Optimal configuration method and system for coaxial flywheel high-inertia distributed phase modifier and storage medium

Abstract

The invention discloses an optimal configuration method and system for a coaxial flywheel high-inertia distributed phase modifier and a storage medium, and belongs to the technical field of resource optimal configuration. The method comprises the steps of obtaining parameter data of a target power grid system; constructing a distribution point and capacity optimization configuration model of the distributed phase modifier according to the parameter data of the target power grid system; solving the distribution point and capacity optimization configuration model of the distributed phase modifier to obtain an optimal distribution point and capacity configuration scheme of the distributed phase modifier; based on the parameter data of the target power grid system and the optimal distribution point and capacity configuration scheme of the distributed phase modifier, constructing an additional flywheel mass block optimal configuration model of the distributed phase modifier; and solving the additional flywheel mass block optimal configuration model of the distributed phase modifier to obtain an optimal additional flywheel mass block configuration scheme of the distributed phase modifier. According to the method, the distribution points, the capacity and the additional flywheel mass block of the coaxial flywheel high-inertia distributed phase modifier are optimally configured, and the short-circuit ratio and the inertia level are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of resource optimization configuration, and in particular relates to an optimization configuration method, system and storage medium for a coaxial flywheel high-inertia distributed phase regulator. Background Art

[0002] Under the background of the "dual carbon" goal, new energy represented by wind power and photovoltaics has developed rapidly. As the penetration rate of new energy in the system continues to increase, the system short-circuit ratio and inertia level continue to decrease, and the system voltage and frequency support capacity is increasingly insufficient. In view of the problem of insufficient system support capacity, it is considered to improve the system support capacity by adding distributed phase regulators.

[0003] At present, most of the research on the optimal configuration of distributed phase condensers only considers their unilateral improvement effect on short-circuit ratio or inertia, and there is a lack of research on the optimal configuration method of distributed phase condensers that comprehensively considers the improvement of short-circuit ratio and inertia level. There are problems such as unreasonable configuration schemes or non-optimal comprehensive support effects on the system, which makes the configured distributed phase condensers fail to fully play their role in improving the short-circuit ratio and inertia level of the system. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and to provide a method, system and storage medium for optimizing the configuration of a coaxial flywheel high-inertia distributed phase regulator, so as to optimize the configuration of the distribution, capacity and additional flywheel mass block of the coaxial flywheel high-inertia distributed phase regulator and improve the system short-circuit ratio and inertia level.

[0005] The present invention provides the following technical solutions:

[0006] In a first aspect, a method for optimizing configuration of a coaxial flywheel high-inertia distributed phase regulator is provided, comprising: obtaining parameter data of a target power grid system;

[0007] Constructing a distributed phase regulator location and capacity optimization configuration model according to the parameter data of the target power grid system;

[0008] Solving the location and capacity optimization configuration model of the distributed phase regulator to obtain the optimal location and capacity configuration plan of the distributed phase regulator;

[0009] Based on the parameter data of the target power grid system and the optimal layout and capacity configuration scheme of the distributed phase regulator, an additional flywheel mass block optimization configuration model of the distributed phase regulator is constructed;

[0010] The additional flywheel mass block optimization configuration model of the distributed phase condenser is solved to obtain the optimal additional flywheel mass block configuration scheme of the distributed phase condenser.

[0011] As an optional technical solution of the present invention, the parameter data of the target power grid system includes: the number of new energy stations, the number of synchronous machines, and the minimum new energy multi-station short-circuit ratio of each node and the minimum and maximum values ​​of the voltage amplitude; the node is located in the new energy station and is used to configure distributed phase regulators.

[0012] As an optional technical solution of the present invention, the objective function of the distributed phase regulator point and capacity optimization configuration model includes minimizing the distributed phase regulator configuration cost and maximizing the system short circuit ratio improvement index value;

[0013] The distributed phase regulator configuration cost is minimal It is expressed as:

[0014] ;

[0015] in, The decision variable indicating whether the i-th node is equipped with a distributed phase regulator, Indicates that the node is configured with a distributed phase regulator. Indicates that the node is not configured with a distributed phase regulator; Indicates the number of distributed phase regulators configured on the i-th node, Represents the capacity of a single distributed phase regulator, represents the unit capacity price of distributed phase regulators, represents the fixed installation cost of a single distributed phase regulator, represents the distributed phase regulator placement screening index of the i-th node, c represents the distributed phase regulator placement screening index penalty factor, and N represents the total number of placements;

[0016] The system short-circuit ratio improvement index value is the maximum It is expressed as:

[0017] ;

[0018] in, Indicates the system short-circuit ratio improvement index value.

