New energy control parameter optimization method considering power angle stability and transient overvoltage

Abstract

The invention discloses a new energy control parameter optimization method considering power angle stability and transient overvoltage, and relates to the technical field of power system operation optimization, and the method comprises the steps: collecting historical data, and carrying out load flow calculation and static and transient stability calculation to obtain calculation data; constructing a new energy control parameter optimization model considering system power angle stability and transient overvoltage according to the calculation data; and solving the optimization model by adopting an atomic orbit search algorithm based on an electron motion law according to the optimization model, and calculating an optimal new energy control parameter. According to the method, the transient overvoltage and the system power angle stability are comprehensively considered, a new energy control parameter optimization model based on the power angle stability and the transient overvoltage is provided, the target optimization model is solved in combination with the atomic orbit search algorithm, the optimal wind power control parameters are obtained, and a powerful guarantee is provided for safe and stable operation of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of power system operation optimization, and in particular to a new energy control parameter optimization method taking power angle stability and transient overvoltage into consideration. Background Art

[0002] The development and utilization of new energy has become an inevitable option for the development of electricity. In recent years, the proportion of new energy power generation represented by wind power and photovoltaic power generation in the total installed capacity of power sources has been increasing year by year. At the same time, due to the reverse distribution of new energy resources such as wind power and photovoltaic power generation and load centers in my country, high-voltage direct current transmission technology with large capacity and long-distance transmission as its advantages has become an important means to achieve effective cross-regional resource allocation. With the widespread application of new energy power generation, direct current transmission and other equipment in the power system, the safety and stability of large power grids have received more and more attention.

[0003] The access of power electronic equipment such as new energy and direct current transmission has led to a significant decrease in the short-circuit capacity of the system, and the voltage support strength has been further reduced. When the system is disturbed, it will produce large voltage fluctuations. The commutation failure, DC lockout, and near-zone AC short-circuit faults of the high-voltage direct current transmission system will cause transient overvoltages in the sending-end power grid, restricting the transmission capacity and threatening the safe and stable operation of the system. The hysteresis of the adjustment of the reactive power compensation device of new energy, and the hysteresis of the reactive power control strategy response of new energy with low voltage ride-through capability during the fault period will cause reactive power surplus at the moment of grid voltage recovery. At the same time, the active power and active power recovery rate of the new energy unit during the low-voltage ride-through period will affect the oscillation amplitude of the generator power angle, and even cause power angle instability. Therefore, the present invention considers the comprehensive evaluation index of transient overvoltage and power angle stability, and provides a new energy control parameter optimization method based on multiple power angle stability and transient overvoltage. Summary of the invention

[0004] In view of the problems existing in the existing new energy control parameter optimization method considering power angle stability and transient overvoltage, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is that the hysteresis of the reactive power compensation device of new energy will cause reactive power surplus at the moment of grid voltage recovery. At the same time, the active power and active power recovery rate of the new energy unit during the low-voltage break-through period will affect the oscillation amplitude of the generator power angle and even cause power angle instability.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In the first aspect, an embodiment of the present invention provides a method for optimizing new energy control parameters taking into account power angle stability and transient overvoltage, which includes collecting historical data, and performing power flow calculations and static and transient stability calculations to obtain calculation data; constructing a new energy control parameter optimization model taking into account system power angle stability and transient overvoltage based on the calculation data; and solving the optimization model based on the optimization model using an atomic orbital search algorithm based on the law of electron motion to calculate the optimal new energy control parameters.

[0008] As a preferred scheme of the method for optimizing new energy control parameters considering power angle stability and transient overvoltage described in the present invention, wherein: the calculation data is obtained by performing power flow calculation and static and transient stability calculation according to the wind-fire bundling system model; the wind-fire bundling system model is expressed as: the sending end is a parallel connection of a thermal power unit and a wind power unit, and then the electric energy is sent into the infinite system in the form of wind-fire bundling through AC and DC transmission lines.

