A power system safety and stability control method, system, device and medium

Abstract

The application discloses a power system safety and stability control method, system, device and medium, first, the power system safety and stability control index is constructed by analyzing the new energy output characteristics; secondly, the safety and stability control model is established by taking the safety and stability control index and the minimum load shedding amount as the target and the operation risk as the constraint; then, the contraction surrounding prey and spiral bubble net attack link in the whale algorithm are improved; finally, the improved whale algorithm is used for solving the safety and stability control model, and the post-fault low-frequency load shedding strategy generation is realized. The application suppresses the instability and safety hidden danger of the power system caused by the new energy output fluctuation, ensures the generation of the low-frequency load shedding strategy of the power system when the power system encounters a fault or new energy fluctuation, and thus ensures the safety and stability of the power system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of safe operation of power systems, and in particular to a power system safety and stability control method, system, device and medium. BACKGROUND

[0002] In order to meet the needs of safe operation of new energy systems, it is urgent to establish a safety and stability control strategy generation model suitable for the configuration of the diversity and complexity of new energy system power flow and stability mode.

[0003] The existing methods for solving the safety and stability control model can be divided into physical model method, data-driven method, physical data fusion method and artificial intelligence algorithm. Among them: for physical modeling, the power system model is used to simulate the power flow and stability characteristics of the new energy system, and through the establishment of a detailed mathematical model, power flow calculation and transient stability analysis are carried out to provide a basis for stability control strategy, but the physical model of the new energy system has high complexity, numerous parameters and difficult to accurately describe the dynamic characteristics. For the data-driven method, machine learning or deep learning algorithms are used to learn the power flow and stability characteristics of the system from historical data, and control strategies are generated through data training, but it depends on high-quality historical data, and the data volume is large and the annotation difficulty is high. For the data fusion method, the physical model and the data-driven model are combined, and the theoretical guidance provided by the physical model is used to assist the data-driven model in adjustment, but the coupling and coordination between the physical model and the data-driven model are difficult to handle, and the calculation resources and data requirements are high. For the artificial intelligence algorithm, safety, stability and economy are taken as multiple objectives, and the optimal stability control strategy is found through optimization algorithm. In the configuration, different characteristics of new energy are introduced to optimize the control strategy, which can comprehensively consider multiple objectives, achieve balanced optimization, and adapt to different working conditions and requirements. The above researches do not consider the output characteristics of new energy, and a complete stability control index is established according to the output characteristics of new energy.

[0004] In summary, the existing methods have a series of problems of low resource use efficiency. Therefore, how to overcome the uncertainty of new energy output and quickly develop a power system safety and stability control scheme to ensure the safe, stable and economic operation of the power grid has become a very challenging task. SUMMARY

[0005] The present application provides a power system safety and stability control method, system, device and medium for suppressing the instability and safety hazards of the power system caused by new energy output fluctuations, so as to ensure the safety and stability of the power system when encountering faults or new energy fluctuations.

[0006] Therefore, the first aspect of the present application provides a power system safety and stability control method, which comprises:

[0007] The safety and stability control index of the power system is constructed according to the new energy output characteristics, and the safety and stability control index comprises: a frequency deviation index, voltage stability, and frequency response time;

[0008] A safety and stability control model is established with the minimum safety and stability control index and the minimum load shedding amount as targets;

[0009] An improved whale optimization algorithm is used to solve the safety and stability control model to generate a low-frequency load shedding strategy after a fault, wherein the improved method of the improved whale optimization algorithm comprises: improving the contraction surrounding prey and spiral bubble net attack links in the whale optimization algorithm.

[0010] Optionally, the safety and stability control index of the power system is constructed according to the new energy output characteristics, and the safety and stability control index comprises:

[0011] The safety and stability control index of the power system is constructed according to the distributed photovoltaic energy output characteristics and the distributed wind power new energy characteristics.

[0012] Optionally, the expression of the frequency deviation index is:

[0013] ;

[0014] In the formula, is a load rate, is a conventional unit output, is a photovoltaic output, is a system equivalent inertia constant, is a system rated frequency.

[0015] Optionally, the expression of the voltage stability is:

[0016] ;

[0017] In the formula, is a change in node voltage, is a node voltage, is an actual output power of a photovoltaic system, is a power of distributed wind power, is a reference output value.