[0019] As an optional technical solution of the present invention, the constraints of the distributed phase-converter point layout and capacity optimization configuration model include MRSCR constraints, node voltage safety constraints, output constraints of different types of units, maximum configuration quantity constraints and power flow equation constraints;

[0020] The MRSCR constraint is expressed as:

[0021] ;

[0022] in, represents the short-circuit ratio of the renewable energy multi-station at the i-th node, represents the minimum short-circuit ratio of new energy multi-stations at the i-th node;

[0023] The node voltage safety constraint is expressed as:

[0024] ;

[0025] in, represents the voltage amplitude of the ith node, and Respectively represent the minimum and maximum voltage amplitudes of the i-th node;

[0026] The output constraints of different types of units are expressed as:

[0027] ;

[0028] in, and They represent the current active and reactive power output of the power supply at the i-th node, respectively. and They represent the upper limit of active power and reactive power output of the power supply at the i-th node respectively;

[0029] The maximum configuration quantity constraint is expressed as:

[0030] ;

[0031] in, Indicates the number of distributed phase regulators configured on the i-th node, They represent the upper limit of the number of distributed phase regulators configured on the i-th node respectively;

[0032] The power flow equation constraint is expressed as:

[0033] ;

[0034] in, and represent the active and reactive loads on the ith node, respectively. and Represent the voltage amplitudes of the i-th node and the j-th node respectively, and denote the conductance and susceptance of the line between the ith node and the jth node, respectively. represents the voltage phase angle between the i-th node and the j-th node.

[0035] As an optional technical solution of the present invention, solving the location and capacity optimization configuration model of the distributed phase regulator to obtain the optimal location and capacity configuration solution of the distributed phase regulator includes:

[0036] A genetic algorithm is used to solve the distributed phase regulator location and capacity optimization configuration model to obtain a Pareto solution set of the distributed phase regulator location and capacity configuration;

[0037] Based on fuzzy theory, the optimal compromise solution is selected from the Pareto solution set of the distributed phase condenser location and capacity configuration to obtain the optimal location and capacity configuration plan of the distributed phase condenser.

[0038] As an optional technical solution of the present invention, the objective function of the additional flywheel mass block optimization configuration model of the distributed phase regulator includes minimizing the investment cost of the additional flywheel mass block and maximizing the system inertia improvement;

[0039] The additional flywheel mass investment cost is minimal It is expressed as:

[0040] ;

[0041] in, represents the total number of distributed phase regulators in the optimal location and capacity configuration scheme of the distributed phase regulators, Indicates the number of additional flywheel masses that need to be configured for the nth distributed phase regulator. represents the unit price of the additional flywheel mass, represents the fixed installation cost of the additional flywheel mass;

[0042] The system inertia is increased to the maximum It is expressed as:

[0043] ;

[0044] in, Indicates the system inertia improvement index value.

[0045] As an optional technical solution of the present invention, the constraint conditions of the additional flywheel mass block optimization configuration model of the distributed phase regulator include minimum inertia safety constraint, maximum number constraint of additional flywheel mass blocks and distribution balance constraint of additional flywheel mass blocks;

[0046] The minimum inertia safety constraint is expressed as:

[0047] ;

[0048] in, represents the equivalent inertia of the system after the additional flywheel mass block is connected, Represents the minimum inertia of the system;

[0049] The maximum number constraint of the additional flywheel mass blocks is expressed as:

[0050] ;

[0051] in, It represents the upper limit of the number of flywheel masses attached to the nth distributed phase regulator;

[0052] The additional flywheel mass distribution balance constraint is expressed as:

[0053] ;

[0054] in, represents the mean value of the number of flywheel masses attached to the distributed condenser, It represents the upper limit of the distribution balance of the additional flywheel mass block of the distributed phase regulator.

