Reactive power reserve demand calculation method for high proportion of wind power ac-dc power system

Abstract

The application discloses a reactive power reserve demand calculation method for a high-proportion wind power AC / DC power system and relates to the technical field of reactive power optimization of a new type of power system with wind power AC / DC hybrid connection. The application accurately depicts the reactive power voltage level of the overall system through a voltage-reactive power comprehensive evaluation index matrix of the wind power AC / DC system, realizes adaptive clustering partitioning and dominant point selection by using comprehensive similarity calculation, greatly improves the calculation speed of the reactive power reserve demand of the power grid, improves the defects of the low model precision and slow solution speed of the current power grid reactive power evaluation model, the overall parameter setting architecture of the application is simple, fast and easy to realize, a reactive power reserve demand distribution optimization model is established, the centralized iterative evaluation mode based on all node information is abandoned, and the application provides a reference for the online evaluation technology of the reactive power reserve or reserve demand of the power system.

Description

Technical Field

[0001] This invention relates to the field of reactive power optimization technology for novel power systems with AC / DC hybrid power generation including wind power, specifically a method for calculating reactive power reserve requirements of AC / DC power systems with a high proportion of wind power. Background Technology

[0002] Under the "dual-carbon" strategy, with the increasing integration of renewable energy sources and the commissioning of multiple DC transmission lines, sufficient reactive power reserves are crucial for maintaining transient voltage stability and improving the system's anti-interference capabilities. During steady-state operation, if the system lacks sufficient reactive power reserves, it will operate in a low-safety-margin, high-risk state. Once a fault or disturbance occurs, the reactive power compensation equipment or reactive power sources may be unable to provide sufficient rapid reactive power / voltage support, potentially leading to continuous commutation failures in the converters, which in turn triggers DC system blocking. This results in a significant voltage surge / dip across the entire system, further generating a chain reaction that could induce widespread cascading failures and grid collapse. Therefore, rapidly and accurately calculating reactive power reserve requirements to reserve sufficient reserves during steady-state operation, cutting off the propagation path of N-1 faults / disturbances, and preventing large-scale cascading failures are of great significance for ensuring the safe operation of AC / DC grids with a high proportion of renewable energy integration.

[0003] Current reactive power reserve assessment and optimization methods mostly target traditional reactive power sources such as conventional generators, neglecting the characteristics of renewable energy sources. With a high proportion of renewable energy integrated into AC / DC hybrid power systems, grid coupling is relatively tight, and the impact of faults is widespread. Reactive power reserve assessment requires calculating the dynamic processes of the grid under hundreds to thousands of anticipated faults. Existing reactive power reserve assessment / optimization methods struggle to effectively decompose this tightly coupled, large-scale optimization problem and suffer from slow system calculation speeds. Some studies propose time-domain simulation-based reactive power reserve assessment calculations, but for large-scale wind power AC / DC grids, the excessively long simulation calculation time is a significant bottleneck limiting its online real-time application. Offline analysis results have limited reference value, and traditional centralized assessment methods iteratively update information from all nodes, resulting in massive computational loads, low efficiency, and difficulty in achieving online assessment. How to efficiently and accurately assess reactive power reserve requirements while fully considering the system's reactive voltage state and the constraints of wind power AC / DC operation characteristics has become a pressing research area for those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide a method for calculating reactive power reserve requirements in high-proportion wind power AC / DC power systems. This method uses a voltage-reactive power comprehensive evaluation index matrix to characterize the system's voltage and reactive power requirements, and employs adaptive clustering and dominant node selection to achieve optimal reactive power reserve requirement assessment and calculation under the conditions of satisfying system voltage security and various reactive power source operating constraints. This significantly improves the calculation speed of grid reactive power reserve requirements, enhances the voltage security level of wind power AC / DC systems, and facilitates the online application of reactive power assessment technology, thereby addressing the shortcomings of current grid reactive power assessment models, such as low accuracy and slow solution speed.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for calculating reactive power reserve requirements in AC / DC power systems with a high proportion of wind power, comprising at least the following steps:

[0006] S1: Evaluate the parameters of the wind power AC / DC power system of the target, obtain the network architecture topology within the system, determine the access locations of different types of reactive power sources within the system, and use the existing acquisition system or data system to determine the information of the DC converter station of the wind farm. The information includes at least the operating control parameters, the voltage of each node in the system, the reactive power output value, and the power flow of the grid.