[0009] As a preferred solution of the new energy control parameter optimization method considering power angle stability and transient overvoltage of the present invention, wherein: the control parameters related to the new energy low voltage ride-through process are determined based on the parameter setting of the transient stability calculation, including the active current value during the low voltage ride-through period, the reactive current value during the low voltage ride-through period and the active recovery control; the calculation of the active current value during the low voltage ride-through period is expressed as:

[0010] I PLVRT =k d1 U t +k d2 I P0 +I Pset

[0011] Among them, k d1 Indicates the active current calculation coefficient that is positively correlated with the measured voltage; k d2 Indicates the active current calculation coefficient that is positively correlated with the initial current; I Pset Indicates the fixed setting value of active current; U t Represents the voltage amplitude of the new energy machine; I P0 represents the active current before entering the fault; the calculation of the reactive current value during the low-break period is expressed as:

[0012] I QLVRT =k q1 (U Lin -U t )+k q2 I Q0 +I Qset

[0013] Among them, k q1 Indicates the reactive current calculation coefficient which is positively correlated with the measured voltage change; k q2Represents the reactive current calculation coefficient which is positively correlated with the initial current; I Qset Indicates the fixed setting value of reactive current; U Lin Indicates the threshold voltage for new energy to enter the low voltage state; U t Represents the voltage amplitude of the new energy machine; I Q0 represents the reactive current before the fault; the active power recovery control adopts a fixed slope k p Take control.

[0014] As a preferred solution of the method for optimizing the control parameters of new energy sources considering power angle stability and transient overvoltage described in the present invention, an objective function is constructed based on the control parameters related to the low voltage ride-through process of new energy sources, which is expressed as:

[0015] minG=g1+ζg2

[0016] g1=max[U imax ]

[0017] g2=max[δ jmax ]

[0018] Among them, U imax Indicates the transient overvoltage peak value of the new energy station; δ jmax Indicates the peak power angle of the thermal power unit.

[0019] As a preferred solution of the new energy control parameter optimization method considering power angle stability and transient overvoltage of the present invention, wherein: based on the objective function, the constraint conditions are determined, including equality constraints, inequality constraints and control variable constraints; the equality constraints are power flow balance equations, and the inequality constraints are actual power constraints of generators; the constraint condition formula is expressed as:

[0020]

[0021] Among them, P Gi , P di , Q Gi , Q di , U i Respectively represent the active output, active load, reactive input, reactive load and node voltage of node i; G ij , B ij ,θ ij Represents the conductance, susceptance and phase angle difference of branch ij; Indicates the lower and upper limits of active output of generator node i; Represents the lower and upper limits of reactive power output of generator node i; N G Indicates the number of generator nodes.

[0022] As a preferred solution of the new energy control parameter optimization method considering power angle stability and transient overvoltage described in the present invention, wherein: the atomic orbital search algorithm based on the law of electron motion solves the optimization model, including: setting the voltage to be measured, power angle data, and wind power control parameters to be optimized; algorithm initialization, setting the parameters of the atomic orbital search algorithm, and the upper and lower limits of the wind power control parameters to be optimized; writing the initial position of the electron into the wind power control card in sequence for temporary stability calculation and reading the result data, calculating and saving the objective function value and the electron position; determining the binding energy and binding state of each level, recording the average value of the electron position in each layer as the binding state, and the binding energy is the average value of each individual objective function value; updating the electron state according to the update strategy, introducing the photon rate PR to represent the probability of photons acting on electrons, and generating a uniformly distributed random number φ for each electron, the random number is in the range of (0,1); further judging whether the maximum number of iterations Gen has been reached, determining the stop condition, and outputting the global optimal value and the optimal low-penetration control parameter.

[0023] As a preferred solution of the new energy control parameter optimization method considering power angle stability and transient overvoltage of the present invention, wherein: based on the relationship between the photon rate PR and the random number φ, the corresponding update formula is used to update the candidate solution position, including: if φ ≥ PR and the energy level of the candidate solution in a certain layer is higher than the binding energy of the layer, that is, The position update formula is expressed as:

[0024]

[0025] in, is the updated position and current position of the candidate solution of the kth layer; α r , β r , γ r is a random number between [0,1]; LE is the global optimal position; B S is the binding state corresponding to the candidate solution; if φ≥PR and the energy level of the candidate solution in a certain layer is lower than the binding energy of that layer, then The position update formula is expressed as:

[0026]

[0027] Among them, LE k It is the electron with the lowest energy level in the kth layer; is the combined state corresponding to the candidate solution of the kth layer; if φ<PR, the position update is expressed as:

[0028]

[0029] Among them, u r is a vector of uniformly distributed random numbers in the range [0,1].