[0055] As an optional technical solution of the present invention, the method of solving the additional flywheel mass block optimization configuration model of the distributed phase condenser to obtain the optimal additional flywheel mass block configuration scheme of the distributed phase condenser includes:

[0056] A genetic algorithm is used to solve the optimization configuration model of the additional flywheel mass block of the distributed phase condenser to obtain a Pareto solution set of the additional flywheel mass block configuration of the distributed phase condenser;

[0057] Based on fuzzy theory, the optimal compromise solution is selected from the Pareto solution set of the additional flywheel mass block configuration of the distributed phase condenser, and the optimal additional flywheel mass block configuration scheme of the distributed phase condenser is obtained.

[0058] In a second aspect, a system for optimizing configuration of a coaxial flywheel high-inertia distributed phase regulator is provided, including: a data acquisition module for acquiring parameter data of a target power grid system;

[0059] A first model building module is used to build a point layout and capacity optimization configuration model of distributed phase regulators according to parameter data of the target power grid system;

[0060] The first solving module is used to solve the location and capacity optimization configuration model of the distributed phase regulator to obtain the optimal location and capacity configuration plan of the distributed phase regulator;

[0061] A second model building module is used to build an additional flywheel mass block optimization configuration model of the distributed phase regulator based on the parameter data of the target power grid system and the optimal layout and capacity configuration plan of the distributed phase regulator;

[0062] The second solving module is used to solve the additional flywheel mass block optimization configuration model of the distributed phase condenser to obtain the optimal additional flywheel mass block configuration scheme of the distributed phase condenser.

[0063] According to a third aspect, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that when the program is executed by a processor, the steps of the method for optimizing the configuration of the coaxial flywheel high-inertia distributed phase regulator according to the first aspect are implemented.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] An optimization configuration method for a coaxial flywheel high-inertia distributed phase regulator provided by the present invention optimizes the distribution, capacity and additional flywheel mass block of the coaxial flywheel high-inertia distributed phase regulator, thereby achieving a better system short-circuit ratio and inertia level improvement effect at a lower configuration cost, and providing a reference basis for the optimization configuration of supporting resources for improving the system short-circuit ratio and inertia level. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 is a flow chart of an optimization configuration method of a coaxial flywheel high-inertia distributed phase regulator in an embodiment of the present invention;

[0067] Figure 2 It is a structural schematic diagram of a 750kV system of the Northwest Power Grid in an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0069] Example 1

[0070] This embodiment provides an optimization configuration method for a coaxial flywheel high-inertia distributed phase regulator, and a 750kV system of the Northwest Power Grid is used as the application object of this method. Figure 1 As shown, the method comprises the following steps:

[0071] Step 1: Obtain parameter data of the target power grid system.

[0072] Specifically, the parameter data of the target power grid system includes: the number of new energy stations, the number of synchronous machines, and the minimum new energy multi-station short-circuit ratio of each node and the minimum and maximum values ​​of the voltage amplitude. The node is located in the new energy station, specifically at the gathering point of the new energy station, and is used to configure the distributed phase regulator.

[0073] like Figure 2 As shown, in this embodiment, a 750kV system of the Northwest Power Grid includes 19 new energy stations and 4 conventional synchronous machines, wherein the 19 new energy stations are divided into 12 photovoltaic stations and 7 wind power stations. The parameter data of the conventional synchronous machine is shown in Table 1, and the parameter data of the new energy station is shown in Table 2.

[0074] Table 1 Conventional synchronous machine parameter data table

[0075] Synchronous machine Inertia time constant H Speed ​​​​regulator time constant T Adjustment coefficient R Damping coefficient D Capacity / MW G1 5.5 8 0.04 2 1250 G2 5.5 7 0.05 1.5 1050 G3 3.5 10 0.03 1 700 G4 3.5 10 0.03 1 700

[0076] Table 2 New energy station parameter data table

[0077]

[0078] In this embodiment, the minimum and maximum values ​​of the node voltage amplitude are 0.95pu and 1.05pu respectively, and the minimum short-circuit ratio of the node is 1.2pu. At the same time, the grid-connected inverter capacity of the new energy station is set to 1.1 times the rated active capacity, and the maximum limit of the power adjustable range of the conventional synchronous machine is set to 15% of the rated power.

[0079] Step 2: Constructing a distributed phase-shifting condenser point and capacity optimization configuration model based on the parameter data of the target power grid system.

[0080] 2.1. The objective function of the distributed phase regulator location and capacity optimization configuration model includes minimizing the distributed phase regulator configuration cost and maximizing the system short circuit ratio improvement index value.

