Control parameter optimization method, system and device for inhibiting repeated low penetration of new energy unit and medium

Abstract

This invention belongs to the field of power system automation technology, and discloses a method, system, equipment, and medium for optimizing control parameters to suppress repeated low-voltage ride-throughs by renewable energy generating units, thereby solving the problem of repeated low-voltage ride-throughs by renewable energy generating units. The method includes: adjusting the terminal voltage of the renewable energy generating unit to the lower limit of the grid operating voltage; identifying vulnerable renewable energy generating units at risk of repeated low-voltage ride-throughs and their corresponding critical faults; for vulnerable renewable energy generating units, generating a set of candidate adjustment schemes for control parameters by independently adjusting their low-voltage ride-through threshold and active current control value during low-voltage ride-throughs; and determining the optimal adjustment scheme from the set of candidate adjustment schemes. This invention can effectively identify renewable energy generating units at risk of repeated low-voltage ride-throughs in the grid after a fault, and solves the problem of repeated low-voltage ride-throughs by adjusting the control parameters of renewable energy generating units without increasing additional equipment investment costs, providing technical support for the safe and stable operation of the power grid and the efficient consumption of renewable energy.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power system automation, and particularly relates to a control parameter optimization method, system, device and medium for suppressing repeated low penetration of new energy units. BACKGROUND

[0002] The penetration rate of new energy such as photovoltaic and wind power in the power grid continues to increase, and the operating characteristics of the power system have changed profoundly. In addition to the common problem of wideband oscillation caused by the interaction between power electronic equipment and the grid or equipment, the phenomenon of active power oscillation of new energy units after line opening has also occurred in the power grid. The root cause of this phenomenon lies in the repeated entry and exit of new energy units into the low voltage penetration state, which can be referred to as the "repeated low penetration" problem. Specifically, line opening leads to a decrease in grid strength and insufficient reactive power support, which in turn causes the terminal voltage of the new energy unit to drop below the low voltage penetration threshold, triggering the low voltage penetration mechanism. Under the action of the low penetration control strategy, the active power output of the new energy unit decreases and the reactive power output increases, which promotes the terminal voltage to rise. Once the terminal voltage exceeds the threshold for exiting the low voltage, the new energy unit exits the low penetration state, which results in an increase in active power output and a decrease in reactive power output, which in turn causes the terminal voltage to drop again. This cycle continues, and the new energy unit repeatedly enters and exits the low penetration state, ultimately leading to oscillation of the terminal voltage and active power.

[0003] Currently, adjusting the control parameters of new energy units, such as reducing their low voltage penetration threshold or increasing the active current reference value during low penetration, is generally considered a potential effective way to suppress the problem from the source, with the advantages of low control cost and flexible approach. However, with the significant increase in the number of grid-connected new energy stations, implementing this strategy faces two key technical bottlenecks: first, the power grid structure is complex, and there are various fault modes. How to accurately and efficiently identify weak units that have a risk of repeated low penetration under a specific fault from a large number of new energy units lacks a systematic screening method. Second, after identifying weak units, how to quickly determine an optimal adjustment scheme that can effectively suppress oscillation and has the least impact on grid operation from numerous possible parameter adjustment combinations still lacks a mature solution.

[0004] In summary, the existing technology lacks a complete technical solution that can automatically identify weak units and optimize their control parameters to solve the repeated low penetration problem caused by line opening in a high-proportion new energy power grid. This defect restricts the safe and stable operation of the power grid and the efficient consumption of new energy. SUMMARY

[0005] Based on the above-mentioned shortcomings and deficiencies existing in the prior art, one of the purposes of the present application is to at least solve one or more of the above-mentioned problems existing in the prior art, in other words, one of the purposes of the present application is to provide a control parameter optimization method, system, device and medium for inhibiting repeated low penetration of new energy units to meet one or more of the aforementioned needs, so as to effectively solve the problem of repeated low penetration of new energy after failure by reasonably adjusting the control parameters of new energy units.

