Power system safety and stability control method, system, equipment and medium

Abstract

The invention discloses a power system safety and stability control method, system and device and a medium, and the method comprises the steps: firstly, analyzing the output characteristics of new energy, and constructing a power system safety and stability control index; secondly, a safety and stability control model is established by taking a safety and stability control index and a minimum load shedding amount as targets and taking an operation risk as a constraint; secondly, improving links of contraction surrounding preys and spiral bubble net attack in the whale algorithm; and finally, solving the safety stability control model by using the improved whale algorithm, and realizing the generation of the low-frequency load shedding strategy after the fault. According to the method, instability and potential safety hazards of the power system caused by new energy output fluctuation are inhibited, and generation of the low-frequency load shedding strategy when the power system encounters a fault or new energy fluctuation is ensured, so that the safety and stability of the power system are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of safe operation of power systems, and in particular to a method, system, equipment and medium for safe and stable control of power systems. Background Art

[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 new energy system trends, stability mode diversity and mechanism complexity.

[0003] The existing methods for solving safety and stability control models 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. By establishing a detailed mathematical model, power flow calculation and transient stability analysis are performed to provide a basis for the stability control strategy. However, the physical model of the new energy system is highly complex, with many 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. However, it relies on high-quality historical data, the data volume is large and the annotation difficulty is high. For the data fusion method, the physical model is combined with the data-driven model, and the theoretical guidance provided by the physical model is used to assist the data-driven model in adjustment. However, the coupling and coordination between the physical model and the data-driven model is difficult to handle, and the requirements for computing resources and data 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 the optimization algorithm. Introducing different characteristics of new energy in the configuration and optimizing the control strategy can comprehensively consider multiple objectives, achieve balanced optimization, and adapt to different working conditions and needs. None of the above studies considered the output characteristics of renewable energy sources and established complete stability control indicators based on the output characteristics of renewable energy sources.

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

[0005] The present invention provides a method, system, equipment and medium for safe and stable control of an electric power system, which are used to suppress the instability and potential safety hazards of the electric power system caused by fluctuations in the output of renewable energy, so that a low-frequency load reduction strategy is generated when the electric power system encounters a fault or fluctuations in renewable energy, thereby ensuring the safety and stability of the electric power system.

[0006] In view of this, the first aspect of the present application provides a method for safe and stable control of a power system, the method comprising:

[0007] Constructing safety and stability indicators of the power system according to the output characteristics of new energy sources, wherein the safety and stability indicators include: frequency deviation index, voltage stability, and frequency response time;

[0008] A safety and stability control model is established with the goal of minimizing the safety and stability control index and the load shedding amount;

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

[0010] Optionally, the safety and stability control indicators of the power system are constructed according to the output characteristics of new energy sources, including:

[0011] According to the output characteristics of distributed photovoltaic energy and distributed wind power new energy characteristics, the safety and stability control indicators of the power system are constructed.

[0012] Optionally, the frequency deviation index is expressed as:

[0013] ;

[0014] In the formula, is the load rate, Output for conventional units, For photovoltaic power generation, is the system equivalent inertia constant, is the rated frequency of the system.

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

[0016] ;

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

[0018] Optionally, the frequency response time is expressed as:

[0019] ;

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

[0021] Optionally, establishing a safety and stability control model with the goal of minimizing the safety and stability control index and the load shedding amount includes:

[0022] The objective functions of minimizing the safety and stability index and minimizing the load shedding are respectively constructed, and the safety and stability model is established with power balance constraint, safety operation risk constraint, static constraint and transient constraint as constraint conditions.

[0023] Optionally, the improvement of the shrinking and surrounding prey and spiral bubble net attack links in the whale algorithm includes:

[0024] Adaptive inertia weight is introduced to improve the shrinking and surrounding prey in the whale algorithm, and the Lévy flight mechanism is added to optimize the spiral bubble net attack link.

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

[0026] The first construction unit is used to construct safety and stability indicators of the power system according to the output characteristics of new energy sources, wherein the safety and stability indicators include: frequency deviation index, voltage stability, and frequency response time;

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

[0028] A solving unit is used to solve the safety and stability control model by using an improved whale algorithm to generate a low-frequency load reduction strategy after a fault, wherein the improved method of the improved whale algorithm includes: improving the shrinking and surrounding prey and the spiral bubble net attack links in the whale algorithm.

[0029] A third aspect of the present invention provides a power system safety and stability control device, the device comprising a processor and a memory:

[0030] The memory is used to store program code and transmit the program code to the processor;

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

[0032] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store program code, and the program code is used to execute the power system security and stability control method described in the first aspect above.