[0081] The distributed phase regulator configuration cost is minimal It is expressed as:

[0082] ;

[0083] in, The decision variable indicating whether the i-th node is equipped with a distributed phase regulator, Indicates that the node is configured with a distributed phase regulator. Indicates that the node is not configured with a distributed phase regulator; Indicates the number of distributed phase regulators configured on the i-th node, Represents the capacity of a single distributed phase regulator, represents the unit capacity price of distributed phase regulators, represents the fixed installation cost of a single distributed phase regulator, represents the distributed phase regulator placement screening index of the i-th node, c represents the distributed phase regulator placement screening index penalty factor, and N represents the total number of placements.

[0084] In this embodiment, the capacity of a single distributed phase condenser is 50 MVar, the unit capacity price of the distributed phase condenser is 240,000 yuan / MVar, the fixed installation cost of a single distributed phase condenser is 1.5 million yuan, the upper limit of the number of distributed phase condensers that can be configured in a single new energy station is 5, and the penalty factor of the distributed phase condenser location screening index is 0.01.

[0085] The short-circuit ratio of the system improves the index value to the maximum It is expressed as:

[0086] ;

[0087] in, Indicates the system short-circuit ratio improvement index value.

[0088] 2.2. The constraints of the distributed phase-converter layout and capacity optimization configuration model include MRSCR (new energy multi-station short-circuit ratio) constraints, node voltage safety constraints, output constraints of different types of units, maximum configuration quantity constraints and power flow equation constraints.

[0089] The MRSCR constraint is expressed as:

[0090] ;

[0091] in, represents the short-circuit ratio of the new energy multi-station at the i-th node, Represents the minimum renewable energy multi-station short-circuit ratio of the i-th node.

[0092] The node voltage safety constraint is expressed as:

[0093] ;

[0094] in, represents the voltage amplitude of the ith node, and They represent the minimum and maximum voltage amplitudes of the i-th node respectively.

[0095] The output constraints of different types of units are expressed as:

[0096] ;

[0097] in, and They represent the current active and reactive power output of the power supply at the i-th node, respectively. and They represent the upper limit of active power and reactive power output of the power supply at the i-th node respectively.

[0098] The maximum configuration quantity constraint is expressed as:

[0099] ;

[0100] in, Indicates the number of distributed phase regulators configured on the i-th node, They respectively represent the upper limit of the number of distributed phase regulators configured on the i-th node.

[0101] The power flow equation constraint is expressed as:

[0102] ;

[0103] in, and represent the active and reactive loads on the ith node, respectively. and Represent the voltage amplitudes of the i-th node and the j-th node respectively, and denote the conductance and susceptance of the line between the ith node and the jth node, respectively. represents the voltage phase angle between the i-th node and the j-th node.

[0104] Step 3: Solve the location and capacity optimization configuration model of the distributed phase regulator to obtain the optimal location and capacity configuration plan of the distributed phase regulator.

[0105] Specifically, a genetic algorithm is used to solve the distributed phase shifter point and capacity optimization configuration model to obtain the Pareto solution set of the distributed phase shifter point and capacity configuration. Based on fuzzy theory, the optimal compromise solution is selected from the Pareto solution set of the distributed phase shifter point and capacity configuration to obtain the optimal point and capacity configuration scheme of the distributed phase shifter. Among them, the maximum number of iterations of the genetic algorithm is 50, the crossover probability is 0.75, and the mutation probability is 0.006. The solution process is the existing technology and will not be repeated here.

[0106] In this embodiment, the optimal compromise solution is: 22 distributed phase regulators are configured at 8 sites (A2, A5, B1, B3, B6, C1, C4, D2). The optimal layout and capacity configuration scheme of the distributed phase regulators are shown in Table 3.

[0107] Table 3 Optimal location and capacity configuration of distributed phase regulators

[0108] Site Number of configuration units Pre-configuration MRSCR After configuring MRSCR A2 4 1.83 2.89 A5 2 1.79 2.67 B1 4 1.74 2.83 B3 2 1.72 2.81 B6 1 1.77 2.73 C1 2 1.81 2.79 C4 4 1.78 2.84 D2 3 1.70 2.81

[0109] Step 4: Based on the parameter data of the target power grid system and the optimal location and capacity configuration plan of the distributed phase regulator, an additional flywheel mass block optimization configuration model of the distributed phase regulator is constructed.

