Voltage stability collaborative planning algorithm considering net rack reinforcement and reactive power optimization

Abstract

The invention provides a voltage stability collaborative planning algorithm considering net rack reinforcement and reactive power optimization. The voltage stability collaborative planning algorithm comprises the following steps: S1, solving a weak line; s2, solving node weakness; s3, establishing a Jacobian matrix considering net rack reinforcement; s4, establishing a Jacobian matrix considering reactive power optimization; s5, establishing a Jacobian matrix comprehensively considering net rack reinforcement and reactive power optimization; s6, considering a grid reinforcement and reactive power optimization voltage stability collaborative planning target and constraint conditions; according to the power system voltage stability collaborative planning model comprehensively considering grid reinforcement and reactive power optimization, the voltage stability control of the new energy base of which the long-distance single channel is merged into the regional grid is more comprehensive and effective, and the voltage stability of the novel power system accessed into the new energy base is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of voltage stability of power systems, and in particular to a voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization. Background Art

[0002] With the massive access to new energy sources, the voltage stability of the power system has ushered in new challenges. At present, the research on improving voltage stability often uses the VQ curve to determine the appropriate reactive power optimization installation point for reactive power optimization to improve voltage stability. However, the new energy base is usually far away from the load center and is generally connected to the regional grid in a long-distance single-channel manner. The power fluctuation of large-scale new energy bases leads to prominent voltage stability problems in the power system. Summary of the invention

[0003] In order to overcome the above-mentioned deficiencies of the prior art, the present invention discloses a voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization.

[0004] The technical solution provided by the present invention is: a voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization, comprising the following steps:

[0005] S1: Finding weak lines;

[0006] S2: Calculation of node weakness;

[0007] S3: Establishment of Jacobian matrix considering grid reinforcement;

[0008] S4: Establishment of Jacobian matrix considering reactive power optimization;

[0009] S5: Establishment of Jacobian matrix considering grid reinforcement and reactive power optimization;

[0010] S6: Consider the coordinated planning objectives and constraints of grid reinforcement and reactive power optimization for voltage stability.

[0011] Preferably, the step S1 specifically includes:

[0012] The grid condition of the existing system is analyzed using the Nk fault analysis method, and the square of the maximum voltage deviation is used as an indicator to select the weak line at k as the line to be strengthened;

[0013] The square of the maximum voltage deviation is defined as:

[0014]

[0015] Where A is the square of the maximum voltage deviation, Δv max It is the maximum deviation per unit value of the node voltage at both ends of the line after the fault.

[0016] Further preferably, the step S2 specifically includes: defining the node weakness as:

[0017]

[0018] Where D i is the degree of node i, that is, the number of edges directly connected to node i, D k is the degree of node k, n is the number of system nodes, m is the degree weight, Q i Reactive power of node i, v i is the voltage at node i, E i is the weakness of node i, select the cutoff parameter τ, and set E i Sort by size, when satisfied When , the first p points are selected as nodes to be strengthened, and D'i is the proportion of the i-node degree in the entire system.

[0019] Further preferably, the step S3 specifically includes: establishing equations (3) and (4) for the relationship between the reactive power disturbance and the node voltage deviation of the power system, selecting point k as the reinforcement line through S1, and equation (5) for the relationship between the reactive power disturbance and the node voltage deviation taking into account the grid reinforcement;

[0020] ΔQ=-BΔU (3)

[0021]

[0022] Where ΔQ is the reactive power disturbance, -B is the Jacobian matrix that only considers the relationship between reactive power disturbance and node voltage deviation, and B e,f is the equivalent susceptance of line (e, f), ΔU is the node voltage deviation;

[0023]

[0024]

[0025] Where -B1 is the Jacobian matrix taking into account the reinforcement of the grid, ΔB1 ​​is the coefficient matrix of the reinforcement of the grid, M is the column vector of n×1, ΔB ij To take into account the change in line susceptance due to grid reinforcement, ΔB ij This variable is the equivalent susceptance between node i and node j after the grid is strengthened.