[0006] In order to achieve the above-mentioned purposes of the application, the following technical solutions are adopted in the present application:

[0007] In a first aspect, the present application provides a control parameter optimization method for inhibiting repeated low penetration of new energy units, comprising the steps of:

[0008] S1, constructing and solving an optimal power flow model with the minimum deviation of the terminal voltage of the new energy unit and the lower limit of the grid operating voltage as the objective function, obtaining the adjustment value of each adjustable resource in the grid, and adjusting the terminal voltage of the new energy unit in the grid to the lower limit of the grid operating voltage based on the adjustment value;

[0009] S2, based on the adjusted grid operating mode, calculating the short-circuit ratio of the new energy multi-station, and combining the line opening fault simulation of the near area of the new energy collection point, identifying the weak new energy unit and the corresponding key fault existing the risk of repeated low penetration from all new energy units in the grid;

[0010] S3, for the weak new energy unit, generating a candidate adjustment scheme set of control parameters by respectively and independently adjusting the low voltage ride through threshold and the active current control value during low voltage ride through;

[0011] S4, for each scheme in the candidate adjustment scheme set, checking by applying the key fault in simulation, screening out effective schemes that can avoid repeated low penetration, and determining the optimal adjustment scheme from the effective schemes based on the principle of minimizing the weighted comprehensive target value of control parameter adjustment amount.

[0012] As a preferred scheme, step S1 comprises:

[0013] S11, obtaining the data of conventional generators, new energy units, reactive power compensation devices, transformers, grid basic parameters and operating state data in the grid;

[0014] S12, according to the active power output and power factor of each new energy unit, calculating the reactive power output limit value to determine the corresponding reactive power adjustment range;

[0015] S13, constructing an optimal power flow optimization model, taking the deviation between the terminal voltage of the new energy unit and the lower limit of the grid operation voltage as the objective function, taking the power flow equation, the tap constraint of the adjustable voltage transformer, and the constraint of the number of switched capacitor groups as the equality constraints, taking the reactive power of the conventional unit, the reactive power of the switched capacitor, the reactive power of the new energy unit, the upper and lower limits of the node voltage of the non-new energy unit, and the transformer tap as the inequality constraints;

[0016] S14, solving the optimal power flow optimization model to obtain the adjustment value of each adjustable resource in the grid when the terminal voltage of the new energy unit is adjusted to the lower limit of the grid operation voltage, and adjusting the terminal voltage of the new energy unit to the lower limit of the grid operation voltage according to the adjustment value.

[0017] As a preferred scheme, step S2 comprises:

[0018] S21, calculating the short-circuit ratio of the new energy multi-station under the adjusted grid operation mode;

[0019] S22, defining the new energy unit with a short-circuit ratio lower than a preset threshold value as a candidate weak new energy unit;

[0020] S23, performing line N-1 or N-2 line outage fault simulation on the lines in the point near area of the candidate weak new energy unit;

[0021] S24, if there is a new energy unit terminal voltage lower than its low voltage ride-through threshold value after the line outage fault simulation, the new energy unit is determined as a weak new energy unit with repeated low penetration risk, and the corresponding fault is defined as a key fault.

[0022] As a preferred scheme, the preset threshold value is 3.0.

[0023] As a preferred scheme, step S3 comprises:

[0024] S31, obtaining the current value, upper limit and lower limit of the low voltage ride-through threshold value and the active current control value of the weak new energy unit;

[0025] S32, keeping the active current control value unchanged, taking the minimum value of the low voltage ride-through threshold value as the starting point, the current value as the ending point, and increasing by a preset first step length, to generate a first number of low voltage ride-through threshold adjustment schemes;

[0026] S33, keeping the low voltage ride-through threshold value unchanged, taking the current value of the active current control value as the starting point, the maximum value as the ending point, and increasing by a preset second step length, to generate a second number of active current control value adjustment schemes;

[0027] S34, the first number of adjustment schemes and the second number of adjustment schemes jointly constitute the control parameter candidate adjustment scheme set.

[0028] As a preferred scheme, the preset first step length and / or the preset second step length is 0.1.