[0007] S2: Screen typical scenarios under different operating modes, construct a calculation formula for the voltage-reactive power comprehensive evaluation index matrix of wind power AC / DC system, combine the acquired system parameters and current status information, determine the voltage-reactive power comprehensive evaluation index results of wind power AC / DC system under various typical scenarios through power flow calculation, and comprehensively characterize the system voltage and reactive power demand. The classic scenarios include at least normal, AC line N-1, and DC blocking outage.

[0008] S3: Construct a formula for calculating the voltage-reactive power comprehensive similarity distance of the wind power AC / DC system. By calculating the comprehensive distance matrix of the wind power AC / DC system, the system is clustered and partitioned to determine the optimal number of clusters M. The optimal partition Sbest set is output. Based on the optimal partition, the node corresponding to the maximum value of the voltage-reactive power comprehensive evaluation index in each region is taken as the dominant node of that region.

[0009] S4: Based on the operating characteristics of reactive power sources in each region, establish an optimization model for reactive power reserve demand allocation to achieve optimal reactive power reserve under the conditions of satisfying system voltage safety and various reactive power source operating constraints. Solve the optimization model based on the genetic intelligent algorithm, output the reactive power reserve calculation results for each region, and realize the optimal reactive power reserve evaluation calculation under the conditions of satisfying system voltage safety and various reactive power source operating constraints, and end the work.

[0010] Furthermore, in the wind power AC / DC power system of S1, the wind power, the reactive power compensation device near the DC power source, and the conventional generator set serve as reactive power reserve sources, specifically including the following reactive power reserves:

[0011] (1)

[0012] In equation (1), S is the set of all nodes included in the wind power AC / DC power system; This represents the total reactive power reserve requirement of the system. This represents the reactive power reserve of the doubly fed wind farm where node i is located in the system. This represents the reactive power reserve of the direct-drive wind farm where node j is located in the system. This represents the reactive power reserve of the reactive power compensation device where node f is located in the system. This represents the reactive power reserve of the conventional generator set where node g is located in the system.

[0013] Furthermore, the typical scenario set in S2 is given by the following formula:

[0014] (2)

[0015] In equation (2), A collection of typical operating scenarios; Let l be the l-th typical scenario in the set of operating scenarios; A is the number of typical scenarios, which can be given in advance by the numerical sampling simulation of the power system.

[0016] The formula for calculating the voltage-reactive power comprehensive evaluation index matrix of wind power AC / DC systems is further constructed as follows:

[0017] (3)

[0018]

[0019]

[0020] (6)

[0021] (7)

[0022] In equations (3) to (5), VQSI is the voltage-reactive power comprehensive evaluation index matrix of the wind power AC / DC system, which is calculated by weighted summation of the system voltage comprehensive index matrix VSI and the system reactive power comprehensive index matrix QSI; α and β are the weight coefficients of the voltage comprehensive index and the reactive power comprehensive index, respectively, which are generally set in advance according to the system operating parameters; VSIil is an element in the system voltage comprehensive index matrix; i is any node in the system node set S; l is the typical scenario set. In any scenario; VSI is an N×A matrix that reflects the voltage stability of N nodes in an AC / DC power system under A typical scenarios; similarly, QSIil is an element in the system reactive power comprehensive index matrix, and QSI is also an N×A matrix that reflects the reactive power reserve effect of N nodes in an AC / DC power system under A typical scenarios.

[0023] Equations (6) and (7) represent the calculation formulas for each element VSI of the system voltage comprehensive index matrix and each element QSI of the system reactive power comprehensive index matrix; U0, Umin, Uend, Tset and Uset represent the initial state value of the node voltage, the lowest value during a fault or disturbance, the steady state value after the fault or disturbance is recovered, the duration of the fault or disturbance at the node, and the node voltage safety threshold, respectively; U0, Umin, Uend and Tset are obtained by the acquisition and monitoring system, while Uset is determined in advance according to the voltage level of the node, and is generally set to 80% of the rated voltage; ε is a correction factor constant, which is generally taken as 0.1; This represents the reactive power regulation between system node i and its physically connected node j. The reactive power-voltage sensitivity parameters of nodes i and j can be determined through power flow calculations. Qij is the reactive power transmission value between nodes i and j, which is obtained by the acquisition and monitoring system.

