power congestion analysis calculation and the number of branches, and improving calculation efficiency.

[0091] In another embodiment of the present invention, a method for processing power generation constraints based on redundant constraint filtering is provided, wherein the first network security constraint includes a base state power flow constraint and a fault state power flow constraint, specifically:

[0092]

[0093]

[0094] Among them, C is the expected fault set; represents the active power flow of branch j after the occurrence of the anticipated fault k; and Represent the base-state active power flow of branches i and j respectively; It represents the power flow transfer coefficient of the disconnected branch i to the non-disconnected branch j after the expected fault k occurs; represents the set of branches disconnected by the expected fault k; represents the set of operating branches after the expected fault k occurs, Indicates the short-time allowable current carrying capacity of branch j.

[0095] Perform power flow analysis on the base state and each anticipated fault state to generate network security constraints represented by power flow transfer relationships. The power flow analysis results before and after the anticipated fault can be combined to form new network security constraints, preparing for subsequent redundant constraint filtering.

[0096] In another embodiment of the present invention, a method for processing power generation constraints based on redundant constraint filtering is provided. The steps of performing redundant constraint filtering on the first network security constraint to obtain the second network security constraint to reduce the set of key constraints that need to be analyzed are specifically as follows:

[0097] A branch coefficient is determined, and according to the branch coefficient and the active power flow of the base-state branch, a branch to be monitored is selected within the base-state power flow constraint to obtain a base-state monitoring branch set.

[0098] Specifically, the sum of the active power flows flowing into the device group is defined as the active power flow of the device group, and the ratio of the branch active power flow value to the active power flow of the device group is defined as the branch coefficient, that is:

[0099]

[0100] Where K Bj represents the branch coefficient of branch j in its corresponding device group; P Bj represents the active power flow of branch j; g represents the equipment group number; P Σg Represents the total active power flow of equipment group g; S G Represents a collection of device groups; Indicates the operating branch set in the base state of device group g.

[0101] Define the branches to monitor. The active power flow distribution ratios for each branch within a device group are approximately constant. Therefore, within each device group, only the branch with the largest ratio of branch coefficient to allowable current capacity needs to be monitored. The branch selected for monitoring is the one most likely to exceed limits in the device group's operating state. If the active power flow of this branch does not exceed limits, the active power flow of all branches in the device group will also remain within limits.

[0102] For the base state branch power flow constraint, the branch to be monitored can be selected according to formula (4).

[0103]

[0104] The base-state branch active power flow is described as a function of the monitoring branch active power flow, that is:

[0105]

[0106] Where M j Indicates the base monitoring branch number of the device group to which branch j belongs.

[0107] According to the branch coefficient and the short-time allowable current carrying capacity, branches that need to be monitored are selected in the fault state power flow constraint to obtain a fault state monitoring branch set.

[0108] Specifically, for the fault branch power flow constraint, the branch to be monitored can be selected according to formula (6).

[0109]

[0110] Where, Represents the operating branch set under fault state k of device group g.

[0111] A monitoring branch set of a first network security constraint is obtained according to the base state monitoring branch set and the fault state monitoring branch set.

[0112] Specifically, the update only requires monitoring the network security constraints of the branch, namely:

[0113]

[0114]

[0115] Where, It is the set of monitoring branches under the fault state k of each equipment group.

[0116] It is determined whether the short-term overload multiple is greater than 1. If it is greater than 1, the monitoring branch set of the first network security constraint is filtered to obtain a second network security constraint.

[0117] Specifically, the monitoring branch set of the first network security constraint is filtered by utilizing the characteristic that the short-term overload multiple is greater than 1, that is:

[0118]

[0119] remember:

[0120]

[0121] but When the power grid base state flow meets the safety constraints The upper bound of is a constant that has nothing to do with the operating state of the power grid.

[0122] like

[0123]

[0124] Then the corresponding inequality constraint in formula (8) must hold, that is, the corresponding constraint is a redundant constraint and can be filtered, which has no effect on the optimization result.

[0125] By selecting the branches that need to be monitored in the base-state power flow constraints, some branches that do not need to be analyzed in the base-state power flow constraints can be filtered out, which can reduce the number of branches that need to be calculated and the calculation scale. At the same time, by selecting the branches that need to be monitored in the fault-state power flow constraints, some branches that do not need to be analyzed in the fault-state power flow constraints can be filtered out, which can reduce the number of branches that need to be calculated and the calculation scale. Then, taking advantage of the characteristic that the short-term overload multiple is greater than 1, the fault-state power flow constraints are filtered a second time to further reduce the number of branches that need to be calculated and improve calculation efficiency.