[0018] Optionally, the expression of the frequency response time is:

[0019] ;

[0020] In the formula, is a frequency response time, is an actual output power of a photovoltaic system, is a power of distributed wind power, is a conventional unit output, and respectively are inertia time constants of new energy and conventional units.

[0021] Optionally, the safety and stability control model is established with the minimum safety and stability control index and the minimum load shedding amount as the target, and the method comprises the following steps:

[0022] Optionally, the safety and stability control model is established by constructing a target function with the minimum safety and stability control index and the minimum load shedding amount as the target, and taking power balance constraints, safety operation risk constraints, static constraints and transient constraints as constraint conditions.

[0023] Optionally, the shrinking surrounding prey and spiral bubble net attack links in the whale algorithm are improved, and the method comprises the following steps:

[0024] Optionally, the shrinking surrounding prey in the whale algorithm is improved by introducing an adaptive inertia weight, and the spiral bubble net attack link is optimized by adding a Lévy flight mechanism.

[0025] The second aspect of the present application provides a power system safety and stability control system, and the system comprises:

[0026] A first construction unit is configured to construct a safety and stability control index of a power system according to a new energy output characteristic, and the safety and stability control index comprises a frequency deviation index, voltage stability and frequency response time.

[0027] A second construction unit is configured to establish a safety and stability control model with the minimum safety and stability control index and the minimum load shedding amount as the target.

[0028] A solution unit is configured to solve the safety and stability control model by using an improved whale algorithm to generate a post-fault low-frequency load shedding strategy, and the improvement method of the improved whale algorithm comprises improving the shrinking surrounding prey and spiral bubble net attack links in the whale algorithm.

[0029] The third aspect of the present application provides a power system safety and stability control device, and the device comprises a processor and a memory:

[0030] The memory is configured to store program code and transmit the program code to the processor.

[0031] The processor is configured to execute the steps of the power system safety and stability control method according to the instructions in the program code.

[0032] The fourth aspect of the present application provides a computer readable storage medium for storing program code, and the program code is used to execute the power system safety and stability control method of the first aspect.

[0033] From the above technical solution can be seen, the present application has the following advantages:

[0034] The power system safety and stability control method provided by the application constructs more accurate power system safety and stability control indexes by analyzing new energy output characteristics, and on this basis, a multi-objective safety and stability control optimization model is established in combination with minimum load shedding amount and operation risk constraints. In view of the deficiencies of the whale algorithm, the "shrinkage surrounding prey" and "spiral bubble net attack" mechanisms are improved, and the global optimization ability of the algorithm is improved. Through the improved algorithm, the generation of the low-frequency load shedding strategy after the fault is successfully realized, and the safety of the power system under fault conditions is enhanced. The application suppresses the instability and safety hazards of the power system caused by new energy output fluctuation, ensures the generation of the low-frequency load shedding strategy when the power system encounters faults or new energy fluctuation, and thus ensures the safety and stability of the power system. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. 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 from these drawings without creative labor.

[0036] Figure 1 A flowchart of the power system safety and stability control method provided by the embodiment of the application is shown in the figure.

[0037] Figure 2 A flowchart of the power system safety and stability control method provided by the embodiment of the application is shown in the figure.

[0038] Figure 3 An improved IEEE39 new type power system provided by the embodiment of the application is shown in the figure.

[0039] Figure 4 The fitness function value under the load shedding of the traditional method and the load shedding of the method of the application is shown in the figure.

[0040] Figure 5 A structure diagram of the power system safety and stability control system provided by the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0041] In order to make the application purposes, features and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings of the embodiments of the present application. Obviously, the following described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0042] Embodiment 1

[0043] Please refer to Figure 1 The power system safety and stability control method provided in the embodiments of the present application comprises:

[0044] Step 101, constructing a safety and stability control index of the power system according to the new energy output characteristics, the safety and stability control index comprising: a frequency deviation index, voltage stability and frequency response time.

[0045] Step 102, establishing a safety and stability control model with the minimum safety and stability control index and the minimum load shedding amount as the target.

[0046] Step 103, solving the safety and stability control model by using an improved whale optimization algorithm to generate a post-fault low-frequency load shedding strategy, wherein the improvement method of the improved whale optimization algorithm comprises: improving the contraction surrounding prey and spiral bubble net attack links in the whale optimization algorithm.