[0033] It can be seen from the above technical solutions that the present invention has the following advantages:

[0034] The present invention provides a method for safe and stable control of a power system. By analyzing the output characteristics of new energy sources, a more accurate indicator of safe and stable control of the power system is constructed. On this basis, a multi-objective safe and stable control optimization model is established in combination with the minimum load shedding amount and the operating risk constraints. In view of the shortcomings of the whale algorithm, the "shrinking and surrounding prey" and "spiral bubble net attack" mechanisms are improved to improve the global optimization capability of the algorithm. Through the improved algorithm, the generation of a low-frequency load reduction strategy after a fault is successfully achieved, and the safety of the power system in the event of a fault is enhanced. The present invention suppresses the instability and safety hazards of the power system caused by fluctuations in the output of new energy sources, and ensures the generation of a low-frequency load reduction strategy for the power system when encountering faults or fluctuations in new energy sources, thereby ensuring the safety and stability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative labor.

[0036] Figure 1 A schematic diagram of a flow chart of a power system safety and stability control method provided by an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a process for solving a safety and stability control model provided by an embodiment of the present invention;

[0038] Figure 3 An improved IEEE39 new power system provided by an embodiment of the present invention;

[0039] Figure 4 The fitness function value of the load shedding method provided by the traditional method of the embodiment of the present invention and the load shedding method of the present invention;

[0040] Figure 5 A schematic diagram of the structure of a power system safety and stability control system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Embodiment 1:

[0043] See also Figure 1 , a method for safe and stable control of a power system provided in an embodiment of the present invention includes:

[0044] Step 101: construct safety and stability indicators of the power system according to the output characteristics of new energy sources. The safety and stability indicators include: frequency deviation index, voltage stability, and frequency response time.

[0045] Step 102: Establish a safety and stability control model with the goal of minimizing the safety and stability control index and the load shedding amount.

[0046] Step 103: Use the improved whale algorithm to solve the safety and stability control model and generate a low-frequency load reduction strategy after a fault. The improved method of the improved whale algorithm includes: improving the shrinking and surrounding prey and the spiral bubble net attack links in the whale algorithm.

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

[0048] Among them, the expression of frequency deviation index is:

[0049] ;

[0050] In the formula, is the load rate, Output for conventional units, For photovoltaic power generation, is the system equivalent inertia constant, is the rated frequency of the system.

[0051] The expression of voltage stability is:

[0052] ;

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

[0054] The expression for frequency response time is:

[0055] ;

[0056] In the formula, is the frequency response time, is the actual output power of the photovoltaic system, is the power of distributed wind power, Output for conventional units, and are the inertia time constants of new energy and conventional units respectively.

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

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

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

[0060] The output of distributed photovoltaic new energy is mainly affected by light intensity. The light radiation can be approximately regarded as Beta distribution. The probability density function of photovoltaic output is:

[0061] ;

[0062] In the formula, Powering photovoltaic power The probability density function of is the actual output power of the photovoltaic system; The maximum output of the system; are the two parameters of the Beta distribution.

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

[0064] The present invention adopts lognormal distribution to describe wind speed data, and the specific probability density function is:

[0065] ;

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

[0067] Then, the safety and stability indicators of the power system are constructed according to the output characteristics of new energy sources, including:

[0068] Frequency Deviation Index:

[0069] In order to measure the frequency stability of the system, the frequency deviation is defined as As a stability indicator:

[0070] ;

[0071] Where: is the load rate; Provide power for conventional units; is the system equivalent inertia constant; is the rated frequency of the system.

[0072] Voltage stability index:

[0073] The inverter characteristics of renewable energy power generation have a weak ability to support grid voltage, so the voltage stability index should include the output changes of renewable energy.

[0074] ;

[0075] Where: is the change of node voltage, is the node voltage, is the reference output value.

[0076] Frequency response time index:

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

[0078] ;

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

[0080] In one embodiment, step 102 includes:

[0081] The objective functions of minimizing the safety and stability index and minimizing the load shedding are constructed respectively, and a safety and stability model is 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, the objective functions of minimizing the safety and stability index and minimizing the load shedding are constructed respectively, including:

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

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

[0086] ;

[0087] In the formula, is represented as a random weight coefficient.

[0088] 2) Minimum load shedding:

[0089] In order to ensure that the system can still operate stably under unbalanced conditions, load shedding is the last resort to ensure system safety. The goal is to reduce the load shedding amount to a minimum. The load shedding objective function is:

[0090] ;

[0091] In the formula, is the total number of nodes that need to shed load in the system; For the The load shedding amount of each node.

[0092] The objective function combines the minimization of the stability control index and the load shedding amount, and is expressed as:

[0093] ;

[0094] Then, power balance constraints, safe operation risk constraints, static constraints and transient constraints are used as constraints, where:

[0095] 1) Static constraints and transient constraints:

[0096] ;

[0097] In the formula, for The system inertia center frequency at time; is the minimum frequency for calculation; is the lower limit of frequency; , are the maximum and minimum values ​​of node load respectively; For the Load shedding node The amount of load reduction; 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] Where: For the The output of a conventional generator; The sum of all new energy outputs; For the The power demand of each load; is the system transmission loss.