[0126] In another embodiment of the present invention, a method for processing power generation constraints based on redundant constraint filtering is provided, wherein the step of performing a sensitivity analysis on the second network security constraint and determining the second network security constraint as the power generation constraint of the first unit according to the analysis result is specifically as follows:

[0127] The tidal current equation is linearized to obtain a linearized tidal current equation.

[0128] Specifically, the tidal flow equation is linearized, namely:

[0129]

[0130] Where, Δe=[Δe1,Δe2…Δe n ], Δf=[Δf1,Δf2…Δf n ].

[0131] Therefore:

[0132]

[0133] Where ΔP and ΔQ represent the matrix of the change in active power flow and reactive power flow of each branch, respectively; Δe and Δf represent the matrix of the change in the real and imaginary parts of the voltage of each node, respectively; J represents the Jacobian matrix of the power flow of each branch to the voltage of each node; Δe n and Δf n Represent the changes in the real and imaginary parts of the voltage at node n respectively.

[0134] The Taylor series expansion of the second network safety constraint branch power flow is performed and the higher-order terms above the second order are filtered out to obtain the Taylor series expansion of the second network safety constraint branch power flow.

[0135] Specifically, the Taylor series expansion is performed on the power flow of the second network security constraint branch, ignoring the higher-order terms above the second order, that is:

[0136]

[0137] Where:

[0138]

[0139]

[0140] Substituting into (13) and (14), we get:

[0141]

[0142] A sensitivity matrix is obtained according to the linearized power flow equation and the Taylor series expansion.

[0143] Specifically, let:

[0144]

[0145] Then the sensitivity matrix A ij The element corresponding to the active power injection of the generator bus is the sensitivity of the branch active power flow to the active output of the unit.

[0146] According to the sensitivity matrix, the second network security constraint is determined as the first unit power generation constraint.

[0147] Specifically, assuming that the reactive power injected by the busbar remains unchanged, that is, ΔQ = 0, equation (18) can be simplified to:

[0148]

[0149] The branch active power flow P ij Described as a linear function of the unit output, that is, the power generation constraint of the first unit:

[0150]

[0151] Where, It represents the constant term of the branch active power flow function.

[0152] By performing sensitivity analysis on network security constraints based on the sensitivity matrix, the network security constraints are converted into a linear function of the unit output, that is, the network security constraints are described as unit power generation constraints represented by the unit output. This allows the unit power generation constraints to be filtered through the conditions of the unit output range to reduce the number of power generation constraints that need to be analyzed, and also prepares for the subsequent solution to maximize the minimum adjustment freedom of the unit.

[0153] Among them, in another embodiment of the present invention, a power generation constraint processing method based on redundant constraint filtering is provided. After the step of performing sensitivity analysis on the second network security constraint and determining the second network security constraint as the power generation constraint of the first unit according to the analysis result, it also includes: judging whether the absolute value of the unit sensitivity of the power generation constraint of the first unit is less than a set threshold; if it is less than the set threshold, filtering the unit.

[0154] Specifically, in practical applications, units with very low sensitivity can be ignored, and only the absolute value of the sensitivity is retained. The unit's sensitivity is greater than a certain threshold (such as 0.03). The unit's power generation constraints can be filtered by the condition that the absolute value of the unit's sensitivity is less than a certain threshold to reduce the number of power generation constraints that need to be analyzed.

[0155] In another embodiment of the present invention, a method for processing power generation constraints based on redundant constraint filtering is provided. The steps of filtering the first power generation constraints of the first unit according to the unit output range to obtain the second power generation constraints of the second unit to reduce the number of power generation constraints are specifically as follows:

[0156] A monitoring branch set of the first unit power generation constraint is obtained according to the first unit power generation constraint and the active power flow of the equipment group.

[0157] Specifically, only the power generation constraints of the monitoring branches of each equipment group are considered, that is:

[0158]

[0159]

[0160] Where, It is a collection of monitoring branches of each device group in the base state.

[0161] The monitoring branch set of the first unit power generation constraint is filtered according to the unit output range to obtain the second unit power generation constraint.