[0024] The matrix form described above comprehensively depicts the voltage and reactive power demand of the wind power AC / DC system, which is more in line with the actual operation. The larger the value of the matrix element, the more stable the system voltage, the higher the voltage-reactive power sensitivity of the corresponding node, and the better the effect of implementing reactive power source regulation of voltage.

[0025] Furthermore, the formula for calculating the voltage-reactive power integrated similarity distance of the wind power AC / DC system in S3 is as follows:

[0026] (8)

[0027] In equation (8), D(i,j) represents the similarity distance between any nodes i and j in the system with respect to the voltage-reactive power comprehensive evaluation index. The smaller the value, the more similar the voltage-reactive power comprehensive evaluation index value of node i is to that of node j.

[0028] Calculate the voltage-reactive power combined similarity distance between any two nodes in the system, and construct the combined similarity distance matrix of the system:

[0029]

[0030] In equation (9), DVQSI represents the comprehensive similarity distance matrix of the wind power AC / DC system, which is an N×N matrix. By clustering and partitioning the matrix based on the value of its elements, the optimal number of clusters M is determined, thereby reducing the N×N matrix to an M×M matrix. At the same time, the optimal partition Sbest set is output.

[0031] (10)

[0032] In Equation (10), Sbest is the optimal partition set of the wind power AC / DC system. The node set S of the wind power AC / DC system is divided into M regions after being clustered by voltage-reactive power comprehensive similarity distance.

[0033] Furthermore, the node corresponding to the maximum value of the voltage-reactive power comprehensive evaluation index in each region is selected as the dominant node in that region:

[0034] (11)

[0035] In Equation (11), Hk represents the voltage-reactive power comprehensive evaluation index value of the dominant node in the kth region within the optimal partition set of the wind power AC / DC system, and || ||∞ represents the infinite norm of the voltage-reactive power comprehensive evaluation index matrix VQSI(i) of node i.

[0036] Furthermore, in S4, based on the operating characteristics of reactive power sources in each region, an optimization model for reactive power reserve demand allocation is established as follows:

[0037] (12)

[0038] In equation (12), G and This represents the overall reactive power reserve requirement for high-proportion wind power AC / DC systems. , , and Let G represent the reactive power reserve values ​​of the doubly-fed wind farm, the direct-drive wind farm, the reactive power compensation device, and the conventional generator set in the k-th region of the optimal partition set of the wind power AC / DC system, respectively; and let G be the objective function for optimizing the allocation of reactive power reserve requirements.

[0039] The optimization model includes equality constraints, namely the power flow equations of the wind power AC / DC system, where and S represents the optimal partition set S of the wind power AC / DC system. k The active power and reactive power values ​​of internal node i; and Optimal partition set S k The active and reactive power values ​​of DC transmission at internal node i; , S represents the optimal set of partitions. k Voltage amplitudes at internal nodes i and j; N k For the optimal set of partitions S k The number of nodes; For the optimal set of partitions S k The phase difference between nodes i and j within the same node; and For the optimal set of partitions S k The admittance matrices of nodes i and j within the matrix;

[0040] The optimization model includes inequality constraints, namely, upper and lower limit constraints on the reactive power output of the wind power AC / DC system. , , , and These are the equivalent parameters of the stator reactance, excitation parameters, maximum allowable operating current of the rotor of the doubly-fed wind farm, terminal voltage of the doubly-fed wind farm, and output active power of the doubly-fed wind farm in the kth region of the optimal zoning set of the AC / DC wind power system, respectively. , and These are the maximum allowable reactive power output, reactive power output, and apparent power output of the direct-drive wind farm units in the kth region of the optimal partition set, respectively. and The maximum allowable output value and current reactive power output value of the reactive power compensation device in the kth region within the optimal partition set; and The maximum permissible reactive power output and current reactive power output of the conventional generator set in the kth region of the optimal partition set; , , and The parameters are related to the wind farm turbine model and the internal wiring topology of the wind farm. and The parameters are related to the corresponding conventional generator set model and can all be determined in advance; , , , , and Data is acquired in real time by the data acquisition and monitoring system.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] 1. This invention achieves accurate characterization of the reactive voltage level of the overall system through the voltage-reactive power comprehensive evaluation index matrix of the wind power AC / DC system, and realizes adaptive clustering partitioning and dominant point selection of the system by using comprehensive similarity calculation, which greatly improves the calculation speed of the power grid reactive power reserve demand and overcomes the shortcomings of the current power grid reactive power evaluation model with low accuracy and slow solution speed.