[0101] 3) Safe operation risk constraints:

[0102] The safe operation of the power system faces multiple risks, including fluctuations in power generation, changes in load, and uncertainty in new energy sources. The comprehensive operation risk should be controlled within an acceptable range:

[0103] ;

[0104] Where: The comprehensive operational risk of the system; , , , are the risks associated with frequency, voltage, generation power and frequency response time respectively; The maximum combined risk allowed by the system;

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

[0106] Regarding step 103, it should be noted that:

[0107] Adaptive inertia weights are introduced to improve the shrinking and encircling prey in the whale algorithm, and the Lévy flight mechanism is added to optimize the spiral bubble net attack link, including:

[0108] 1) Introducing adaptive inertia weight:

[0109] In order to improve the flexibility and dynamics of the shrinking and encircling stage, an exponential decay mechanism is used instead of linear decay, and an adaptive inertia weight and fuzzy control strategy are introduced to enable whale individuals to have different shrinking and encircling speeds at different stages. Improved to:

[0110] ;

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

[0112] ;

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

[0114] 2) Add Lévy flight mechanism:

[0115] Spiral motion is usually continuous and regular, but in order to increase the randomness and globality of exploration, a Lévy flight mechanism is added to enable individuals to perform jumping searches between local and long distances, while dynamically adjusting the contraction and expansion of the spiral path.

[0116] ;

[0117] In the formula, is the coefficient that controls the Lévy flight step length; is Lévy distribution; , is the control parameter of Lévy distribution; To control the randomness of the search range.

[0118] Finally, the improved whale algorithm is used to solve the safety and stability control model and generate a low-frequency load reduction strategy after a fault, such as Figure 2 As shown, the specific steps include:

[0119] Step S41, initializing parameters;

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

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

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

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

[0124] ;

[0125] In the formula, For individual whales The new position in iteration ; is the position (of the prey) of the current optimal solution; is a weight coefficient controlled by the algorithm, which is used to control the amplitude of the shrinkage. It decreases linearly from 2 to 0, which is used to control the shrinkage range. is the distance between the whale and its prey; is a random vector; Is a random number.

[0126] Step S45, spiral bubble net attack;

[0127] When whales hunt, they sometimes approach their prey in a spiral path. The spiral trajectory updates the whale's position. The mathematical model is expressed as:

[0128] ;

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

[0130] Step S46: Determine Is it greater than 1? If so, proceed to the next step. If less than 1, return to S45.

[0131] Step S47, randomly searching for prey;

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

[0133] ;

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

[0135] Step S48, determine whether the maximum number of iterations has been reached. If so, output the position of the whale, which is the optimal solution.

[0136] Embodiment 2:

[0137] Based on the IEEE10-machine 39-node distribution network system, the generator sets at nodes 30, 32, and 38 are replaced with photovoltaic unit models of equal capacity, and nodes 31, 33, and 35 are replaced with wind power generation units of equal capacity, ensuring that the new energy penetration rate is between 40% and 60%. The new energy network structure diagram is shown in Figure 3.

[0138] Assume 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, specifically:

[0139] Solution 1: The load shedding method of the present invention taking into account the output characteristics of new energy sources;

[0140] Option 2: Traditional method;

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

[0142] Table 1 Traditional method of load shedding

[0143]

[0144] Table 2 Load shedding method of the present invention

[0145]

[0146] According to the comparative analysis of Table 1 and Table 2, after 5 rounds of load shedding, the method proposed by the present invention can quickly restore the system frequency and voltage of the new power system and maintain them in a stable state, which significantly improves the safety and reliability of the system. In contrast, the traditional method not only has the problem of large frequency deviation, but also the voltage has never been restored to the safe voltage range, making it difficult to effectively ensure the safe operation of the system. Further from the perspective of response time, the total response time of the method of the present invention is 2.5 seconds, which is 30% shorter than the traditional method. This shows that the method has significant advantages in rapid response and adjustment capabilities, which helps to improve the system's dynamic adjustment capabilities in the event of sudden load changes and ensure the stability and anti-disturbance capabilities of the power system. The 1 iteration curves of the two schemes are shown in the figure below. Figure 4 shown.

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

[0148] The present invention provides a power system safety and stability control method, which proposes power system safety and stability control indicators by analyzing the output characteristics of new energy; considers the minimum safety and stability control indicator quantification and the minimum load shedding as the goal, and establishes a safety and stability control model by combining static constraints, transient constraints, power balance and other constraints; improves the shrinking and surrounding prey and spiral bubble net attack in the whale algorithm, so that the whale optimization algorithm can handle complex optimization problems more efficiently, and finally uses the improved whale algorithm to solve the model.