[0162] Specifically, for a fault-free state, the branch current is required to be less than its long-term current carrying capacity, that is:

[0163]

[0164] For the anticipated fault state, the branch current is required to be less than its short-term current carrying capacity, that is:

[0165]

[0166] Since the unit may output In formula (23) or formula (24), if the unit with positive sensitivity value takes the maximum output The unit with negative sensitivity value takes the minimum output of 0, which can obtain the maximum forward power that may flow through the branch; on the contrary, if the unit with positive sensitivity value takes the minimum output of 0, the unit with negative sensitivity value takes the maximum output. The minimum forward power (or maximum reverse power) that can flow through the branch can be obtained. If the maximum and minimum powers that can occur in the branch are both within the corresponding allowable range, it means that the unit output can be adjusted arbitrarily within the allowable range and branch ij will not be overloaded. Such constraints do not need to be considered.

[0167] By filtering the unit power generation constraints according to the unit output range, the unit power generation constraints can be filtered according to the filtering conditions of branch flow and current carrying capacity, so that only the units with output ranges that meet the requirements are retained, otherwise they are filtered out, reducing the number of branches participating in the sensitivity analysis, and only performing sensitivity analysis on a small number of key branches, thereby reducing the calculation scale and improving the calculation efficiency.

[0168] Among them, in another embodiment of the present invention, a power generation constraint processing method based on redundant constraint filtering is provided, wherein the power generation constraint linear programming model is specifically:

[0169]

[0170] in, and They represent the maximum available output, peak power and capacity of unit g respectively; w represents the minimum adjustment freedom of the unit.

[0171] According to the filtered unit power generation constraints, the minimum adjustment freedom of each unit can be obtained by constructing a power generation constraint linear programming model with the minimum adjustment freedom of the unit as the goal. and its Lagrange multiplier can determine which units have the minimum degree of freedom of regulation w. Since only some units have the minimum degree of freedom of regulation w, the degree of freedom of regulation of the remaining units can be further increased. Lock the maximum available output and peak power of the units with the minimum degree of freedom of regulation w, and ignore the formula The constraints of the corresponding units in .

[0172] Example 2

[0173] Accordingly, please refer to Figure 2 , a power generation constraint processing device based on redundant constraint filtering provided by an embodiment of the present invention includes: an information acquisition module, a power flow analysis module, a redundant filtering module, a sensitivity analysis module, a filtering module, a model building module and a model solving module.

[0174] The information acquisition module is used to acquire a power grid model and a predicted fault set, wherein the predicted fault set includes a base state and various predicted fault states.

[0175] The power flow analysis module is used to perform power flow analysis on the base state and each of the anticipated fault states according to the power grid model and the power flow equation, and generate a first network security constraint according to the analysis result.

[0176] The first network security constraint includes a base state power flow constraint and a fault state power flow constraint, specifically:

[0177]

[0178]

[0179] Among them, C is the expected fault set; represents the active power flow of branch j after the occurrence of the anticipated fault k; and Represent the base-state active power flow of branches i and j respectively; It represents the power flow transfer coefficient of the disconnected branch i to the non-disconnected branch j after the expected fault k occurs; represents the set of branches disconnected by the expected fault k; represents the set of operating branches after the expected fault k occurs, Indicates the short-time allowable current carrying capacity of branch j.

[0180] The redundancy filtering module is used to perform redundant constraint filtering on the first network security constraint to obtain a second network security constraint, so as to reduce the key constraint set that needs to be analyzed.

[0181] Among them, the redundant filtering module is specifically used to determine the branch coefficient, and according to the branch coefficient and the active power flow of the base state branch, select the branch to be monitored in the base state flow constraint to obtain the base state monitoring branch set; according to the branch coefficient and the short-time allowable current carrying capacity, select the branch to be monitored in the fault state flow constraint to obtain the fault state monitoring branch set; according to the base state monitoring branch set and the fault state monitoring branch set, obtain the monitoring branch set of the first network security constraint; judge whether the short-time overload multiple is greater than 1. If it is greater than 1, filter the monitoring branch set of the first network security constraint to obtain the second network security constraint.

[0182] The sensitivity analysis module is used to perform a sensitivity analysis on the second network security constraint, and determine the second network security constraint as the first unit power generation constraint based on the analysis result.