[0043] 2. The overall parameter setting architecture of this invention is simple, fast and easy to implement. It establishes an optimization model for reactive power reserve demand allocation, abandons the centralized iterative evaluation mode based on all node information, and provides a reference for online evaluation technology of reactive power reserve or reserve demand in power systems.

[0044] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart of the present invention;

[0047] Figure 2 This is a network topology diagram of the test system of the present invention and a schematic diagram of the clustering and partitioning situation under the implementation of the method of the present invention;

[0048] Figure 3 This is a schematic diagram showing the calculation results of reactive power reserve requirements of the test system of the present invention under different operating scenarios;

[0049] Figure 4 This is a schematic diagram illustrating the calculation efficiency of reactive power reserve requirements in the test system of this invention.

[0050] Figure 5 This is a schematic diagram showing the steady-state voltage distribution of each node in the test system of this invention after implementing reactive power reserve and without implementing reactive power reserve. Detailed Implementation

[0051] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0052] Example 1:

[0053] This embodiment proposes a method for calculating reactive power reserve requirements in AC / DC power systems with a high proportion of wind power. Please refer to [link / reference]. Figure 1 It includes at least the following steps:

[0054] S1: Evaluate the parameters of the wind power AC / DC power system of the target, obtain the network architecture topology within the system, determine the access locations of different types of reactive power sources within the system, and use the existing acquisition system or data system to determine the information of the DC converter station of the wind farm. The information includes at least the operating control parameters, the voltage of each node in the system, the reactive power output value, and the power flow of the grid.

[0055] S2: Screen typical scenarios under different operating modes, construct a calculation formula for the voltage-reactive power comprehensive evaluation index matrix of wind power AC / DC system, combine the acquired system parameters and current status information, determine the voltage-reactive power comprehensive evaluation index results of wind power AC / DC system under various typical scenarios through power flow calculation, and comprehensively characterize the system voltage and reactive power demand. The classic scenarios include at least normal, AC line N-1, and DC blocking outage.

[0056] S3: Construct a formula for calculating the voltage-reactive power comprehensive similarity distance of the wind power AC / DC system. By calculating the comprehensive distance matrix of the wind power AC / DC system, the system is clustered and partitioned to determine the optimal number of clusters M. The optimal partition Sbest set is output. Based on the optimal partition, the node corresponding to the maximum value of the voltage-reactive power comprehensive evaluation index in each region is taken as the dominant node of that region.

[0057] S4: Based on the operating characteristics of reactive power sources in each region, establish an optimization model for reactive power reserve demand allocation to achieve optimal reactive power reserve under the conditions of satisfying system voltage safety and various reactive power source operating constraints. Solve the optimization model based on the genetic intelligent algorithm, output the reactive power reserve calculation results for each region, and realize the optimal reactive power reserve evaluation calculation under the conditions of satisfying system voltage safety and various reactive power source operating constraints, and end the work.

[0058] In the wind power AC / DC power system of S1, wind power, nearby DC reactive power compensation devices, and conventional generator sets serve as reactive power reserve sources, specifically including the following reactive power reserves:

[0059] (1)

[0060] In equation (1), S is the set of all nodes included in the wind power AC / DC power system; This represents the total reactive power reserve requirement of the system. This represents the reactive power reserve of the doubly fed wind farm where node i is located in the system. This represents the reactive power reserve of the direct-drive wind farm where node j is located in the system. This represents the reactive power reserve of the reactive power compensation device where node f is located in the system. This represents the reactive power reserve of the conventional generator set where node g is located in the system.

[0061] The typical scenario set in S2 is shown in the following formula:

[0062] (2)

[0063] In equation (2), A collection of typical operating scenarios; Let l be the l-th typical scenario in the set of operating scenarios; A is the number of typical scenarios, which can be given in advance by the numerical sampling simulation of the power system.