[0029] As a preferred scheme, step S4 comprises:

[0030] S41, under the adjusted power grid operation mode, for each scheme in the candidate adjustment scheme set, the key fault is simulated and analyzed;

[0031] S42, the scheme that can make the new energy unit not repeatedly enter and exit the low voltage ride through state after simulation analysis is defined as an effective control parameter adjustment scheme;

[0032] S43, according to the low voltage ride through threshold value of the effective control parameter adjustment scheme, the adjustment value of the active current control value and the corresponding weight value, the comprehensive target value of each effective control parameter adjustment scheme is calculated;

[0033] S44, the effective control parameter adjustment scheme with the minimum comprehensive target value is determined as the optimal adjustment scheme.

[0034] In a second aspect, the present application provides a control parameter optimization system for inhibiting new energy unit repeated low penetration, which is used to realize the control parameter optimization method as described in the first aspect, comprising:

[0035] The voltage adjustment module is used to adjust the terminal voltage of the new energy unit in the power grid to the lower limit of the power grid operation voltage.

[0036] The weak unit identification module is used to identify the weak new energy unit with repeated low penetration risk based on the adjusted power grid operation mode.

[0037] The candidate scheme generation module is used to generate a set of control parameter candidate adjustment schemes of the weak new energy unit.

[0038] The optimal scheme determination module is used to determine the optimal adjustment scheme of the new energy unit control parameter from the candidate adjustment scheme set.

[0039] In a third aspect, the present application provides an electronic device, which comprises a memory, a processor and a computer program, and the computer program is executed by the processor to realize the control parameter optimization method as described in the first aspect.

[0040] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by the processor to realize the control parameter optimization method as described in the first aspect.

[0041] Compared with the prior art, the present application has the following beneficial effects:

[0042] 1. The application constructs an accurate voltage regulation model to solve the optimal power flow, which lays a solid foundation for subsequent analysis; calculates the short circuit ratio and combines fault simulation to accurately locate weak units and key faults; and adjusts the control parameters to generate candidate solutions and selects the optimal one. This systematic solution can solve the problem of repeated low penetration from the root, ensuring stable operation of the power grid.

[0043] 2. The application optimizes control parameters to better adapt the unit to the power grid during faults, maintain power output during low voltage periods, provide support for the power grid, improve the power grid's anti-interference ability, and enhance operational reliability and stability.

[0044] 3. The application selects the optimal solution based on the principle of minimizing the weighted comprehensive target value of the control parameter adjustment amount, which reduces the adjustment amount and the disturbance to the unit and the power grid while solving the problem of repeated low penetration, improving the safety and stability of the power system.

[0045] Further or more detailed beneficial effects will be described in the specific embodiments in conjunction with specific examples. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are only some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0047] Figure 1 is a flowchart of the control parameter optimization method provided by the embodiment of the application.

[0048] Figure 2 is a structural diagram of the control parameter optimization system provided by the embodiment of the application.

[0049] Figure 3 is a structural diagram of the electronic device provided by the embodiment of the application.

[0050] Reference numerals:

[0051] 300, electronic device;

[0052] 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the application will be described clearly and completely below in conjunction with the drawings in the embodiments of the application.

[0054] In the following description, numerous specific details are set forth to provide a thorough understanding of the present application. However, there is no intention to limit the application to the specific embodiments disclosed herein. Rather, the specific embodiments were provided to illustrate the present application. Other embodiments can be derived from the teaching of the present application, which is to be understood by those skilled in the art. While each embodiment is presented and described in sufficient detail, it will be understood that various alternatives, modifications, and variations can be used in conjunction with other embodiments and that it is intended to embrace all such alternatives, modifications and variations.

[0055] The following description provides examples, and is not intended to limit the scope, applicability or examples set forth in the claims. Alterations to the function and arrangement of the described elements can be made without departing from the scope of the present content. Various examples can omit, substitute, or add various procedures or components as appropriate. For instance, the methods described can be performed in an order different than that described, and various steps can be added, omitted, or combined. Also, features described with respect to some examples can be combined in other examples.

[0056] In order to better understand the embodiments of the present application, before the specific embodiments of the present application are explained in detail, the application scenarios thereof are described.