[0047] In one embodiment, step 101 comprises: constructing a safety and stability control index of the power system according to the distributed photovoltaic energy output characteristics and the distributed wind power new energy characteristics, including: a frequency deviation index, voltage stability and frequency response time.

[0048] The expression of the frequency deviation index is:

[0049] ;

[0050] In the formula, is the load rate, is the conventional unit output, is the photovoltaic output, is the system equivalent inertia constant, is the system rated frequency.

[0051] The expression of the voltage stability is:

[0052] ;

[0053] In the formula, is the change of the node voltage, is the node voltage, This represents the actual output power of the photovoltaic system. For the power of distributed wind power, This is a reference output value.

[0054] The expression for frequency response time is:

[0055] ;

[0056] In the formula, For frequency response time, This represents the actual output power of the photovoltaic system. For the power of distributed wind power, To provide power to conventional units, and These are the inertial time constants for new energy and conventional generating units, respectively.

[0057] Regarding step 101, it should be noted that:

[0058] First, we analyze the output characteristics of new energy sources, including: the output characteristics of distributed photovoltaic energy and the characteristics of distributed wind power, among which:

[0059] 1) Analysis of the output characteristics of distributed photovoltaic energy:

[0060] The output of distributed photovoltaic (PV) renewable energy is mainly affected by solar irradiance. Solar irradiance can be approximated as a Beta distribution, and the probability density function of PV output is as follows:

[0061] ;

[0062] In the formula, Contribute to photovoltaic power The probability density function; This refers to the actual output power of the photovoltaic system. This is the system's maximum output. For each of the two parameters of the Beta distribution.

[0063] 2) Analysis of the characteristics of distributed wind power renewable energy:

[0064] This invention uses a log-normal distribution to describe wind speed data, with the specific probability density function being:

[0065] ;

[0066] In the formula, Wind speed The probability density function; Wind speed; The mean of the logarithmic wind speed; The standard deviation of the logarithmic wind speed; is the natural logarithm of wind speed; The wind power output; The cut-in wind speed of the wind turbine; The cut-out wind speed; The rated wind speed; The rated power; The power of the distributed wind power.

[0067] Then, the safety and stability control index of the power system is constructed according to the new energy output characteristics, including:

[0068] The frequency deviation index:

[0069] In order to measure the frequency stability of the system, the frequency deviation as a stability control index:

[0070] ;

[0071] In the formula: The load rate; The conventional unit output; The equivalent inertia constant of the system; The rated frequency of the system.

[0072] The voltage stability index:

[0073] The inverter characteristics of new energy generation have weak support ability for the voltage of the power grid, so the voltage stability index should include the output change of new energy.

[0074] ;

[0075] In the formula: The change of the node voltage, The node voltage, The reference output value.

[0076] The frequency response time index:

[0077] Due to the low inertia of new energy units, the frequency response time will be prolonged, affecting the frequency stability of the system:

[0078] ;

[0079] In the formula, The frequency response time; And The inertia time constant of new energy and conventional units.

[0080] In one embodiment, step 102 includes:

[0081] Objective functions for minimizing safety and stability control indicators and minimizing load shedding are constructed respectively, and safety and stability control models are established with power balance constraints, safe operation risk constraints, static constraints and transient constraints as constraints.

[0082] Regarding step 102, it should be noted that:

[0083] First, objective functions for minimizing the safety and stability control index and the load shedding amount are constructed, including:

[0084] 1) Minimize the quantity of indicators for complete stability control:

[0085] Minimizing the stability control index is to ensure that the system can quickly recover to normal operation under various disturbances. The stability control index is represented as a weighted sum of multiple sub-indicators, specifically:

[0086] ;

[0087] In the formula, Let be represented as random weight coefficients.

[0088] 2) Minimum load shedding:

[0089] To ensure stable system operation even under unbalanced conditions, load shedding is the last resort to guarantee system safety. The goal is to minimize the load shedding amount, and the objective function for load shedding is:

[0090] ;

[0091] In the formula, This represents the total number of nodes in the system that require load shedding. For the first The load shedding amount of each node.

[0092] The objective function, which combines the stability control index and the load shedding rate, is expressed as:

[0093] ;

[0094] Then, the constraints are power balance constraints, safe operation risk constraints, static constraints, and transient constraints, among which:

[0095] 1) Static constraints and transient constraints:

[0096] ;

[0097] In the formula, for The system's center frequency of inertia at any given moment; The minimum frequency used in the calculation; This is the lower limit of the frequency. , respectively the maximum and minimum of the node load; is the cut load node the reduced load; is the lower limit of the system inertia center frequency; is the upper limit of the system inertia center frequency.