[0064] The formula for calculating the voltage-reactive power comprehensive evaluation index matrix of wind power AC / DC systems is further constructed as follows:

[0065] (3)

[0066]

[0067]

[0068] (6)

[0069] (7)

[0070] In equations (3) to (5), VQSI is the voltage-reactive power comprehensive evaluation index matrix of the wind power AC / DC system, which is calculated by weighted summation of the system voltage comprehensive index matrix VSI and the system reactive power comprehensive index matrix QSI; α and β are the weight coefficients of the voltage comprehensive index and the reactive power comprehensive index, respectively, which are generally set in advance according to the system operating parameters; VSIil is an element in the system voltage comprehensive index matrix; i is any node in the system node set S; l is the typical scenario set. In any scenario; VSI is an N×A matrix that reflects the voltage stability of N nodes in an AC / DC power system under A typical scenarios; similarly, QSIil is an element in the system reactive power comprehensive index matrix, and QSI is also an N×A matrix that reflects the reactive power reserve effect of N nodes in an AC / DC power system under A typical scenarios.

[0071] Equations (6) and (7) represent the calculation formulas for each element VSI of the system voltage comprehensive index matrix and each element QSI of the system reactive power comprehensive index matrix; U0, Umin, Uend, Tset and Uset represent the initial state value of the node voltage, the lowest value during a fault or disturbance, the steady state value after the fault or disturbance is recovered, the duration of the fault or disturbance at the node, and the node voltage safety threshold, respectively; U0, Umin, Uend and Tset are obtained by the acquisition and monitoring system, while Uset is determined in advance according to the voltage level of the node, and is generally set to 80% of the rated voltage; ε is a correction factor constant, which is generally taken as 0.1; This represents the reactive power regulation between system node i and its physically connected node j. The reactive power-voltage sensitivity parameters of nodes i and j can be determined through power flow calculations. Qij is the reactive power transmission value between nodes i and j, which is obtained by the acquisition and monitoring system.

[0072] The matrix form described above comprehensively depicts the voltage and reactive power demand of the wind power AC / DC system, which is more in line with the actual operation. The larger the value of the matrix element, the more stable the system voltage, the higher the voltage-reactive power sensitivity of the corresponding node, and the better the effect of implementing reactive power source regulation of voltage.

[0073] The formula for calculating the voltage-reactive power integrated similarity distance of the wind power AC / DC system in S3 is as follows:

[0074] (8)

[0075] In equation (8), D(i,j) represents the similarity distance between any nodes i and j in the system with respect to the voltage-reactive power comprehensive evaluation index. The smaller the value, the more similar the voltage-reactive power comprehensive evaluation index value of node i is to that of node j.

[0076] Calculate the voltage-reactive power combined similarity distance between any two nodes in the system, and construct the combined similarity distance matrix of the system:

[0077]

[0078] In equation (9), DVQSI represents the comprehensive similarity distance matrix of the wind power AC / DC system, which is an N×N matrix. By clustering and partitioning the matrix based on the value of its elements, the optimal number of clusters M is determined, thereby reducing the N×N matrix to an M×M matrix. At the same time, the optimal partition Sbest set is output.

[0079] (10)

[0080] In Equation (10), Sbest is the optimal partition set of the wind power AC / DC system. The node set S of the wind power AC / DC system is divided into M regions after being clustered by voltage-reactive power comprehensive similarity distance.

[0081] Furthermore, the node corresponding to the maximum value of the voltage-reactive power comprehensive evaluation index in each region is selected as the dominant node in that region:

[0082] (11)

[0083] In Equation (11), Hk represents the voltage-reactive power comprehensive evaluation index value of the dominant node in the kth region within the optimal partition set of the wind power AC / DC system, and || ||∞ represents the infinite norm of the voltage-reactive power comprehensive evaluation index matrix VQSI(i) of node i.

[0084] In S4, based on the operating characteristics of reactive power sources in each region, an optimization model for reactive power reserve demand allocation is established as follows:

[0085] (12)

[0086] In equation (12), G and This represents the overall reactive power reserve requirement for high-proportion wind power AC / DC systems. , , and Let G represent the reactive power reserve values ​​of the doubly-fed wind farm, the direct-drive wind farm, the reactive power compensation device, and the conventional generator set in the k-th region of the optimal partition set of the wind power AC / DC system, respectively; and let G be the objective function for optimizing the allocation of reactive power reserve requirements.