[0057] The control parameter optimization method described in the embodiments of the present application is applied to the operation process of new energy units accessing the power grid. In these scenarios, the application of the control parameter optimization method aims to solve the repeated low penetration problem of new energy units, ensure the stable operation of new energy units, and thus improve the reliability and stability of the entire power grid operation.

[0058] The new energy unit, the lower limit of the grid operating voltage, the short-circuit ratio of the new energy multi-station, the low voltage ride-through threshold, and the active current control value during low voltage ride-through involved in the embodiments of the present application are simply explained as follows:

[0059] New energy units generally refer to combinations of devices that generate electricity using renewable energy sources such as wind and solar energy. For example, wind turbine generators rotate blades driven by wind to drive generators to generate electricity; solar photovoltaic generators convert light energy directly into electrical energy using the photovoltaic effect of the semiconductor interface. These new energy units have characteristics such as intermittency and randomness, and their output power fluctuates with changes in natural conditions.

[0060] The lower limit of the grid operating voltage is the lowest value of the voltage allowed during normal operation of the power grid. The grid voltage needs to be maintained within a certain range to ensure the normal operation of various types of electrical equipment. When the voltage is lower than the lower limit of the operating voltage, it may cause electrical equipment to work abnormally, or even be damaged. The lower limit of the grid operating voltage is set to ensure the stable operation of the power grid and the quality of power supply.

[0061] The short-circuit ratio of new energy multi-station is an important indicator for measuring the voltage support strength of the new energy grid-connected system. It reflects the strength of the power grid after the new energy station is connected to the grid and the ability to withstand power fluctuations of the new energy station. The greater the short-circuit ratio of the new energy multi-station, the stronger the power grid's ability to accommodate power fluctuations of the new energy station, and the relatively smaller the impact of the new energy station on the power grid; otherwise, it means that the power grid is relatively weak, and the new energy station may have a greater impact on the stable operation of the power grid.

[0062] The low voltage ride through threshold refers to the threshold value at which the new energy unit enters the low voltage ride through state when the grid voltage drops. When the grid voltage drops below the threshold value, the new energy unit enters the low voltage ride through state and increases the reactive power to improve the voltage support capability of the grid. Setting a reasonable low voltage ride through threshold can ensure that the new energy unit can continue to operate stably when the grid voltage fluctuates and provide certain power support to the grid.

[0063] The active current control value during low voltage ride through refers to the value of the active current control of the unit output when the new energy unit is in the low voltage ride through state (i.e. the grid voltage drops below the low voltage ride through threshold and the unit remains connected to the grid). By reasonably adjusting the active current control value during low voltage ride through, the power output characteristics of the new energy unit during low voltage ride through can be optimized, and the repeated low voltage ride through of the new energy unit can be suppressed.

[0064] Embodiment one:

[0065] As shown in Figure 1 , the embodiment provides a control parameter optimization method for suppressing repeated low voltage ride through of new energy units, comprising the steps of:

[0066] S1, constructing and solving an optimal power flow model with the minimum deviation of the terminal voltage of the new energy unit and the lower limit of the grid operating voltage as the objective function, obtaining the adjustment value of each adjustable resource in the grid, and adjusting the terminal voltage of the new energy unit in the grid to the lower limit of the grid operating voltage based on the adjustment value;

[0067] S2, based on the adjusted grid operating mode, calculate the short-circuit ratio of new energy multi-station, and identify the weak new energy unit and the corresponding key fault that exist repeated low voltage ride through risk from all new energy units in the grid by combining the line opening fault simulation of the new energy collection point near area;

[0068] S3, for the weak new energy unit, generate a set of candidate adjustment schemes of control parameters by independently adjusting the low voltage ride through threshold and the active current control value during low voltage ride through respectively;

[0069] S4. For each scheme in the candidate adjustment scheme set, apply the key fault in the simulation to verify it, screen out the effective schemes that can avoid repeated low-altitude penetration, and determine the optimal adjustment scheme from the effective schemes based on the principle of minimizing the weighted comprehensive target value of the control parameter adjustment amount.

[0070] Specifically, step S1 includes:

[0071] S11. Obtain data on conventional generators, new energy units, reactive power compensation devices, transformers, and basic grid parameters and operating status within the power grid.