[0026] Further preferably, the step S4 specifically includes: performing reactive power optimization according to the p nodes obtained in step S2, and formula (7) is an expression for the relationship between the reactive power disturbance and the node voltage deviation taking into account the reactive power optimization:

[0027]

[0028]

[0029]

[0030]

[0031] Formula (7) is a rearrangement of Formula (4), where the relationship between the reactive power disturbance and the voltage deviation of the p nodes that need to be strengthened obtained in step S2 is arranged at the end, the first np nodes are nodes that do not need to be strengthened, and n-p+1→n are the p nodes to be strengthened; The capacity for reactive power optimization of the selected p nodes in S2, is the reactive power disturbance after reactive power optimization, B2 is the Jacobian matrix taking reactive power optimization into account, ΔB2 is the coefficient matrix of reactive power optimization, and Ci is the capacitance value of the ith node in parallel.

[0032] Further preferably, the step S5 specifically includes: comprehensively considering the correlation between reactive power and voltage deviation of grid reinforcement and reactive power optimization is:

[0033]

[0034]

[0035] Further preferably, the step S6 specifically includes: comprehensively considering the grid reinforcement and reactive power optimization to obtain the characteristic root of the Jacobian matrix related to the stability criterion, that is, the closer the absolute value of the characteristic root is to 0, the closer the operating state is to the limit, and its minimum modulus characteristic root can be used as a system stability margin measure, and the objective function is set as:

[0036]

[0037] Where t1 is the weight of considering the minimum modulus eigenvalue, t2 is the weight of considering the geometric mean of all eigenvalues ​​of the Jacobian matrix, |λ min | is the minimum modulus characteristic root of the Jacobian matrix obtained by comprehensive consideration of grid reinforcement and reactive power optimization, The geometric mean of all characteristic root modes of the Jacobian matrix obtained by comprehensive consideration of grid reinforcement and reactive power optimization.

[0038] Further preferably, in step S6, the constraint conditions are equality constraints and inequality constraints;

[0039] The power flow constraints are:

[0040]

[0041] P i Inject active power into node i; Qi is the injected reactive power of node i, the ΔQ mentioned above i Q is the disturbance i The change in P gi , Q gi is the active power and reactive power of the generator node; P Di , Q Di is the active power and reactive power of the load node; Q c Reactive power provided to the reactive power optimization device. i , U j is the voltage between node i and node j; G ij , B′ ij is the conductance and susceptance of branch (i, j), B′ ij is the element in row i and column j in the Jacobian matrix B3 above; θ i ,θ j is the phase angle between node i and node j;

[0042] Inequality constraints:

[0043] 1) The active and reactive power of the generator must meet the following requirements:

[0044]

[0045] It is the lower and upper limits of the active power of the generator. is the lower and upper limits of the generator reactive power;

[0046] 2) The node voltage must meet the following requirements:

[0047]

[0048] are the lower and upper limits of the node voltage;

[0049] 3) The grid reinforcement needs to meet the following requirements:

[0050]

[0051] Strengthen the lower and upper limits of electrical susceptance for the grid;

[0052] 4) The capacity to be compensated for reactive power optimization must meet the following requirements:

[0053]

[0054] It is the lower and upper limits of the compensation capacity of the reactive power compensation device.

[0055] The beneficial effects of the present invention are:

[0056] 1) The present invention is based on the Nk fault analysis method and uses the maximum square value of the node voltage deviation at both ends of the line as an indicator to determine the weak line, and determines the weak node of the system voltage stability based on the node weakness, and quickly and accurately obtains the line to be strengthened and the node to be reactively optimized. Different from the previous improvement of voltage stability by only reactive power optimization, the present invention comprehensively considers the power system voltage stability collaborative planning model of grid reinforcement and reactive power optimization, and the voltage stability control of the new energy base with a long-distance single channel incorporated into the regional grid is more comprehensive and effective;