[0149] The beneficial effects of the present invention are: analyzing the output characteristics of new energy sources, and proposing safety and stability indicators based on the output characteristics of new energy sources, which helps to identify and control these fluctuations to prevent impacts on the frequency and voltage of the power grid, and avoid system instability or large-scale power outages; an improved whale algorithm is proposed to solve the new power system safety and stability model, which is superior to other algorithms in terms of optimization performance, convergence speed and stability, and can effectively solve the problem of safety and stability of new energy systems. The present invention suppresses the instability and safety hazards of the power system caused by fluctuations in the output of new energy sources, and ensures the generation of a low-frequency load reduction strategy when the power system encounters a fault or fluctuations in new energy sources, thereby ensuring 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 present invention, and the following is a power system safety and stability control system provided in an embodiment of the present invention.

[0151] See also Figure 5 , a power system safety and stability control system provided in an embodiment of the present invention includes:

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

[0153] The second building unit 202 is used to build a safety and stability control model with the goal of minimizing the safety and stability control index and the minimum load shedding amount.

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

[0155] Furthermore, an embodiment of the present invention also provides a power system safety and stability control device, the device comprising a processor and a memory:

[0156] The memory is used to store program code and transmit the program code to the processor;

[0157] The processor is used to execute the steps of the power system safety and stability control method as described in the above method embodiment according to the instructions in the program code.

[0158] Furthermore, a computer-readable storage medium is provided in an embodiment of the present invention, and the computer-readable storage medium is used to store program codes, and the program codes are used to execute the power system safety and stability control method described in the above method embodiment.

[0159] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0160] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an 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 may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0162] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0163] If the integrated unit is implemented in the form of a software functional 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 solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0164] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for safe and stable control of a power system, characterized in that: include: Constructing safety and stability indicators of the power system according to the output characteristics of new energy sources, wherein the safety and stability indicators include: frequency deviation index, voltage stability, and frequency response time; A safety and stability control model is established with the goal of minimizing the safety and stability control index and the load shedding amount; The improved whale algorithm is used to solve the safety and stability control model to generate a low-frequency load reduction strategy after a fault, wherein the improved method of the improved whale algorithm includes: improving the shrinking and surrounding prey and the spiral bubble net attack links in the whale algorithm.

2. The power system safety and stability control method according to claim 1, characterized in that: The safety and stability control indicators of the power system constructed according to the output characteristics of new energy sources include: According to the output characteristics of distributed photovoltaic energy and distributed wind power new energy characteristics, the safety and stability control indicators of the power system are constructed.

3. The power system safety and stability control method according to claim 1 or 2, characterized in that: The expression of the frequency deviation index is: ； In the formula, is the load rate, Output for conventional units, For photovoltaic power output, is the system equivalent inertia constant, is the rated frequency of the system.

4. The power system safety and stability control method according to claim 1, characterized in that: The expression of voltage stability is: ； In the formula, is the change of node voltage, is the node voltage, is the actual output power of the photovoltaic system, is the power of distributed wind power, is the reference output value.

5. The power system safety and stability control method according to claim 1, characterized in that: The expression of the frequency response time is: ； In the formula, is the frequency response time, is the actual output power of the photovoltaic system, is the power of distributed wind power, Output for conventional units, and are the inertia time constants of new energy and conventional units respectively.

6. The power system safety and stability control method according to claim 1, characterized in that: The safety and stability control model is established with the goal of minimizing the safety and stability control index and the load shedding amount, including: The objective functions of minimizing the safety and stability index and minimizing the load shedding are respectively constructed, and the safety and stability model is established with power balance constraint, safety operation risk constraint, static constraint and transient constraint as constraint conditions.

7. The power system safety and stability control method according to claim 1, characterized in that: The improvements to the shrinking and surrounding prey and spiral bubble net attack links in the whale algorithm include: Adaptive inertia weight is introduced to improve the shrinking and surrounding prey in the whale algorithm, and the Lévy flight mechanism is added to optimize the spiral bubble net attack link.

8. A power system safety and stability control system, characterized in that: include: The first construction unit is used to construct safety and stability indicators of the power system according to the output characteristics of new energy sources, wherein the safety and stability indicators include: frequency deviation index, voltage stability, and frequency response time; A second construction unit is used to establish a safety and stability control model with the minimum safety and stability control index and the minimum load shedding amount as the goal; A solving unit is used to solve the safety and stability control model by using an improved whale algorithm to generate a low-frequency load reduction strategy after a fault, wherein the improved method of the improved whale algorithm includes: improving the shrinking and surrounding prey and the spiral bubble net attack links in the whale algorithm.

9. A power system safety and stability control device, characterized in that: The device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the power system safety and stability control method described in any one of claims 1-7 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program code, and the program code is used to execute the power system security and stability control method described in any one of claims 1-7.

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