[0072] More specifically, the conventional generator data includes the upper and lower limits of reactive power output of conventional generating units; the new energy generating unit data includes the current active power output, power factor or rated apparent power, and the upper and lower limits of reactive power output calculated based on its current operating status; the reactive power compensation device data includes the upper and lower limits of reactive power output of the reactive power compensation device (such as a static var generator SVG) located at the grid connection point of the new energy generating unit, as well as the single-unit reactive power capacity, current number of switching groups and maximum number of switching groups of the capacitive reactors or reactors installed in substations at all levels in the power grid; the transformer data includes the current tap position and total number of tap positions of each on-load tap-changing transformer, and the turns ratio or turns ratio adjustment range corresponding to each tap position; the power grid basic parameters and operating status data include network topology and line impedance parameters, active and reactive loads of each node, upper and lower limits of voltage operation of each node (bus), and the specific lower limit of voltage operation at the generator terminals of the new energy generating units.

[0073] S12. Calculate the reactive power output limit of each new energy unit based on its active power output and power factor, so as to determine the corresponding reactive power adjustment range.

[0074] More specifically, the formula for calculating the reactive power output limit is as follows:

[0075] (1)

[0076] In equation (1), For the first k Taiwan's renewable energy units' reactive power output limits For the first k The positive contributions of Taiwan's new energy power units For the first k The power factor of the new energy unit is preferably 0.95 in this embodiment.

[0077] Therefore, based on the reactive power output limit calculated using formula (1), the reactive power adjustment range of the new energy unit is [- Q k , Q k].

[0078] S13. Construct an optimal power flow optimization model with the objective function of minimizing the deviation between the terminal voltage of new energy generating units and the lower limit of the grid operating voltage. The model uses the power flow equation, adjustable transformer tap constraints, and the number of capacitor switching groups as equality constraints, and the upper and lower limits of reactive power of conventional generating units, reactive power of capacitors, reactive power of new energy generating units, node voltage of non-new energy generating units, and transformer tap positions as inequality constraints.

[0079] More specifically, the expression for the objective function is as follows:

[0080] (2)

[0081] In equation (2), For the first k Taiwan's new energy unit terminal voltage, For the first k Lower limit of operating voltage at the generator terminals of new energy power units in Taiwan S e It is a collection of new energy generating units in the power grid.

[0082] The expression for the power flow equation is as follows:

[0083] (3)

[0084] In equation (3), and The first The active and reactive power of a conventional generating unit and For separate nodes The active and reactive power of the load, For nodes and The electrical conductance between them For nodes and The susceptance between them.

[0085] The expression for the tap constraint of the adjustable transformer is as follows:

[0086] (4)

[0087] In equation (4), For transformer k ij The corresponding values ​​for each tap position. m Its total gears, S T This is a collection of adjustable voltage transformers.

[0088] The expression for the constraint on the number of capacitive reactor switching groups is as follows:

[0089] (5)

[0090] In equation (5), For capacitor Q Ci The corresponding reactive power output values ​​for each group m Its total number of groups, S C It is a set of switchable capacitive reactors.

[0091] The inequality constraints are as follows:

[0092] (6)

[0093] (7)

[0094] (8)

[0095] (9)

[0096] (10)

[0097] In equations (6)-(10), , and The first The reactive power of a conventional generating unit and its upper and lower limits. , and For the first i The reactive power and its upper and lower limits of the capacitive reactor at each node. , and For the first i The reactive power of Taiwan's new energy generating units and its upper and lower limits. , and These refer to the voltage and its upper and lower limits at all nodes in the power grid except for the generator terminals of new energy generating units. , and For the first ij Each transformer tap and its upper and lower limits.

[0098] S14. Solve the optimal power flow optimization model to obtain the adjustment values ​​of each adjustable resource in the power grid when the terminal voltage of the new energy generating unit is adjusted to the lower limit of the power grid operating voltage, and adjust the terminal voltage of the new energy generating unit to the lower limit of the power grid operating voltage accordingly.