[0110] 4.1. The objective function of the additional flywheel mass block optimization configuration model of the distributed phase regulator includes minimizing the investment cost of the additional flywheel mass block and maximizing the system inertia improvement.

[0111] The additional flywheel mass investment cost is minimal It is expressed as:

[0112] ;

[0113] in, Indicates the number of additional flywheel masses that need to be configured for the nth distributed phase regulator. represents the unit price of the additional flywheel mass, represents the fixed installation cost of the additional flywheel mass.

[0114] In this embodiment, the additional flywheel mass block of a single distributed phase condenser provides 100MWs of inertia support, the unit price of the additional flywheel mass block is 1 million yuan, the fixed installation cost of the additional flywheel mass block is 100,000 yuan, and the upper limit of the number of flywheel mass blocks that can be added to a single distributed phase condenser is 3.

[0115] The system inertia is increased to the maximum It is expressed as:

[0116] ;

[0117] in, Indicates the system inertia improvement index value.

[0118] 4.2. The constraint conditions of the additional flywheel mass block optimization configuration model of the distributed phase regulator include minimum inertia safety constraint, maximum number constraint of additional flywheel mass blocks and distribution balance constraint of additional flywheel mass blocks.

[0119] The minimum inertia safety constraint is expressed as:

[0120] ;

[0121] in, represents the equivalent inertia of the system after the additional flywheel mass block is connected, Indicates the minimum inertia of the system, which is the minimum inertia of the system when the system initial frequency change rate does not exceed 0.2 Hz / s and the maximum system frequency deviation does not exceed 0.5 Hz.

[0122] In this embodiment, the system minimum inertia corresponding to the system initial frequency change rate does not exceed 0.2Hz / s and the maximum system frequency deviation does not exceed 0.5Hz

[0123] The maximum number constraint of the additional flywheel mass blocks is expressed as:

[0124] .

[0125] The additional flywheel mass distribution balance constraint is expressed as:

[0126] ;

[0127] in, represents the mean value of the number of flywheel masses attached to the distributed condenser, It represents the upper limit of the distribution balance of the additional flywheel mass block of the distributed phase regulator.

[0128] Step 5: Solve the additional flywheel mass block optimization configuration model of the distributed phase condenser to obtain the optimal additional flywheel mass block configuration scheme of the distributed phase condenser.

[0129] Specifically, a genetic algorithm is used to solve the optimization configuration model of the additional flywheel mass block of the distributed phase condenser, and a Pareto solution set of the additional flywheel mass block configuration of the distributed phase condenser is obtained. Based on fuzzy theory, the optimal compromise solution is selected from the Pareto solution set of the additional flywheel mass block configuration of the distributed phase condenser, and the optimal additional flywheel mass block configuration scheme of the distributed phase condenser is obtained. Among them, the maximum number of iterations of the genetic algorithm is 50, the crossover probability is 0.75, and the mutation probability is 0.006. The solution process is the existing technology and will not be repeated here.

[0130] In this embodiment, the configuration result of the additional flywheel mass blocks of the distributed phase condenser is as follows: each distributed phase condenser is configured with 2 additional flywheel mass blocks.

[0131] The optimal distribution and capacity of distributed condensers and the improvement results of system short-circuit ratio and inertia level before and after the additional flywheel mass block configuration are shown in Table 4.

[0132] Table 4 Comparison of system short-circuit ratio and inertia level improvement results before and after configuration

[0133] Minimum MRSCR MRSCR pass rate / % Short circuit ratio improvement index value System inertia H / s Inertia improvement index value Before configuration 1.70 17.4 -0.149 1.60 -0.111 After configuration 2.67 100 0.866 2.16 0.197

[0134] As shown in Table 4, after the coaxial flywheel high-inertia distributed phase regulator is configured, the MRSCR of the new energy station is increased from the lowest 1.70 to 2.67, the MRSCR pass rate is increased from 17.4% to 100%, and the system short-circuit ratio improvement index value is increased from -0.149 before configuration to 0.866, indicating that the voltage support capacity of the system is significantly improved. After the coaxial flywheel high-inertia distributed phase regulator is configured, the system inertia level is increased from 1.60 to 2.16, and the system inertia improvement index value is increased from -0.111 before configuration to 0.197, and the system inertia level is significantly improved.