[0087] The optimization model includes equality constraints, namely the power flow equations of the wind power AC / DC system, where and S represents the optimal partition set S of the wind power AC / DC system. k The active power and reactive power values ​​of internal node i; and Optimal partition set S k The active and reactive power values ​​of DC transmission at internal node i; , S represents the optimal set of partitions. k Voltage amplitudes at internal nodes i and j; N k For the optimal set of partitions S k The number of nodes; For the optimal set of partitions S k The phase difference between nodes i and j within the same node; and For the optimal set of partitions Sk The admittance matrices of nodes i and j within the matrix;

[0088] The optimization model includes inequality constraints, namely, upper and lower limit constraints on the reactive power output of the wind power AC / DC system. , , , and These are the equivalent parameters of the stator reactance, excitation parameters, maximum allowable operating current of the rotor of the doubly-fed wind farm, terminal voltage of the doubly-fed wind farm, and output active power of the doubly-fed wind farm in the kth region of the optimal zoning set of the AC / DC wind power system, respectively. , and These are the maximum allowable reactive power output, reactive power output, and apparent power output of the direct-drive wind farm units in the kth region of the optimal partition set, respectively. and The maximum allowable output value and current reactive power output value of the reactive power compensation device in the kth region within the optimal partition set; and The maximum permissible reactive power output and current reactive power output of the conventional generator set in the kth region of the optimal partition set; , , and The parameters are related to the wind farm turbine model and the internal wiring topology of the wind farm. and The parameters are related to the corresponding conventional generator set model and can all be determined in advance; , , , , and Data is acquired in real time by the data acquisition and monitoring system.

[0089] Example 2:

[0090] Some further additions are proposed based on the above embodiments;

[0091] like Figure 2 As shown, an improved IEEE 39-bus test system is constructed, comprising two doubly-fed induction generator (DFIG) wind farms, one direct-drive wind farm, and two conventional DC transmission lines. The wind farms have a single turbine capacity of 1.5MW, and the collector voltage is 35kV. The reactive power and voltage levels of the test system are accurately characterized using a comprehensive voltage-reactive power evaluation index matrix for the AC / DC system. Adaptive clustering partitioning of the test system is achieved using comprehensive similarity calculations. Figure 2As shown, the optimal number of clusters is 5, and the partitions are S1, S2, S3, S4 and S5. The dominant node numbers of each region are #30, #28, #6, #19 and #23, respectively. The reactive power reserve assessment calculation model is simplified through cluster partitioning.

[0092] Comparing the reactive power reserve demand calculation method of this invention with two other methods—one that does not consider clustering partitioning—the corresponding calculation results are obtained, such as... Figure 3 As shown, under different scenarios such as normal operation, N-1 on AC lines, and DC line shutdown, the optimal reactive power reserve demand assessment calculation results proposed by this method are always too small. This indicates that under the conditions of meeting system voltage safety and various reactive power source operation constraints, the reactive power reserve proposed by this invention has lower cost and better economic efficiency. Figure 4 To test the reactive power reserve requirement calculation efficiency of the test system in this embodiment of the invention, that is, to compare the calculation time of the method proposed in this invention with the method without considering clustering and partitioning under the same typical scenario, it can be found that the calculation time of this method is much lower than that of the previous method, and the calculation efficiency advantage becomes more obvious as the simulation scenario and the node scale increase. Figure 5 In this embodiment of the invention, the test system is used to measure the steady-state voltage distribution of each node under a typical DC line blocking scenario, with and without reactive power reserve. Without reactive power reserve, the voltage amplitude fluctuation of each node changes significantly, and some nodes even exceed the voltage safety range boundary of high / low voltage crossing, seriously threatening the safety of the power grid. However, with the reactive power reserve implemented by the method of this invention, although the amplitude fluctuates slightly during the process, it does not exceed the safety boundary, and the overall voltage safety level of the wind power AC / DC system is significantly improved.