[0099] Specifically, step S2 includes:

[0100] S21, calculate a new energy multi-station short circuit ratio under an adjusted power grid operation mode;

[0101] S22, define a new energy unit with a new energy multi-station short circuit ratio lower than a preset threshold value as a candidate weak new energy unit;

[0102] S23, perform line N-1 or N-2 line outage fault simulation on lines in a point near area of the candidate weak new energy unit;

[0103] S24, if there is a new energy unit with a terminal voltage lower than a low voltage ride through threshold value after the line outage fault simulation, the new energy unit is determined as a weak new energy unit with a repeated low penetration risk, and the corresponding fault is defined as a key fault.

[0104] Specifically, the preset threshold value is 3.0.

[0105] Specifically, step S3 comprises:

[0106] S31, obtaining a current value, an upper limit and a lower limit of a low voltage ride through threshold value and an active current control value of the weak new energy unit;

[0107] S32, keeping the active current control value unchanged, taking the minimum value of the low voltage ride through threshold value as the starting point, the current value as the end point, and increasing by a preset first step length, to generate a first number of low voltage ride through threshold value adjustment schemes;

[0108] S33, keeping the low voltage ride through threshold value unchanged, taking the current value of the active current control value as the starting point, the maximum value as the end point, and increasing by a preset second step length, to generate a second number of active current control value adjustment schemes;

[0109] S34, the first number of adjustment schemes and the second number of adjustment schemes jointly constitute the control parameter candidate adjustment scheme set.

[0110] Specifically, the preset first step length and / or the preset second step length is 0.1.

[0111] Specifically, step S4 comprises:

[0112] S41, under the adjusted power grid operation mode, each scheme in the candidate adjustment scheme set is subjected to simulation analysis under the key fault;

[0113] S42, a scheme that can make the new energy unit not repeatedly enter and exit the low voltage ride through state after simulation analysis is defined as an effective control parameter adjustment scheme.

[0114] S43, according to the low voltage ride through threshold value of the effective control parameter adjustment scheme and the adjustment value of the active current control value and the corresponding weight value, the comprehensive target value of each effective control parameter adjustment scheme is calculated, and the calculation formula is as follows:

[0115] (11)

[0116] In formula (11), is the comprehensive target value of the first i effective control parameter adjustment scheme, is the adjustment amount of the active current control value of the first i effective control parameter adjustment scheme, is the adjustment amount of the low voltage ride through threshold value of the first i effective control parameter adjustment scheme, , respectively, the weight value of the active current control value adjustment amount and the low voltage ride through threshold value adjustment amount, the comprehensive weighting method combining subjective weighting method and objective weighting method is adopted to determine in the embodiment;

[0117] S44, the effective control parameter adjustment scheme with the smallest comprehensive target value is determined as the optimal adjustment scheme.

[0118] Embodiment two:

[0119] As shown in Figure 2 , the embodiment provides a control parameter optimization system for suppressing repeated low penetration of new energy units, which is used to realize the control parameter optimization method as described in embodiment one, and includes:

[0120] A voltage adjustment module is configured to adjust the terminal voltage of the new energy unit in the power grid to the lower limit of the power grid operating voltage.

[0121] A weak unit identification module is configured to identify weak new energy units with repeated low penetration risk based on the adjusted power grid operating mode.

[0122] A candidate scheme generation module is configured to generate a set of control parameter candidate adjustment schemes for the weak new energy units.

[0123] An optimal scheme determination module is configured to determine an optimal adjustment scheme for the control parameters of the new energy units from the set of candidate adjustment schemes.

[0124] Embodiment three:

[0125] As shown in Figure 3 , the embodiment provides an electronic device, which can include at least one processor, at least one network interface, a user interface, a memory, and at least one communication bus.

[0126] The communication bus can be used to realize the connection and communication of the above-mentioned components.

[0127] The user interface can include a key, and the optional user interface can further include a standard wired interface, a wireless interface.

[0128] The network interface can include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, etc.

[0129] The processor can include one or more processing cores. The processor connects various parts in the entire electronic device through various interfaces and lines, executes various functions of the electronic device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory. Optionally, the processor can be implemented in at least one of the hardware forms of DSP, FPGA, PLA. The processor can integrate one or a combination of CPU, GPU and modem, etc. Among them, the CPU mainly processes the operating system, user interface and application program, etc.; the GPU is responsible for rendering and drawing the content required to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem can also not be integrated into the processor, but be realized by a separate chip.