[0183] On the one hand, the sensitivity analysis module is specifically used to linearize the power flow equation to obtain a linearized power flow equation; perform Taylor series expansion on the second network safety constraint branch power flow and filter out higher-order terms of the second order and above to obtain the Taylor series expansion of the second network safety constraint branch power flow; obtain a sensitivity matrix based on the linearized power flow equation and the Taylor series expansion; and determine the second network safety constraint as the power generation constraint of the first unit based on the sensitivity matrix.

[0184] On the other hand, the sensitivity analysis module is further specifically used to determine whether the absolute value of the unit sensitivity of the power generation constraint of the first unit is less than a set threshold, and if so, filter the unit.

[0185] The filtering module is used to filter the first unit power generation constraints according to the unit output range to obtain the second unit power generation constraints, so as to reduce the number of power generation constraints.

[0186] Among them, the filtering module is specifically used to obtain the monitoring branch set of the first unit power generation constraint based on the first unit power generation constraint and the active power flow of the equipment group; and filter the monitoring branch set of the first unit power generation constraint according to the unit output range to obtain the second unit power generation constraint.

[0187] The model building module is used to build a power generation constraint linear programming model according to the power generation constraint of the second unit.

[0188] The power generation constraint linear programming model is specifically:

[0189]

[0190] in, and They represent the maximum available output, peak power and capacity of unit g respectively; w represents the minimum adjustment freedom of the unit.

[0191] The solving module is used to solve the power generation constraint linear programming model according to the optimization algorithm to obtain the allowable power generation range of each unit.

[0192] By implementing the embodiments of the present invention, fault-state branch flow constraints can be screened, and only constraints that are likely to work can be added to the optimization model, thereby reducing the number of fault-state constraints in the power congestion analysis problem, making the scale of existing unit power congestion analysis calculations smaller and the number of branches smaller, improving computing efficiency, and allowing the arrangement of power grid operation modes to reduce network congestion, avoid unit power congestion, and improve the reliability of safe operation of the power system.

[0193] Example 3

[0194] An embodiment of the present invention also provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program is running, it controls the device where the computer-readable storage medium is located to execute a power generation constraint processing method based on redundant constraint filtering as described in any of the above embodiments.

[0195] Example 4

[0196] An embodiment of the present invention also provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When executing the computer program, the processor implements a power generation constraint processing method based on redundant constraint filtering as described in any of the above embodiments.

[0197] Preferably, the computer program can be divided into one or more modules / units (e.g., computer program, computer program), which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units can be a series of computer program instruction segments that can perform specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0198] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or the processor can be any conventional processor. The processor is the control center of the terminal device, and uses various interfaces and lines to connect the various parts of the terminal device.

[0199] The memory mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system, an application program required for at least one function, etc., and the data storage area can store related data, etc. In addition, the memory can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, and a flash card, etc., or the memory can also be other volatile solid-state storage devices.

[0200] It should be noted that the above-mentioned terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that the above-mentioned terminal device is merely an example and does not constitute a limitation on the terminal device. It may include more or fewer components, or a combination of certain components, or different components.

[0201] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A power generation constraint processing method based on redundant constraint filtering, characterized in that: include: Acquire a power grid model and a set of anticipated faults, wherein the set of anticipated faults includes a base state and various anticipated fault states; performing power flow analysis on the base state and each of the anticipated fault states according to the power grid model and the power flow equation, and generating a first network security constraint according to the analysis result; Performing redundant constraint filtering on the first network security constraint to obtain a second network security constraint, so as to reduce a set of key constraints that need to be analyzed; performing a sensitivity analysis on the second network security constraint, and determining the second network security constraint as a power generation constraint of the first unit according to the analysis result; filtering the first unit power generation constraints according to the unit output range to obtain the second unit power generation constraints, thereby reducing the number of power generation constraints; Constructing a power generation constraint linear programming model based on the power generation constraint of the second unit; The power generation constraint linear programming model is solved according to the optimization algorithm to obtain the allowable power generation range of each unit.

2. The power generation constraint processing method based on redundant constraint filtering according to claim 1, characterized in that: The first network security constraint includes a base state power flow constraint and a fault state power flow constraint, specifically: Among them, C is the expected fault set; represents the active power flow of branch j after the predicted fault k occurs; and Represent the base-state active power flow of branches i and j respectively; It represents the power flow transfer coefficient of the disconnected branch i to the non-disconnected branch j after the expected fault k occurs; represents the set of branches disconnected by the expected fault k; represents the set of operating branches after the expected fault k occurs, Indicates the short-time allowable current carrying capacity of branch j.