[0135] Example 2

[0136] This embodiment provides an optimized configuration system for a coaxial flywheel high-inertia distributed phase regulator, including:

[0137] The data acquisition module is used to acquire parameter data of the target power grid system.

[0138] The first model building module is used to build a distributed phase regulator point layout and capacity optimization configuration model according to the parameter data of the target power grid system.

[0139] The first solving module is used to solve the location and capacity optimization configuration model of the distributed phase regulator to obtain the optimal location and capacity configuration plan of the distributed phase regulator.

[0140] The second model building module is used to build an additional flywheel mass block optimization configuration model of the distributed phase regulator based on the parameter data of the target power grid system and the optimal layout and capacity configuration plan of the distributed phase regulator.

[0141] The second solving module is used to solve the additional flywheel mass block optimization configuration model of the distributed phase condenser to obtain the optimal additional flywheel mass block configuration scheme of the distributed phase condenser.

[0142] Example 3

[0143] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of the method for optimizing the configuration of the coaxial flywheel high-inertia distributed phase regulator described in Embodiment 1 are implemented.

[0144] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0145] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0146] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0147] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0148] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for optimizing the configuration of a coaxial flywheel high-inertia distributed phase regulator, characterized in that: include: Obtain parameter data of the target power grid system; Constructing a distributed phase regulator location and capacity optimization configuration model according to the parameter data of the target power grid system; Solving the location and capacity optimization configuration model of the distributed phase regulator to obtain the optimal location and capacity configuration plan of the distributed phase regulator; Based on the parameter data of the target power grid system and the optimal layout and capacity configuration scheme of the distributed phase regulator, an additional flywheel mass block optimization configuration model of the distributed phase regulator is constructed; The additional flywheel mass block optimization configuration model of the distributed phase condenser is solved to obtain the optimal additional flywheel mass block configuration scheme of the distributed phase condenser.

2. The method for optimizing the configuration of a coaxial flywheel high inertia distributed phase condenser according to claim 1, characterized in that: The parameter data of the target power grid system include: the number of new energy stations, the number of synchronous machines, and the minimum short-circuit ratio of new energy multiple stations and the minimum and maximum values ​​of the voltage amplitude of each node; The node is located in the new energy station and is used to configure the distributed phase regulator.

3. The method for optimizing the configuration of a coaxial flywheel high inertia distributed phase condenser according to claim 1, characterized in that: The objective function of the distributed phase regulator point and capacity optimization configuration model includes minimizing the distributed phase regulator configuration cost and maximizing the system short circuit ratio improvement index value; The distributed phase regulator configuration cost is minimal It is expressed as: ； in, The decision variable indicating whether the i-th node is equipped with a distributed phase regulator, Indicates that the node is configured with a distributed phase regulator. Indicates that the node is not configured with a distributed phase regulator; Indicates the number of distributed phase regulators configured on the i-th node, Represents the capacity of a single distributed phase regulator, represents the unit capacity price of distributed phase regulators, represents the fixed installation cost of a single distributed phase regulator, represents the distributed phase regulator placement screening index of the i-th node, c represents the distributed phase regulator placement screening index penalty factor, and N represents the total number of placements; The short-circuit ratio of the system improves the index value to the maximum It is expressed as: ； in, Indicates the system short-circuit ratio improvement index value.

4. The method for optimizing the configuration of a coaxial flywheel high inertia distributed phase condenser according to claim 2, characterized in that: The constraints of the distributed phase-converter layout and capacity optimization configuration model include MRSCR constraints, node voltage safety constraints, output constraints of different types of units, maximum configuration quantity constraints and power flow equation constraints; The MRSCR constraint is expressed as: ； in, represents the short-circuit ratio of the renewable energy multi-station at the i-th node, represents the minimum short-circuit ratio of new energy multi-stations at the i-th node; The node voltage safety constraint is expressed as: ； in, represents the voltage amplitude of the ith node, and Respectively represent the minimum and maximum voltage amplitudes of the i-th node; The output constraints of different types of units are expressed as: ； in, and They represent the current active and reactive power output of the power supply at the i-th node, and They represent the upper limit of active power and reactive power output of the power supply at the i-th node respectively; The maximum configuration quantity constraint is expressed as: ； in, Indicates the number of distributed phase regulators configured on the i-th node, They represent the upper limit of the number of distributed phase regulators configured on the i-th node respectively; The power flow equation constraint is expressed as: ； in, and represent the active and reactive loads on the ith node, respectively. and Represent the voltage amplitudes of the i-th node and the j-th node respectively, and denote the conductance and susceptance of the line between the ith node and the jth node, respectively. represents the voltage phase angle between the i-th node and the j-th node.