[0130] The memory can include RAM and ROM. Optionally, the memory includes a non-transitory computer readable medium. The memory can be used to store instructions, programs, codes, code sets or instruction sets. The memory can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playing function, image playing function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory can also be at least one storage device located away from the above-mentioned processor. The memory as a computer storage medium can include an operating system, a network communication module, a user interface module and an optimization application. The processor can be used to call the optimization application stored in the memory, and execute the steps of the control parameter optimization method mentioned in the above-mentioned embodiments.

[0131] Embodiment four:

[0132] The embodiment provides a computer readable storage medium, which stores instructions, when the instructions run on a computer or a processor, the computer or the processor executes the above-mentioned Figure 1The steps of one or more of the embodiments shown. The various constituent modules of the electronic device described above, if implemented in the form of software function units and sold or used as independent products, can be stored in the computer readable storage medium.

[0133] In the above embodiments, all or part can be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transmitted by the computer readable storage medium. The computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer readable storage medium can be any available medium that a computer can access or a data storage device such as a server, data center, etc. that includes one or more available media sets. The available media can be magnetic media (for example, floppy disk, hard disk, magnetic tape), optical media (for example, digital versatile disc (DVD)), or semiconductor media (for example, solid state disk (SSD)) and the like.

[0134] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by a computer program to instruct related hardware, which can be stored in a computer readable storage medium. The program can include the processes of the above-mentioned embodiments when executed. The storage medium includes ROM, RAM, magnetic or optical disk, and various program code storage media. In the case of no conflict, the technical features in the embodiments and the embodiments can be combined arbitrarily.

[0135] It should be noted that for the above-mentioned method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the order of the described actions, because according to the present application, certain steps can be performed in other order or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0136] In the above-described embodiments, the description of each embodiment is focused on a certain aspect, and the part not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0137] The above descriptions are merely exemplary embodiments of the present application, but cannot limit the scope of the present application. Any equivalent changes and modifications made according to the teachings of the present application shall still fall within the scope of the present application. Any implementation of the present application will be readily apparent to those skilled in the art in view of the disclosure herein and practice of the present application. The present application is intended to cover any variations, uses, or adaptive changes of the present application following the general principles thereof and including those falling within the prior art. The scope of the present application should be defined by the claims and their equivalents, and the scope of the present application should be limited by the claims and their equivalents.

Claims

1. A method for optimizing control parameters for inhibiting repeated low penetration of a new energy unit, characterized in that, The method comprises the steps of: S1, constructing and solving an optimal power flow model with the objective function of minimizing the deviation of the terminal voltage of the new energy unit from the lower limit of the operating voltage of the power grid, obtaining the adjustment value of each adjustable resource in the power grid, and adjusting the terminal voltage of the new energy unit in the power grid to the lower limit of the operating voltage of the power grid; S2, based on the adjusted operation mode of the power grid, calculating the short-circuit ratio of the new energy multi-station, and combining the line outage fault simulation of the near area of the new energy collection point, identifying the weak new energy unit and the corresponding key fault which exist the risk of repeated low penetration from all new energy units in the power grid; S3, for the weak new energy unit, by respectively and independently adjusting the low voltage ride through threshold and the active current control value during the low voltage ride through, a candidate adjustment scheme set of control parameters is generated; S4, for each scheme in the candidate adjustment scheme set, the key fault is applied in the simulation for verification, the effective scheme which can avoid repeated low penetration is screened out, and the optimal adjustment scheme is determined from the effective scheme according to the principle of minimizing the weighted comprehensive target value of the control parameter adjustment amount.