3. The power generation constraint processing method based on redundant constraint filtering according to claim 2, characterized in that: The step of filtering redundant constraints on the first network security constraint to obtain the second network security constraint to reduce the set of key constraints that need to be analyzed is specifically: Determine a branch coefficient, and select a branch to be monitored within the base state power flow constraint according to the branch coefficient and the base state branch active power flow to obtain a base state monitoring branch set; Selecting a branch to be monitored in the fault state power flow constraint according to the branch coefficient and the short-time allowable current carrying capacity, to obtain a fault state monitoring branch set; Obtaining a first network security-constrained monitoring branch set according to the base state monitoring branch set and the fault state monitoring branch set; It is determined whether the short-term overload multiple is greater than 1. If it is greater than 1, the monitoring branch set of the first network security constraint is filtered to obtain a second network security constraint.

4. The power generation constraint processing method based on redundant constraint filtering according to claim 1, characterized in that: The step of performing a sensitivity analysis on the second network security constraint and determining the second network security constraint as the power generation constraint of the first unit according to the analysis result is specifically: Linearizing the tidal current equation to obtain a linearized tidal current equation; Perform Taylor series expansion on the second network safety constraint branch power flow and filter out higher-order terms above the second order to obtain the Taylor series expansion of the second network safety constraint branch power flow; Obtaining a sensitivity matrix according to the linearized power flow equation and the Taylor series expansion; According to the sensitivity matrix, the second network security constraint is determined as the first unit power generation constraint.

5. The power generation constraint processing method based on redundant constraint filtering according to claim 1, characterized in that: After the step of performing a sensitivity analysis on the second network security constraint and determining the second network security constraint as the power generation constraint of the first unit according to the analysis result, the method further includes: It is determined whether the absolute value of the unit sensitivity of the power generation constraint of the first unit is less than a set threshold. If it is less than the set threshold, the unit is filtered.

6. The power generation constraint processing method based on redundant constraint filtering according to claim 1, characterized in that: The step of filtering the first unit power generation constraints according to the unit output range to obtain the second unit power generation constraints to reduce the number of power generation constraints is specifically: Obtaining a monitoring branch set of the first unit's power generation constraint according to the first unit's power generation constraint and the active power flow of the equipment group; The monitoring branch set of the first unit power generation constraint is filtered according to the unit output range to obtain the second unit power generation constraint.

7. The power generation constraint processing method based on redundant constraint filtering according to claim 1, characterized in that: The power generation constraint linear programming model is specifically: in, and They represent the maximum available output, peak power and capacity of unit g respectively; w represents the minimum adjustment freedom of the unit.

8. A power generation constraint processing device based on redundant constraint filtering, characterized in that: include: Information acquisition module, power flow analysis module, redundancy filtering module, sensitivity analysis module, filtering module, model building module and model solving module; The information acquisition module is used to obtain a power grid model and a predicted fault set, wherein the predicted fault set includes a base state and each predicted fault state; The power flow analysis module is used to perform power flow analysis on the base state and each of the anticipated fault states according to the power grid model and the power flow equation, and generate a first network security constraint according to the analysis result; The redundancy filtering module is used to perform redundant constraint filtering on the first network security constraint to obtain a second network security constraint, so as to reduce the key constraint set that needs to be analyzed; The sensitivity analysis module is configured to perform a sensitivity analysis on the second network security constraint, and determine the second network security constraint as the power generation constraint of the first unit according to the analysis result; The filtering module is used to filter the first unit power generation constraints according to the unit output range to obtain the second unit power generation constraints, so as to reduce the number of power generation constraints; The model building module is used to build a power generation constraint linear programming model according to the power generation constraint of the second unit; The solving module is used to solve the power generation constraint linear programming model according to the optimization algorithm to obtain the allowable power generation range of each unit.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored computer program; wherein, when the computer program is run, it controls the device where the computer-readable storage medium is located to execute a power generation constraint processing method based on redundant constraint filtering as described in any one of claims 1-7.

10. A terminal device, characterized in that: The invention comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements a power generation constraint processing method based on redundant constraint filtering according to any one of claims 1 to 7 when executing the computer program.

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