5. The method for optimizing the configuration of a coaxial flywheel high inertia distributed phase condenser according to claim 1, characterized in that: The step of solving the location and capacity optimization configuration model of the distributed phase regulator to obtain the optimal location and capacity configuration scheme of the distributed phase regulator includes: A genetic algorithm is used to solve the distributed phase condenser point and capacity optimization configuration model to obtain a Pareto solution set of the distributed phase condenser point and capacity configuration; Based on fuzzy theory, the optimal compromise solution is selected from the Pareto solution set of the distributed phase condenser location and capacity configuration to obtain the optimal location and capacity configuration plan of the distributed phase condenser.

6. The method for optimizing the configuration of a coaxial flywheel high inertia distributed phase condenser according to claim 1, characterized in that: The objective function of the additional flywheel mass block optimization configuration model of the distributed phase regulator includes minimizing the investment cost of the additional flywheel mass block and maximizing the system inertia improvement; The additional flywheel mass investment cost is minimal It is expressed as: ； in, represents the total number of distributed phase regulators in the optimal location and capacity configuration scheme of the distributed phase regulators, Indicates the number of additional flywheel masses that need to be configured for the nth distributed phase regulator. represents the unit price of the additional flywheel mass, represents the fixed installation cost of the additional flywheel mass; The system inertia is increased to the maximum It is expressed as: ； in, Indicates the system inertia improvement index value.

7. The method for optimizing the configuration of a coaxial flywheel high inertia distributed phase condenser according to claim 6, characterized in that: The constraint conditions of the additional flywheel mass block optimization configuration model of the distributed phase regulator include minimum inertia safety constraint, maximum number constraint of additional flywheel mass blocks and distribution balance constraint of additional flywheel mass blocks; The minimum inertia safety constraint is expressed as: ； in, represents the equivalent inertia of the system after the additional flywheel mass block is connected, Represents the minimum inertia of the system; The maximum number constraint of the additional flywheel mass blocks is expressed as: ； in, It represents the upper limit of the number of flywheel masses attached to the nth distributed phase regulator; The additional flywheel mass distribution balance constraint is expressed as: ； in, represents the mean value of the number of flywheel masses attached to the distributed condenser, It represents the upper limit of the distribution balance of the additional flywheel mass block of the distributed phase regulator.

8. The method for optimizing the configuration of a coaxial flywheel high inertia distributed phase condenser according to claim 1, characterized in that: The step of solving the additional flywheel mass block optimization configuration model of the distributed phase condenser to obtain the optimal additional flywheel mass block configuration scheme of the distributed phase condenser includes: A genetic algorithm is used to solve the optimization configuration model of the additional flywheel mass block of the distributed phase condenser to obtain a Pareto solution set of the additional flywheel mass block configuration of the distributed phase condenser; Based on fuzzy theory, the optimal compromise solution is selected from the Pareto solution set of the additional flywheel mass block configuration of the distributed phase condenser, and the optimal additional flywheel mass block configuration scheme of the distributed phase condenser is obtained.

9. An optimized configuration system for a coaxial flywheel high inertia distributed phase regulator, characterized in that: include: A data acquisition module, used to acquire parameter data of a target power grid system; A first model building module is used to build a point layout and capacity optimization configuration model of distributed phase regulators according to parameter data of the target power grid system; The first solving module is used to solve the location and capacity optimization configuration model of the distributed phase regulator to obtain the optimal location and capacity configuration plan of the distributed phase regulator; A second model building module is used to build an additional flywheel mass block optimization configuration model of the distributed phase regulator based on the parameter data of the target power grid system and the optimal layout and capacity configuration plan of the distributed phase regulator; The second solving module is used to solve the additional flywheel mass block optimization configuration model of the distributed phase regulator to obtain the optimal additional flywheel mass block configuration scheme of the distributed phase regulator.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method for optimizing the configuration of a coaxial flywheel high-inertia distributed phase regulator as described in any one of claims 1 to 8 are implemented.

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