2. The control parameter optimization method for suppressing repeated low penetration of a new energy unit according to claim 1, characterized in that, Step S1 comprises: S11, obtaining the data of conventional generators, new energy unit data, reactive power compensation device data, transformer data, power grid basic parameter and operation state data in the power grid; S12, according to the active power output and power factor of each new energy unit, the reactive power output limit value is calculated to determine the corresponding reactive power adjustment range; S13, constructing an optimal power flow optimization model, taking the objective function of minimizing the deviation of the terminal voltage of the new energy unit from the lower limit of the operating voltage of the power grid, taking the power flow equation, the tap constraint of adjustable voltage transformer, and the constraint of the number of switched capacitors as the equality constraint, taking the upper and lower limits of the reactive power of conventional units, the reactive power of capacitors, the reactive power of new energy units, the node voltage of non-new energy units and the transformer tap as the inequality constraint; S14, solving the optimal power flow optimization model, obtaining the adjustment value of each adjustable resource in the power grid when the terminal voltage of the new energy unit is adjusted to the lower limit of the operating voltage of the power grid, and adjusting the terminal voltage of the new energy unit to the lower limit of the operating voltage of the power grid.

3. The control parameter optimization method for suppressing repeated low penetration of a new energy unit according to claim 2, characterized in that, Step S2 comprises: S21, calculating the short-circuit ratio of the new energy multi-station under the adjusted operation mode of the power grid; S22, defining the new energy unit with the short-circuit ratio of the new energy multi-station lower than the preset threshold value as a candidate weak new energy unit; S23, performing line N-1 or N-2 line outage fault simulation on the lines near the candidate weak new energy unit collection point; S24, if there is a new energy unit terminal voltage lower than its low voltage ride through threshold after the line outage fault simulation, the new energy unit is determined as a weak new energy unit with repeated low penetration risk, and the corresponding fault is defined as a key fault.

4. The control parameter optimization method for suppressing repeated low penetration of new energy units according to claim 3, characterized in that: The preset threshold value is 3.

0.

5. The control parameter optimization method for suppressing repeated low penetration of a new energy unit according to claim 4, characterized in that, Step S3 comprises: S31, obtaining the current value, upper limit and lower limit of the low voltage ride through threshold and active current control value of the weak new energy unit. S32, keep the active current control value unchanged, starting from the minimum value of the low voltage ride through threshold, ending at the current value, increasing by a preset first step, to generate a first number of low voltage ride through threshold adjustment schemes; S33, keep the low voltage ride through threshold unchanged, starting from the current value of the active current control value, ending at the maximum value, increasing by a preset second step, to generate a second number of active current control value adjustment schemes; S34, the first number of adjustment schemes and the second number of adjustment schemes together constitute the control parameter candidate adjustment scheme set.

6. The control parameter optimization method for inhibiting repeated low penetration of new energy units according to claim 5, characterized in that: The preset first step and / or the preset second step is 0.

1.

7. The control parameter optimization method for suppressing repeated low penetration of a new energy unit according to claim 6, characterized in that, Step S4 includes: S41, under the adjusted power grid operating mode, each scheme in the candidate adjustment scheme set is subjected to simulation analysis under the key fault; S42, the scheme that can make the new energy unit not repeatedly enter and exit the low voltage ride through state after simulation analysis is defined as an effective control parameter adjustment scheme; S43, according to the adjustment value of the low voltage ride through threshold and the active current control value of the effective control parameter adjustment scheme and the corresponding weight value, the comprehensive target value of each effective control parameter adjustment scheme is calculated; S44, the effective control parameter adjustment scheme with the smallest comprehensive target value is determined as the optimal adjustment scheme.

8. A control parameter optimization system for inhibiting repeated low penetration of a new energy unit, characterized in that, For implementing the control parameter optimization method according to any one of claims 1 to 7, comprising: a voltage adjustment module for adjusting the terminal voltage of the new energy unit in the power grid to the lower limit of the power grid operating voltage; a weak unit identification module for identifying the weak new energy unit with repeated low penetration risk based on the adjusted power grid operating mode; a candidate scheme generation module for generating a control parameter candidate adjustment scheme set of the weak new energy unit; an optimal scheme determination module for determining the optimal adjustment scheme of the new energy unit control parameter from the candidate adjustment scheme set.

9. A computer device comprising a memory, a processor and a computer program, characterized in that The computer program is executed by the processor to implement the control parameter optimization method according to any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the control parameter optimization method according to any one of claims 1 to 7.

Images