[0030] In the second aspect, an embodiment of the present invention provides a new energy control parameter optimization system that takes power angle stability and transient overvoltage into consideration, which includes: a collection module for collecting historical data, and performing power flow calculations and static and transient stability calculations to obtain calculation data; an optimization module for constructing a new energy control parameter optimization model that takes system power angle stability and transient overvoltage into consideration based on the calculation data; a calculation module for solving the optimization model based on the optimization model using an atomic orbital search algorithm based on the laws of electron motion, and calculating the optimal new energy control parameters.

[0031] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, it implements any step of the above-mentioned method for optimizing new energy control parameters considering power angle stability and transient overvoltage.

[0032] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned method for optimizing new energy control parameters considering power angle stability and transient overvoltage is implemented.

[0033] The beneficial effect of the present invention is that the present invention comprehensively considers transient overvoltage and system power angle stability, provides a new energy control parameter optimization model based on power angle stability and transient overvoltage, combines the atomic orbital search algorithm to solve the target optimization model, and obtains the optimal wind power control parameters, providing a strong guarantee for the safe and stable operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0035] Figure 1 A flow chart of a new energy control parameter optimization method considering power angle stability and transient overvoltage;

[0036] Figure 2 This is the model diagram of the wind and fire bundling system. Figure 3 is the electron probability density diagram. DETAILED DESCRIPTION

[0037] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0038] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0039] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0040] Example 1

[0041] Reference Figure 1 to Figure 3 , which is the first embodiment of the present invention, provides a new energy control parameter optimization method considering power angle stability and transient overvoltage, including:

[0042] S1: Collect historical data, and perform power flow calculations and static and transient stability calculations to obtain calculation data.

[0043] The historical data on the risks of power angle instability and transient overvoltage caused by failures in the AC / DC transmission system of wind-fire bundling are collected, and the historical data are subjected to power flow calculation and static and transient stability calculation according to the wind-fire bundling system model to obtain the calculation data.

[0044] like Figure 2 As shown, the sending end is a parallel connection of thermal power units and wind power units, and then the electric energy is sent to the infinite system in the form of wind-fire bundles through AC and DC transmission lines.

[0045] The wind-fire bundling system model refers to a model in which wind power and thermal power transmit electricity through the same transmission line. The infinite system refers to an idealized power system model in which the power supply capacity is infinite relative to the user load, and the voltage and frequency are accurately simulated to remain constant. In this way, the optimization research on the relevant control parameters of the wind-fire bundling model is not affected by the receiving system.

[0046] S2: Construct a new energy control parameter optimization model based on the calculated data, taking into account system power angle stability and transient overvoltage.

[0047] Based on the parameter setting of transient stability calculation, the relevant control parameters of the new energy low voltage ride-through process are determined, including the active current value during the low voltage ride-through period, the reactive current value during the low voltage ride-through period and the active power recovery control;

[0048] The calculation of the active current value during the low-voltage wear period is expressed as:

[0049] I PLVRT =k d1 U t +k d2 I P0 +I Pset

[0050] Among them, k d1 Indicates the active current calculation coefficient that is positively correlated with the measured voltage; k d2 Indicates the active current calculation coefficient that is positively correlated with the initial current; I Pset Indicates the fixed setting value of active current; U t Represents the voltage amplitude of the new energy machine; I P0 Indicates the active current before entering the fault;

[0051] The calculation of reactive current value during low-voltage wear-through is expressed as:

[0052] I QLVRT =k q1 (U Lin -U t )+k q2 I Q0 +I Qset

[0053] Among them, k q1 Indicates the reactive current calculation coefficient which is positively correlated with the measured voltage change; k q2 Represents the reactive current calculation coefficient which is positively correlated with the initial current; I Qset Indicates the fixed setting value of reactive current; U Lin Indicates the threshold voltage for new energy to enter the low voltage state; U t Represents the voltage amplitude of the new energy machine; I Q0 Indicates the reactive current before entering the fault;

[0054] Furthermore, the active power recovery control adopts a constant slope k p To exercise control;

[0055] Active power control during low voltage ride-through includes: specifying active current value, specifying active current as a percentage of initial current, specifying active power value, and specifying active power as a percentage of initial power.