[0057] 2) The present invention establishes a Jacobian matrix that comprehensively considers grid reinforcement and reactive power optimization, determines the weighted sum of the minimum modulus eigenvalue of the Jacobian matrix and the geometric mean of all eigenvalue moduli as the objective function, thereby determining the optimal grid reinforcement amount and reactive power optimization capacity, thereby improving the voltage stability of the new power system connected to the new energy base. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A schematic diagram of the structure of a voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization provided by the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0060] like Figure 1 As shown, the present invention comprises the following steps:

[0061] S1: Finding weak lines;

[0062] The grid condition of the existing system is analyzed using the Nk fault analysis method, and the square of the maximum voltage deviation is used as an indicator to select the weak line at k as the line to be strengthened;

[0063] The Nk fault analysis method is used to analyze the grid conditions of the existing system. The square of the maximum voltage deviation is used as an indicator, and the weak line at k is selected as the line to be strengthened. The square of the maximum voltage deviation can help evaluate the weakness of the line in the system. The larger the square of the maximum voltage deviation, the weaker the line is and needs to be strengthened. The square of the maximum voltage deviation is defined as:

[0064]

[0065] Where A is the square of the maximum voltage deviation, Δv max It is the maximum deviation per unit value of the node voltage at both ends of the line after the fault;

[0066] S2: Calculation of node weakness;

[0067] Node weakness is a comprehensive performance indicator of the importance of a node in the system and the impact of reactive power on the voltage of the node. That is, the higher the node weakness, the greater the impact of the node on the stability of the power system. This paper defines node weakness as:

[0068]

[0069] Where D i is the degree of node i, that is, the number of edges directly connected to node i, D k is the degree of node k, n is the number of system nodes, m is the degree weight, Q i Reactive power of node i, v i is the voltage at node i, C i is the weakness of node i, select the cutoff parameter τ, and set C i Sort by size, when satisfied When , the first p points are selected as nodes to be strengthened, and D'i is the proportion of the degree of the i node in the entire system;

[0070] S3: Establishment of Jacobian matrix considering grid reinforcement;

[0071] Formula (3) and (4) are established to represent the relationship between the reactive power disturbance and the node voltage deviation of the power system. Through S1, point k is selected as the reinforcement line. Formula (5) represents the relationship between the reactive power disturbance and the node voltage deviation taking into account the grid reinforcement.

[0072] ΔQ=-BΔU (3)

[0073]

[0074] Where ΔQ is the reactive power disturbance, -B is the Jacobian matrix that only considers the relationship between reactive power disturbance and node voltage deviation, and B e,f is the equivalent susceptance of line (e, f), ΔU is the node voltage deviation;

[0075]

[0076]

[0077] Where -B1 is the Jacobian matrix taking into account the reinforcement of the grid, ΔB1 ​​is the coefficient matrix of the reinforcement of the grid, M is the column vector of n×1, ΔB ij To take into account the change in line susceptance due to grid reinforcement, ΔB ij This variable is the equivalent susceptance between nodes i and j after the grid is strengthened;

[0078] S4: Establishment of Jacobian matrix considering reactive power optimization;

[0079] Reactive power optimization is performed on the p nodes obtained in step S2. Formula (7) is the relationship between the reactive power disturbance and the node voltage deviation taking into account reactive power optimization:

[0080]

[0081]

[0082]

[0083]

[0084] Formula (7) is a rearrangement of Formula (4), where the relationship between the reactive power disturbance and the voltage deviation of the p nodes that need to be strengthened obtained in step S2 is arranged at the end, the first np nodes are nodes that do not need to be strengthened, and n-p+1→n are the p nodes to be strengthened; The capacity for reactive power optimization of the selected p nodes in S2, is the reactive power disturbance after reactive power optimization, B2 is the Jacobian matrix taking reactive power optimization into account, ΔB2 is the coefficient matrix of reactive power optimization, Ci is the capacitance value of the ith node in parallel; S5: the establishment of the Jacobian matrix taking into account grid reinforcement and reactive power optimization;

[0085] The correlation between reactive power and voltage deviation considering grid reinforcement and reactive power optimization is as follows:

[0086]