[0098] 2) Power balance constraints:

[0099] ;

[0100] wherein: is the output of the i-th conventional generator; is the total output of all new energy; is the power demand of the i-th load; is the system transmission loss.

[0101] 3) Safe operation risk constraints:

[0102] The safe operation of the power system faces various risks from generation output fluctuations, load changes, new energy uncertainties, etc., and the comprehensive operation risk should be controlled within an acceptable range:

[0103] ;

[0104] wherein: is the comprehensive operation risk of the system; , , , represent the risks related to frequency, voltage, power generation and frequency response time respectively; is the maximum comprehensive risk allowed by the system;

[0105] In one embodiment, the steps 103 improve the shrinkage surrounding prey and spiral bubble net attack links in the whale algorithm, including: introducing an adaptive inertia weight to improve the shrinkage surrounding prey in the whale algorithm, and adding a Lévy flight mechanism to optimize the spiral bubble net attack link.

[0106] For step 103, it needs to be noted that:

[0107] The adaptive inertia weight is introduced to improve the shrinkage surrounding prey in the whale algorithm, and the Lévy flight mechanism is added to optimize the spiral bubble net attack link, which specifically includes:

[0108] 1) Introduce an adaptive inertia weight:

[0109] ​To improve the flexibility and dynamics of the shrinkage surrounding stage, an exponential decay mechanism is used instead of linear decay, and an adaptive inertia weight and fuzzy control strategy are introduced, so that the whale individuals have different shrinkage surrounding speeds in different stages, and the weight coefficients controlled by the algorithm The improvements are:

[0110] ;

[0111] In the formula, Exponential decay rate, used to control the shrinkage speed; It is an adaptive inertia weight, which is dynamically adjusted according to the historical performance of the individual, and the specific formula is:

[0112] ;

[0113] In the formula, It is a regulation factor; It is the fitness of the current individual; It is the global optimal fitness value;

[0114] 2) Add Lévy flight mechanism:

[0115] Helical motion is usually continuous and regular, but in order to increase the randomness and globality of exploration, Lévy flight mechanism is added to make the individual jump between local and long distance search, while dynamically adjusting the shrinkage and expansion of the helical path,

[0116] ;

[0117] In the formula, It is a coefficient for controlling the step length of Lévy flight; It is a Lévy distribution; , It is a control parameter of Lévy distribution; It is a random control of search range.

[0118] Finally, the improved whale algorithm is used to solve the security and stability control model, and the low-frequency load shedding strategy after fault is generated, as shown in Figure 2 The specific steps are as follows:

[0119] Step S41, initialize parameters;

[0120] Step S42, calculate the fitness value according to the objective function;

[0121] Step S43, update the global optimal value and optimal position;

[0122] Step S44, shrink and surround the prey;

[0123] In nature, whales can identify prey and surround it. In the algorithm, assuming the current optimal solution is the prey, the whale will update its own position by gradually approaching the optimal solution, and the mathematical model is expressed as:

[0124] ;

[0125] In the formula, is the new position of the whale individual in the th iteration; is the position of the current optimal solution (prey); is a weight coefficient controlled by the algorithm, used to control the amplitude of the shrinking enclosure; it is linearly reduced from 2 to 0, and is used to control the shrinking range is the distance between the whale and the prey; is a random vector; is a random number.

[0126] Step S45, spiral bubble net attack;

[0127] When hunting, whales sometimes approach prey in a spiral path, and the position of the whale is updated through the spiral trajectory, and the mathematical model is expressed as:

[0128] ;

[0129] In the formula, is a constant that defines the shape of the spiral path; is a random number between , used to determine the randomness of the spiral.

[0130] Step S46, determine whether is greater than 1, if greater than 1, proceed to the next step, if less than 1, return to S45;

[0131] Step S47, randomly search for prey;

[0132] In order to balance the local optimization and global search ability of the algorithm, when , the whale will explore new areas by moving away from the optimal solution in some cases, simulating random search in areas far from the prey, and the mathematical model is expressed as:

[0133] ;

[0134] In the formula, is the position of a randomly selected whale individual; is the distance between the current whale individual and the randomly selected whale individual.