[0056] In order to prevent the inverter from overcurrent, new energy models generally adopt current control during low voltage ride-through.

[0057] The active power output during low voltage ride-through and the active power recovery rate after the fault is over play a decisive role in the characteristics of new energy.

[0058] The objective function is constructed based on the relevant control parameters of the new energy low voltage ride-through process and is expressed as:

[0059] minG=g1+ζg2

[0060] g1=max[U imax ]

[0061] g2=max[δ jmax ]

[0062] Among them, U imax Indicates the transient overvoltage peak value of the new energy station; δ jmax Indicates the peak power angle of the thermal power unit.

[0063] The constraint conditions are determined according to the objective function, including equality constraints, inequality constraints and control variable constraints; the equality constraints are power flow balance equations, and the inequality constraints are actual power constraints of the generators, which are expressed as:

[0064]

[0065] Among them, P Gi , P di , Q Gi , Q di , U i Respectively represent the active output, active load, reactive input, reactive load and node voltage of node i; G ij , B ij ,θ ij Represents the conductance, susceptance and phase angle difference of branch ij; Indicates the lower and upper limits of active output of generator node i; Represents the lower and upper limits of reactive power output of generator node i; N G Indicates the number of generator nodes.

[0066] S3: According to the optimization model, the atomic orbital search algorithm based on the law of electron motion is used to solve the optimization model and determine the optimal new energy control parameters.

[0067] The atomic orbital search algorithm based on the laws of electron motion solves the optimization model, including:

[0068] Set the voltage to be measured, power angle data, and wind power control parameters to be optimized;

[0069] Initialize the algorithm, set the parameters of the atomic orbital search algorithm, and the upper and lower limits of the wind power control parameters to be optimized;

[0070] The initial positions of the electrons are sequentially written into the wind power control card for temporary stability calculation and the result data is read, and the objective function value and the electron position are calculated and saved;

[0071] Determine the binding energy and binding state of each level, record the average value of the electron position in each layer as the binding state, and the binding energy as the average value of each individual objective function;

[0072] The space around the nucleus is set to n virtual layers. The number of virtual layers divides the entire search space into multiple parts. The probability density function (PDF) is used to distribute candidate solutions in the virtual layers. The electron probability density diagram is as follows: Figure 3 As shown in Figure 2, the electron with the lowest energy level in each virtual layer is considered to be the optimal candidate solution for that layer, and the electron with the lowest energy level in the optimal candidate solutions of each layer is considered to be the global optimal solution.

[0073] The binding state and binding energy corresponding to each virtual layer:

[0074]

[0075] In the formula, is the k-th layer binding state and binding energy; is the rth candidate solution in the kth virtual layer; p is the total number of candidate solutions in the kth virtual layer; n is the maximum number of virtual layers; is the objective function value of the rth candidate solution in the kth virtual layer.

[0076] Atomic binding state and binding energy:

[0077]

[0078] In the formula, B S ,B E is the binding state and binding energy of the atom; X r is the rth candidate solution in the atom; E r is the objective function value of the rth candidate solution in the atom; m is the number of candidate solutions in the search space.

[0079] Update the electronic state according to the update strategy, introduce the photon rate PR to represent the probability of photons acting on electrons, and generate a uniformly distributed random number φ for each electron, which is in the range of (0,1);

[0080] Further judge whether the maximum number of iterations Gen is reached, determine the stop condition, and output the global optimal value and the optimal low-penetration control parameters.

[0081] Based on the relationship between the photon rate PR and the random number φ, the candidate solution position is updated using a corresponding update formula, including:

[0082] If φ≥PR and the energy level of the candidate solution at a certain layer is higher than the binding energy of that layer, then The position update formula is expressed as:

[0083]

[0084] in, is the updated position and current position of the candidate solution of the kth layer; α r , β r , γ r is a random number between [0,1]; LE is the global optimal position; B S is the binding state corresponding to the candidate solution;

[0085] If φ≥PR and the energy level of the candidate solution at a certain layer is lower than the binding energy of that layer, then The position update formula is expressed as:

[0086]

[0087] Among them, LE k It is the electron with the lowest energy level in the kth layer; is the binding state corresponding to the candidate solution of the kth layer;

[0088] If φ<PR, the position update is expressed as:

[0089]

[0090] Among them, u r is a vector of uniformly distributed random numbers in the range [0,1].