[0087]

[0088] S6: Considering the coordinated planning objectives and constraints of grid reinforcement and reactive power optimization and voltage stability;

[0089] Taking into account the grid reinforcement and reactive power optimization, the characteristic root of the Jacobian matrix is ​​related to the stability criterion. That is, the closer the absolute value of the characteristic root is to 0, the closer the operating state is to the limit. Its minimum modulus characteristic root can be used as a measure of the system stability margin. The objective function is set as:

[0090]

[0091] Where t1 is the weight of considering the minimum modulus eigenvalue, t2 is the weight of considering the geometric mean of all eigenvalues ​​of the Jacobian matrix, |λ min | is the minimum modulus characteristic root of the Jacobian matrix obtained by comprehensive consideration of grid reinforcement and reactive power optimization, The geometric mean of all characteristic root modes of the Jacobian matrix obtained by comprehensive consideration of grid reinforcement and reactive power optimization;

[0092] The constraints are equality constraints and inequality constraints;

[0093] Equality constraints:

[0094] The power flow constraints are:

[0095]

[0096] P i Inject active power into node i; Q i is the injected reactive power of node i, the ΔQ mentioned above i Q is the disturbance i The change in P gi , Q gi is the active power and reactive power of the generator node; P Di , Q Di is the active power and reactive power of the load node; Q c Reactive power provided to the reactive power optimization device, U i , U j is the voltage between node i and node j; G ij , B′ ij is the conductance and susceptance of branch)i,j), B′ ij is the element in row i and column j in the Jacobian matrix B3 above; θ i ,θ j is the phase angle between node i and node j;

[0097] Inequality constraints:

[0098] 1) The active and reactive power of the generator must meet the following requirements:

[0099]

[0100] It is the lower and upper limits of the active power of the generator. is the lower and upper limits of the generator reactive power;

[0101] 2) The node voltage must meet the following requirements:

[0102]

[0103] are the lower and upper limits of the node voltage;

[0104] 3) The grid reinforcement needs to meet the following requirements:

[0105]

[0106] Strengthen the lower and upper limits of electrical susceptance for the grid;

[0107] 4) The capacity to be compensated for reactive power optimization must meet the following requirements:

[0108]

[0109] It is the lower and upper limits of the compensation capacity of the reactive power compensation device.

[0110] It should be understood that, inspired by the technical concept of the present invention, those skilled in the art can make various improvements and changes based on the above description without departing from the content of the present invention, which still fall within the protection scope of the present invention.

[0111] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the claims.

[0112] It should be understood that the present invention is not limited to the precise construction shown in the above description and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization, characterized in that: The steps include: S1: Finding weak lines; S2: Calculation of node weakness; S3: Establishment of Jacobian matrix considering grid reinforcement; S4: Establishment of Jacobian matrix considering reactive power optimization; S5: Establishment of Jacobian matrix considering grid reinforcement and reactive power optimization; S6: Consider the coordinated planning objectives and constraints of grid reinforcement and reactive power optimization for voltage stability.

2. A voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization according to claim 1, characterized in that: The step S1 specifically includes: The Nk fault analysis method is used to analyze the grid conditions of the existing system, and the square of the maximum voltage deviation is used as an indicator to select the weak line at k as the line to be strengthened; The square of the maximum voltage deviation is defined as: Where A is the square of the maximum voltage deviation, Δv max It is the maximum deviation per unit value of the node voltage at both ends of the line after the fault.

3. The voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization according to claim 1 is characterized in that: The step S2 specifically includes: The definition of node weakness is: Where D i is the degree of node i, that is, the number of edges directly connected to node i, D k is the degree of node k, n is the number of system nodes, m is the degree weight, Q i Reactive power of node i, v i is the voltage at node i, E i is the weakness of node i, select the cutoff parameter τ, and set E i Sort by size, when satisfied When , the first p points are selected as nodes to be strengthened, and D'i is the proportion of the degree of the i node in the entire system.