[0135] Step S48, judging whether the maximum iteration number is reached, if the maximum iteration number is reached, outputting the position of the whale, that is, the optimal solution.

[0136] Example 2

[0137] Based on the IEEE 10-machine 39-node power distribution network system, the generator groups of nodes 30, 32 and 38 are replaced with equal-capacity photovoltaic generator models, and nodes 31, 33 and 35 are replaced with equal-capacity wind power generation units, so as to ensure that the new energy penetration rate is between 40% and 60%, and the new energy network structure diagram is shown in FIG. 3.

[0138] It is assumed that at 0.5s, the generators at nodes 34 and 39 of the new power system fail, and lose 1500MW of active power. Two methods are set, which are as follows:

[0139] Scheme 1: the load shedding method considering the output characteristics of new energy of the application;

[0140] Scheme 2: the traditional method;

[0141] The safe operation results of the new power system after the implementation of the two load shedding methods are shown in Table 1 and Table 2.

[0142] Table 1: traditional load shedding method

[0143]

[0144] Table 2: load shedding method of the application

[0145]

[0146] According to the comparative analysis of Table 1 and Table 2, the method proposed in the application makes the system frequency and voltage of the new power system quickly recover and remain in a stable state after 5 rounds of load shedding, significantly improving the safety and reliability of the system. In contrast, the traditional method not only has a large frequency deviation, but also fails to restore the voltage to the safe voltage range, making it difficult to effectively guarantee the safe operation of the system. Further from the perspective of response time, the total response time of the method of the application is 2.5 seconds, which is 30% shorter than that of the traditional method, indicating that the method has a significant advantage in fast response and adjustment capability, which helps to improve the dynamic adjustment capability of the system under sudden load changes, and guarantees the stability and anti-disturbance capability of the power system. The 1 iteration curve of the two schemes is shown in FIG. Figure 4 .

[0147] Figure 4 ​It can be seen that, compared with the method proposed by the traditional method, the method of the application converges successfully after only 20 iterations, while the method in the traditional method has not reached the convergence state at this time, which is obviously lagging behind the method of the application. At the same time, the traditional method does not clearly propose a unified safety and stability index, resulting in a higher fitness function value than the method of the application. The larger the fitness function value, the more serious the damage to the system. In summary, the method proposed by the application has more obvious advantages in iteration speed, convergence effect and system performance optimization compared with the traditional method algorithm, and has significant application value in ensuring the stability and safety of the power system.

[0148] The power system safety and stability control method provided by the application analyzes the output characteristics of new energy to propose a power system safety and stability control index; considering the minimum safety and stability control index quantization and the minimum load shedding amount as the target, a safety and stability control model is established in combination with static constraints, transient constraints and power balance constraints; the contraction surrounding prey and spiral bubble net attack in the whale algorithm are improved, so that the whale optimization algorithm can more efficiently handle complex optimization problems, and finally the improved whale algorithm is used to solve the model.

[0149] The application has the advantages that: the output characteristics of new energy are analyzed, and a safety and stability index is proposed according to the output characteristics of new energy, which helps to identify and control these fluctuations to prevent the impact on the grid frequency and voltage and avoid system instability or large-scale power outages; an improved whale algorithm is proposed to solve the new type of power system safety and stability model, which is superior to other algorithms in optimization performance, convergence speed and stability, and can effectively solve the safety and stability problems of new energy systems. The application suppresses the instability and safety hazards of the power system caused by the fluctuation of new energy output, ensures the generation of low-frequency load shedding strategies when the power system encounters faults or new energy fluctuations, and thus ensures the safety and stability of the power system.

[0150] The above is a power system safety and stability control method provided in an embodiment of the application, and the following is a power system safety and stability control system provided in an embodiment of the application.

[0151] Please refer to Figure 5 The power system safety and stability control system provided in an embodiment of the application comprises:

[0152] The first construction unit 201 is configured to construct a safety and stability control index of the power system according to the output characteristics of new energy, and the safety and stability control index comprises: a frequency deviation index, voltage stability and frequency response time.

[0153] The second construction unit 202 is configured to establish a safety and stability control model with the minimum safety and stability control index and the minimum load shedding amount as the target.