[0091] In summary, the present invention comprehensively considers transient overvoltage and system power angle stability, provides a new energy control parameter optimization model based on power angle stability and transient overvoltage, combines the atomic orbital search algorithm to solve the target optimization model, and obtains the optimal wind power control parameters, providing a strong guarantee for the safe and stable operation of the system.

[0092] Example 2

[0093] Reference Figure 1 Based on the first embodiment, this embodiment further provides a new energy control parameter optimization system considering power angle stability and transient overvoltage, including:

[0094] The collection module is used to collect historical data and perform power flow calculations and static and transient stability calculations to obtain calculation data;

[0095] The optimization module is used to construct a new energy control parameter optimization model that takes into account system power angle stability and transient overvoltage based on the calculated data;

[0096] The calculation module is used to solve the optimization model according to the optimization model using an atomic orbital search algorithm based on the law of electron motion, and calculate the optimal new energy control parameters.

[0097] This embodiment also provides a computer device, which is suitable for the case of a method for optimizing control parameters of new energy sources considering power angle stability and transient overvoltage, and includes a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the method for optimizing control parameters of new energy sources considering power angle stability and transient overvoltage as proposed in the above embodiment.

[0098] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0099] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for optimizing the control parameters of new energy sources taking into account power angle stability and transient overvoltage as proposed in the above embodiment is implemented.

[0100] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0101] Example 3

[0102] On the basis of the previous two embodiments, this embodiment provides a new energy control parameter optimization method considering power angle stability and transient overvoltage. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0103] Taking a 500kV power grid at the sending end of my country as an example, considering that the proportion of wind power in the total power source is between 10% and 50%, the current mode flow calculation and static and transient stability calculation are completed. In the atomic orbital search algorithm, the population number is set to 15 and the genetic evolution generation is 10. The atomic orbital search algorithm based on the law of electron motion is used to solve the target optimization model and output the optimal wind power control parameters.

[0104] Wind power original control parameter k d2 =0.45,k p =2, after optimization by the new energy control parameter optimization method considering power angle stability and transient overvoltage, the results are shown in Table 1, and the optimal control parameter is k d2 =0.79,k p =2.17, the transient overvoltage at the machine end of each wind farm was significantly reduced, and no power angle instability occurred.

[0105] Table 1 Optimization effect of new energy control parameters

[0106]

[0107] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A new energy control parameter optimization method considering power angle stability and transient overvoltage, characterized by: include, Collect historical data, and perform power flow calculations and static and transient stability calculations to obtain calculation data; Based on the calculated data, a new energy control parameter optimization model considering system power angle stability and transient overvoltage is constructed; According to the optimization model, the atomic orbital search algorithm based on the law of electron motion is used to solve the optimization model and calculate the optimal new energy control parameters.

2. The method for optimizing new energy control parameters considering power angle stability and transient overvoltage as claimed in claim 1, characterized in that: The calculation data is obtained by performing power flow calculation and static and transient stability calculation based on the wind-fire bundling system model; The wind-fire bundling system model is represented as follows: the sending end is a parallel connection of a thermal power unit and a wind power unit, and then the electric energy is sent to the infinite system in the form of wind-fire bundling through AC and DC transmission lines.

3. The method for optimizing new energy control parameters considering power angle stability and transient overvoltage as claimed in claim 2, characterized in that: Determine the control parameters related to the low voltage ride-through process of the new energy source based on the parameter setting of the transient stability calculation, including the active current value during the low voltage ride-through period, the reactive current value during the low voltage ride-through period and the active power recovery control; The calculation of the active current value during the low-break period is expressed as: I PLVRT =k d1 U t +k d2 I P0 +I Pset Among them, k d1 Indicates the active current calculation coefficient that is positively correlated with the measured voltage; k d2 Indicates the active current calculation coefficient that is positively correlated with the initial current; I Pset Indicates the fixed setting value of active current; U t Represents the voltage amplitude of the new energy machine; I P0 Indicates the active current before entering the fault; The calculation of the reactive current value during the low-break period is expressed as: AND QLVRT =k q1 (IN Lin -IN t )+k q2 AND Q0 +I Qset Among them, k q1 Indicates the reactive current calculation coefficient which is positively correlated with the measured voltage change; k q2 Represents the reactive current calculation coefficient which is positively correlated with the initial current; I Qset Indicates the fixed setting value of reactive current; U Lin Indicates the threshold voltage for new energy to enter the low voltage state; U t Represents the voltage amplitude of the new energy machine; I Q0 Indicates the reactive current before entering the fault; The active power recovery control adopts a constant slope k p Take control.