[0093] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for calculating reactive power reserve requirements in AC / DC power systems with a high proportion of wind power, characterized by: At least the following steps are included: S1: Evaluate the parameters of the wind power AC / DC power system of the target, obtain the network architecture topology within the system, determine the access locations of different types of reactive power sources within the system, and use the existing acquisition system or data system to determine the information of the DC converter station of the wind farm. The information includes at least the operating control parameters, the voltage of each node in the system, the reactive power output value, and the power flow of the grid. S2: Screen typical scenarios under different operating modes, construct a calculation formula for the voltage-reactive power comprehensive evaluation index matrix of wind power AC / DC power system, combine the acquired system parameters and current status information, determine the voltage-reactive power comprehensive evaluation index results of wind power AC / DC power system under various typical scenarios through power flow calculation, and comprehensively characterize the voltage and reactive power demand of the system. The typical scenarios include at least normal, AC line N-1, and DC blocking outage. The typical scenarios in S2 are a set of typical scenarios, as shown in the following formula: （2） In equation (2), A collection of typical scenarios; is the l-th typical scenario in the set of typical scenarios; A is the number of typical scenarios, which is given in advance by the numerical sampling simulation of the power system. The formula for calculating the voltage-reactive power comprehensive evaluation index matrix of wind power AC / DC power systems is as follows: （3） （6） （7） In equations (3) to (5), This is a comprehensive evaluation index matrix of voltage and reactive power for wind power AC / DC power systems, derived from the comprehensive voltage index matrix of the system. System reactive power comprehensive index matrix The weighted summation is used to calculate the result; α and β are the weighting coefficients for the voltage comprehensive index and the reactive power comprehensive index, respectively, which are set in advance based on the system operating parameters; VSI il These are elements in the system voltage comprehensive index matrix; i represents any node in the system node set S; l represents the set of typical scenarios. Any scenario; It is an N×A matrix, reflecting the voltage stability of N nodes in an AC / DC power system under A typical scenarios; Similarly, QSI il For elements in the system reactive power comprehensive index matrix, Also an N×A matrix, it reflects the reactive power reserve effect of N nodes in AC / DC power system under A typical scenarios; Equations (6) and (7) represent the calculation formulas for each element VSI of the system voltage comprehensive index matrix and each element QSI of the system reactive power comprehensive index matrix; U0, U min U end T set and U set U0 and U1 represent the initial state value of the node voltage, the lowest value during a fault or disturbance, the steady-state value after the fault or disturbance is recovered, the duration of the fault or disturbance at the node, and the node voltage safety threshold, respectively; min U end and T set Acquired by the data acquisition and monitoring system, U set The voltage level of the node is determined in advance and set to 80% of the rated voltage; ε is a correction factor constant, which is taken as 0.1; This represents the reactive power regulation between system node i and its physically connected node j. The reactive-voltage sensitivity parameters for nodes i and j are determined through power flow calculations, Q. ij The reactive power transmission value between nodes i and j is obtained by the acquisition and monitoring system; The above matrix form comprehensively depicts the voltage and reactive power demand of the wind power AC / DC power system, which is more in line with the actual operation. The larger the element value of the comprehensive evaluation index matrix, the more stable the system voltage, the higher the voltage-reactive power sensitivity of the corresponding node, and the better the effect of implementing reactive power source regulation on voltage. S3: Construct a formula for calculating the voltage-reactive power integrated similarity distance of the wind power AC / DC power system. Cluster the system by calculating the integrated distance matrix, determine the optimal number of clusters M, and output the optimal partition S. best Based on the optimal partitioning, the node corresponding to the maximum value of the voltage-reactive power comprehensive evaluation index in each region is selected as the dominant node in that region. S4: Based on the operating characteristics of reactive power sources in each region, establish an optimization model for reactive power reserve demand allocation to achieve optimal reactive power reserve under the conditions of satisfying system voltage safety and various reactive power source operating constraints. Solve the optimization model based on the genetic intelligent algorithm, output the reactive power reserve calculation results for each region, and realize the optimal reactive power reserve evaluation calculation under the conditions of satisfying system voltage safety and various reactive power source operating constraints, and end the work.