[0154] The solving unit 203 is used for solving the safety and stability control model by using the improved whale optimization algorithm to generate the low-frequency load shedding strategy after the fault, wherein the improved method of the improved whale optimization algorithm comprises: improving the contraction surrounding prey and spiral bubble net attack links in the whale optimization algorithm.

[0155] Further, the embodiment of the present application further provides a power system safety and stability control device, the device comprising a processor and a memory:

[0156] The memory is used for storing program codes and transmitting the program codes to the processor.

[0157] The processor is used for executing the steps of the power system safety and stability control method according to the instructions in the program codes.

[0158] Further, the embodiment of the present application further provides a computer readable storage medium, the computer readable storage medium is used for storing program codes, and the program codes are used for executing the power system safety and stability control method.

[0159] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-mentioned system, device and unit can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0160] In several embodiments provided by the present application, it should be understood that the disclosed system, device and method can be implemented by other manners. For example, the above-mentioned device embodiments are only schematic, for example, the division of units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0161] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on a plurality of network units. According to actual needs, some or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0162] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit.

[0163] If the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the prior art that essentially contributes or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0164] The above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A power system safety and stability control method, characterized by, Comprise: According to the new energy output characteristics, the safety and stability control index of the power system is constructed, and the safety and stability control index comprises: frequency deviation index, voltage stability, frequency response time; A safety and stability control model is established with the minimum safety and stability control index and the minimum load shedding amount as the target; An improved whale optimization algorithm is used to solve the safety and stability control model to generate a post-fault low-frequency load shedding strategy, wherein the improved method of the improved whale optimization algorithm comprises: improving the contraction surrounding prey and spiral bubble net attack links in the whale optimization algorithm; The expression of the frequency deviation index is: ； wherein, is the load power, is the conventional unit output, is the actual output power of the photovoltaic system, is the system equivalent inertia constant, is the system rated frequency, is the power of the distributed wind power.

2. The power system safety and stability control method of claim 1, wherein, The safety and stability control index of the power system is constructed according to the distributed photovoltaic energy output characteristics and the distributed wind power new energy characteristics. The expression of the voltage stability is:

3. The power system safety and stability control method of claim 1, wherein, The expression of the frequency response time is: ； wherein is the change in the node voltage, is the node voltage, is the actual output power of the photovoltaic system, is the power of the distributed wind power, is the reference output value.

4. The power system safety and stability control method of claim 1, wherein, The safety and stability control model is established with the minimum safety and stability control index and the minimum load shedding amount as the target, comprising: ； wherein is the frequency response time, is the actual output power of the photovoltaic system, is the power of the distributed wind power, is the output of the conventional generating units, and are the inertia time constants of the new energy and the conventional generating units, respectively.

5. The power system safety and stability control method of claim 1, wherein, Respectively, the objective functions with the minimum safety and stability control index and the minimum load shedding amount are constructed, and the safety and stability control model is established with power balance constraints, safety operation risk constraints, static constraints and transient constraints as constraint conditions. The contraction surrounding prey and spiral bubble net attack links in the whale optimization algorithm are improved, comprising:

6. The power system safety and stability control method of claim 1, wherein, The contraction surrounding prey in the whale optimization algorithm is improved by introducing an adaptive inertia weight, and the spiral bubble net attack link is optimized by adding a Lévy flight mechanism. Comprise:

7. A power system safety and stability control system characterized by comprising: A first construction unit is configured to construct a safety and stability control index of a power system according to new energy output characteristics, and the safety and stability control index comprises: frequency deviation index, voltage stability, frequency response time; A second construction unit is configured to establish a safety and stability control model with the minimum safety and stability control index and the minimum load shedding amount as the target; A solving unit is configured to solve the safety and stability control model using an improved whale optimization algorithm to generate a post-fault low-frequency load shedding strategy, wherein the improved method of the improved whale optimization algorithm comprises: improving the contraction surrounding prey and spiral bubble net attack links in the whale optimization algorithm; The expression of the frequency deviation index is: The device comprises a processor and a memory: ； wherein is the load power, is the conventional unit output, is the actual output power of the photovoltaic system, is the system equivalent inertia constant, is the system rated frequency, is the power of the distributed wind power.

8. A power system safety and stability control device, characterized by comprising: The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the power system safety and stability control method according to the instructions in the program code. The computer readable storage medium is used to store program code, and the program code is used to execute the power system safety and stability control method.

9. A computer-readable storage medium, characterized in that, ​

Images