4. The method for optimizing new energy control parameters considering power angle stability and transient overvoltage as claimed in claim 3, characterized in that: The objective function is constructed based on the relevant control parameters of the new energy low voltage ride-through process and is expressed as: min G=g1+ζg2 g1=max[U imax ] g2=max[δ jmax ] Among them, U imax Indicates the transient overvoltage peak value of the new energy station; δ jmax Indicates the peak power angle of the thermal power unit.

5. The method for optimizing new energy control parameters considering power angle stability and transient overvoltage as claimed in claim 4, characterized in that: Determining constraint conditions based on the objective function, including equality constraints, inequality constraints and control variable constraints; the equality constraints are power flow balance equations, and the inequality constraints are actual power constraints of generators; The constraint formula is expressed as: Among them, P Gi , P di , Q Gi , Q di , U i Respectively represent the active output, active load, reactive input, reactive load and node voltage of node i; G ij , B ij ,θ ij Represents the conductance, susceptance and phase angle difference of branch ij; Indicates the lower and upper limits of active output of generator node i; Represents the lower and upper limits of reactive power output of generator node i; N G Indicates the number of generator nodes.

6. The method for optimizing the control parameters of new energy sources considering power angle stability and transient overvoltage as claimed in claim 5, characterized in that: The atomic orbital search algorithm based on the laws of electron motion solves the optimization model, including: Set the voltage to be measured, power angle data, and wind power control parameters to be optimized; Initialize the algorithm, set the parameters of the atomic orbital search algorithm, and the upper and lower limits of the wind power control parameters to be optimized; The initial positions of the electrons are sequentially written into the wind power control card for temporary stability calculation and the result data is read, and the objective function value and the electron position are calculated and saved; Determine the binding energy and binding state of each level, record the average value of the electron position in each layer as the binding state, and the binding energy as the average value of each individual objective function; Update the electronic state according to the update strategy, introduce the photon rate PR to represent the probability of photons acting on electrons, and generate a uniformly distributed random number φ for each electron, which is in the range of (0,1); Further judge whether the maximum number of iterations Gen is reached, determine the stop condition, and output the global optimal value and the optimal low-penetration control parameters.

7. The method for optimizing new energy control parameters considering power angle stability and transient overvoltage as claimed in claim 6, characterized in that: Based on the relationship between the photon rate PR and the random number φ, the candidate solution position is updated using a corresponding update formula, including: If φ≥PR and the energy level of the candidate solution at a certain layer is higher than the binding energy of that layer, then The position update formula is expressed as: in, is the updated position and current position of the candidate solution of the kth layer; α r , β r , γ r is a random number between [0,1]; LE is the global optimal position; B S is the binding state corresponding to the candidate solution; If φ≥PR and the energy level of the candidate solution at a certain layer is lower than the binding energy of that layer, then The position update formula is expressed as: Among them, LE k It is the electron with the lowest energy level in the kth layer; is the binding state corresponding to the candidate solution of the kth layer; If φ<PR, the position update is expressed as: Among them, u r is a vector of uniformly distributed random numbers in the range [0,1].

8. A new energy control parameter optimization system considering power angle stability and transient overvoltage, based on the new energy control parameter optimization method considering power angle stability and transient overvoltage as described in any one of claims 1 to 7, characterized in that: include, The collection module is used to collect historical data and perform power flow calculations and static and transient stability calculations to obtain calculation data; The optimization module is used to construct a new energy control parameter optimization model that takes into account system power angle stability and transient overvoltage based on the calculated data; The calculation module is used to solve the optimization model according to the optimization model using an atomic orbital search algorithm based on the law of electron motion, and calculate the optimal new energy control parameters.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for optimizing the control parameters of new energy taking into account power angle stability and transient overvoltage as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for optimizing the control parameters of new energy sources taking into account power angle stability and transient overvoltage as described in any one of claims 1 to 7 are implemented.

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