4. The voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization according to claim 1, characterized in that: The step S3 specifically includes: Formula (3) and (4) are established to represent the relationship between the reactive power disturbance and the node voltage deviation of the power system. Through S1, point k is selected as the reinforcement line. Formula (5) represents the relationship between the reactive power disturbance and the node voltage deviation taking into account the grid reinforcement. ΔQ=-BΔU (3) Where ΔQ is the reactive power disturbance, -B is the Jacobian matrix that only considers the relationship between reactive power disturbance and node voltage deviation, and B e,f is the equivalent susceptance of line (e, f), ΔU is the node voltage deviation; Where -B1 is the Jacobian matrix taking into account the reinforcement of the grid, ΔB1 ​​is the coefficient matrix of the reinforcement of the grid, M is the column vector of n×1, ΔB ij To take into account the change in line susceptance due to grid reinforcement, ΔB ij This variable is the equivalent susceptance between node i and node j after the grid is strengthened.

5. The voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization according to claim 1 is characterized in that: The step S4 specifically includes: Reactive power optimization is performed on the p nodes obtained in step S2. Formula (7) is the relationship between the reactive power disturbance and the node voltage deviation taking into account reactive power optimization: Formula (7) is a rearrangement of Formula (4), where the relationship between the reactive power disturbance and the voltage deviation of the p nodes that need to be strengthened obtained in step S2 is arranged at the end, the first np nodes are nodes that do not need to be strengthened, and n-p+1→n are the p nodes to be strengthened; The capacity of reactive power optimization for the selected p nodes in S2, is the reactive power disturbance after reactive power optimization, B2 is the Jacobian matrix taking reactive power optimization into account, ΔB2 is the coefficient matrix of reactive power optimization, and Ci is the capacitance value in parallel with the i-th node.

6. The voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization according to claim 1 is characterized in that: The step S5 specifically includes: The correlation between reactive power and voltage deviation considering grid reinforcement and reactive power optimization is:

7. The voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization according to claim 1 is characterized in that: The step S6 specifically includes: Taking into account the grid reinforcement and reactive power optimization, the characteristic root of the Jacobian matrix is ​​related to the stability criterion. That is, the closer the absolute value of the characteristic root is to 0, the closer the operating state is to the limit. Its minimum modulus characteristic root can be used as a measure of the system stability margin. The objective function is set as: Where t1 is the weight of considering the minimum modulus eigenvalue, t2 is the weight of considering the geometric mean of all eigenvalues ​​of the Jacobian matrix, |λ min | is the minimum modulus characteristic root of the Jacobian matrix obtained by comprehensive consideration of grid reinforcement and reactive power optimization, The geometric mean of all characteristic root modes of the Jacobian matrix obtained by comprehensive consideration of grid reinforcement and reactive power optimization.

8. A voltage stability collaborative planning algorithm taking into account grid reinforcement and reactive power optimization according to claim 7, characterized in that: In step S6, the constraint conditions are equality constraints and inequality constraints; Equality constraints: The power flow constraints are: P i Inject active power into node i; Q i is the injected reactive power of node i, the αQ mentioned above i Q is the disturbance i The change in P gi , Q gi is the active power and reactive power of the generator node; P Di , Q Di is the active power and reactive power of the load node; Q c Reactive power provided to the reactive power optimization device. i , U j is the voltage between node i and node j; G ij , B′ ij is the conductance and susceptance of branch (i, j), B′ ij is the element in row i and column j in the Jacobian matrix B3 above; θ i ,θ j is the phase angle between node i and node j; Inequality constraints: 1) The active and reactive power of the generator must meet the following requirements: It is the lower and upper limits of the generator active power. is the lower and upper limits of the generator reactive power; 2) The node voltage must meet the following requirements: are the lower and upper limits of the node voltage; 3) The grid reinforcement electrical susceptance must meet the following requirements: Strengthen the lower and upper limits of electrical susceptance for the grid; 4) The capacity to be compensated for reactive power optimization must meet the following requirements: It is the lower and upper limits of the compensation capacity of the reactive power compensation device.

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