2. The method for calculating reactive power reserve requirements of AC / DC power systems with a high proportion of wind power, as described in claim 1, is characterized in that: In the wind power AC / DC power system of S1, wind power, nearby DC reactive power compensation devices, and conventional generator sets serve as reactive power reserve sources, specifically including the following reactive power reserves: （1） In equation (1), S is the set of all nodes included in the wind power AC / DC power system; This represents the total reactive power reserve requirement of the system. This represents the reactive power reserve of the doubly fed wind farm where node i is located in the system; This represents the reactive power reserve of the direct-drive wind farm where node j is located in the system. This represents the reactive power reserve of the reactive power compensation device where node f is located in the system. This represents the reactive power reserve of the conventional generator set where node g is located in the system.

3. The method for calculating reactive power reserve requirements of AC / DC power systems with a high proportion of wind power, as described in claim 2, is characterized in that: The formula for calculating the voltage-reactive power comprehensive similarity distance of the wind power AC / DC power system in S3 is as follows: （8） In equation (8), D(i,j) represents the similarity distance between any node i and j in the system with respect to the voltage-reactive power comprehensive evaluation index. The smaller the value, the more similar the voltage-reactive power comprehensive evaluation index value of node i is to that of node j. Calculate the voltage-reactive power combined similarity distance between any two nodes in the system, and construct the system's combined distance matrix: In equation (9), The comprehensive distance matrix of the wind power AC / DC power system is an N×N matrix. By clustering and partitioning the matrix elements according to their values, the optimal number of clusters M is determined, thus reducing the N×N matrix to an M×M matrix. Simultaneously, the optimal partition S is output. best gather: （10） In equation (10), S best The optimal partition set for the wind power AC / DC power system is defined by the node set S of the wind power AC / DC power system, which is divided into M regions after voltage-reactive power comprehensive similarity distance clustering. Furthermore, the node corresponding to the maximum value of the voltage-reactive power comprehensive evaluation index in each region is selected as the dominant node in that region: （11） In equation (11), H k Represents the k-th region S within the optimal partition set of the wind power AC / DC power system. k The voltage-reactive power comprehensive evaluation index value of the dominant node, || || ∞ This represents the voltage-reactive power comprehensive evaluation index matrix for node i. The infinite norm of .

4. The method for calculating reactive power reserve requirements of AC / DC power systems with a high proportion of wind power as described in claim 1, characterized in that: In S4, based on the operating characteristics of reactive power sources in each region, an optimization model for reactive power reserve demand allocation is established as follows: （12） In equation (12), G and This represents the overall reactive power reserve requirement for AC / DC power systems with a high proportion of wind power. , , and Let G represent the reactive power reserve values ​​of doubly-fed wind farms, direct-drive wind farms, reactive power compensation devices, and conventional generator sets in the k-th region of the optimal partition set of the wind power AC / DC power system, respectively; and let G be the objective function for optimizing the allocation of reactive power reserve requirements. The optimization model includes equality constraints, namely the power flow equations of the wind power AC / DC power system, where and Represent the k-th region S within the optimal partition set of the wind power AC / DC power system. k The active power and reactive power values ​​of internal node i; and For the k-th region S in the optimal partition set k The active and reactive power values ​​of DC transmission at internal node i; , The k-th region S in the optimal partition set k Voltage amplitudes at internal nodes i and j; N k For the k-th region S in the optimal partition set k The number of nodes; For the k-th region S in the optimal partition set k The phase difference between nodes i and j within the same node; and For the k-th region S in the optimal partition set k The admittance matrices of nodes i and j within the matrix; The optimization model includes inequality constraints, namely, upper and lower limit constraints on the reactive power output of the wind power AC / DC power system. , , , and These are the equivalent parameters of the stator reactance, excitation parameters, maximum allowable rotor current of the doubly-fed wind farm, terminal voltage of the doubly-fed wind farm, and output active power of the doubly-fed wind farm in the kth region of the optimal zoning set of the wind power AC / DC power system, respectively. , and These are the maximum allowable reactive power output, reactive power output, and apparent power output of the direct-drive wind farm units in the kth region of the optimal partition set, respectively. and The maximum allowable output value and current reactive power output value of the reactive power compensation device in the kth region within the optimal partition set; and The maximum allowable reactive power output value and the current reactive power output value of the conventional generator set in the kth region of the optimal partition set; , , and The parameters are related to the wind farm turbine model and the internal wiring topology of the wind farm; , , , , and Data is acquired in real time by the data acquisition and monitoring system.

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