Stability control method for high-proportion new energy power system and related product

Abstract

The embodiment of the invention relates to the technical field of power system control, and provides a stability control method for a high-proportion new energy power system and related products, and the method comprises the steps: obtaining the unit information of each generator set in the high-proportion new energy power system; obtaining a frequency sensitivity coefficient and an active sensitivity coefficient of each generator set according to the set information of each generator set; obtaining a generator tripping priority coefficient of each generator set according to the frequency sensitivity coefficient and the active sensitivity coefficient of each generator set; according to the generator tripping priority coefficient of each generator set, obtaining a preliminary generator tripping quantity distribution result of each generator set; constructing a target function according to the initial generator tripping quantity distribution result of each generator set; and optimizing the Gini coefficient to obtain a target generator tripping amount distribution result of each generator set. According to the invention, collaborative optimization of frequency stability efficiency and generator tripping fairness can be realized, and safe and balanced stable control generator tripping of a high-proportion new energy power system is ensured.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of power system control, and in particular, to a stable control method and related products for a high-proportion new energy power system. Background Art

[0002] With the advancement of the "dual carbon" goal, the power system shows the characteristics of high-proportion new energy (such as wind power, photovoltaic, etc.) grid connection. With the large-scale grid connection of new energy such as wind power and photovoltaic, the operating characteristics of the power system and the strategies of game players have changed. Although the new energy converters used in the aforementioned power system, such as voltage source converters (VSCs for short), have flexible control capabilities, they lack the physical inertia and speed regulation characteristics of synchronous generators, resulting in a decrease in the equivalent inertia of the power system and a weakening of frequency stability.

[0003] When the power system enters the island passively (such as the tripping of the tie line) or experiences a severe power deficit, since the new energy converter cannot provide the inertia response at the synchronous machine level, in the case of insufficient inertia support, the stable control generator tripping decision needs to consider both inertia retention and active power balance simultaneously. Moreover, the frequency response mechanisms of synchronous machines and new energy are significantly different, and a single index (such as active power capacity, frequency threshold) cannot accurately describe the equipment characteristics, which will lead to the lack of multi-type coordination. The traditional stable control generator tripping strategy is not applicable to a high-proportion new energy power system and cannot ensure the stable control of a high-proportion new energy power system. Summary of the Invention

[0004] The embodiments of the present application provide a stable control method and related products for a high-proportion new energy power system, which can realize the collaborative optimization of frequency stability efficiency and generator tripping fairness, and provide a safer and more balanced stable control generator tripping solution for a high-proportion new energy power system.

[0005] In one aspect, the embodiments of the present application provide a stable control method for a high-proportion new energy power system, and the method includes:

[0006] Obtain the unit information of each generating unit in the high-proportion new energy power system; wherein, each generating unit includes at least one type of generator;

[0007] According to the unit information of each generating unit, obtain the frequency sensitivity coefficient and active power sensitivity coefficient of each generating unit; wherein, the frequency sensitivity coefficient is used to reflect the support strength of each generating unit for frequency stability, and the active power sensitivity coefficient is used to reflect the influence degree of generator tripping on frequency stability;

[0008] According to the frequency sensitivity coefficient and active power sensitivity coefficient of each generating unit, obtain the generator tripping priority coefficient of each generating unit;

[0009] According to the unit shedding priority coefficients of the respective generating units, obtain the preliminary unit shedding quantity allocation results of the respective generating units;

[0010] Construct an objective function according to the preliminary unit shedding quantity allocation results of the respective generating units; the value of the objective function is the Gini coefficient;

[0011] Optimize the Gini coefficient to obtain the target unit shedding quantity allocation results of the respective generating units.

[0012] On the other hand, an embodiment of the present application provides a stable control device for a high-proportion new energy power system, and the device includes:

[0013] A unit information acquisition module, configured to acquire the unit information of the respective generating units in the high-proportion new energy power system; wherein, each generating unit includes at least one type of generator;

[0014] A sensitivity coefficient generation module, configured to obtain the frequency sensitivity coefficient and the active power sensitivity coefficient of the respective generating units according to the unit information of the respective generating units; wherein, the frequency sensitivity coefficient is used to reflect the support intensity of the respective generating units for frequency stability, and the active power sensitivity coefficient is used to reflect the influence degree of unit shedding on frequency stability;

[0015] A priority coefficient generation module, configured to obtain the unit shedding priority coefficients of the respective generating units according to the frequency sensitivity coefficient and the active power sensitivity coefficient of the respective generating units;

[0016] A preliminary allocation result generation module, configured to obtain the preliminary unit shedding quantity allocation results of the respective generating units according to the unit shedding priority coefficients of the respective generating units;

[0017] An objective function construction module, configured to construct an objective function according to the preliminary unit shedding quantity allocation results of the respective generating units; the value of the objective function is the Gini coefficient;

[0018] A target allocation result generation module, configured to optimize the Gini coefficient to obtain the target unit shedding quantity allocation results of the respective generating units.

[0019] In yet another aspect, an embodiment of the present application further provides an electronic device, including: a processor, a memory, and a computer program stored on the memory and capable of running on the processor, and when the computer program is executed by the processor, it implements the stable control method of the high-proportion new energy power system described in any one of the above.

[0020] In yet another aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the stable control method of the high-proportion new energy power system described in any one of the above.

[0021] In yet another aspect, an embodiment of the present application further provides a computer program product containing instructions. When it runs on a computer, it causes the computer to execute the stable control method of the high-proportion new energy power system described in each of the above aspects.

[0022] The stable control method and related products provided by the embodiments of the present application obtain the unit information of each generating unit in the high-proportion new energy power system including at least one type of generator, and obtain the frequency sensitivity coefficient and active power sensitivity coefficient of each generating unit according to the unit information of each generating unit. Among them, the frequency sensitivity coefficient can be used to reflect the support intensity of each generating unit for frequency stability, and the active power sensitivity coefficient can be used to reflect the influence degree of generator tripping on frequency stability. By introducing the dual indexes of frequency sensitivity and active power sensitivity, the limitation of a single index is broken through, the contribution differences of multiple types of generators to frequency stability are accurately quantified, and the risk of frequency collapse caused by mis-tripping high-inertia units is avoided; further, the generator tripping priority coefficient of each generating unit can be obtained according to the frequency sensitivity coefficient and active power sensitivity coefficient of each generating unit, and the preliminary generator tripping amount allocation result of each generating unit can be obtained according to the generator tripping priority coefficient of each generating unit. Then, a target function is constructed according to the preliminary generator tripping amount allocation result of each generating unit, and the value of the target function, that is, the Gini coefficient, is optimized to optimize the generator tripping amount allocation in the target function based on the Gini coefficient, and the target generator tripping amount allocation result of each generating unit is obtained, so as to realize the fairness optimization of the preliminary generator tripping amount allocation result, avoid a single unit from over-undertaking the generator tripping task, reduce the loss risk of a single unit, and improve the long-term operation reliability of the system. The embodiments of the present application can realize the collaborative optimization of frequency stability efficiency and generator tripping fairness, and provide a safer and more balanced stable control and generator tripping solution for the high-proportion new energy power system. Description of the Drawings

[0023] Figure 1 is a framework schematic diagram of a high-proportion new energy power system provided by an embodiment of the present application;

[0024] Figure 2 is a step flow chart of a stable control method of a high-proportion new energy power system provided by an embodiment of the present application;

[0025] Figure 3 is a structural block diagram of a stable control device of a high-proportion new energy power system according to an embodiment of the present application;

[0026] Figure 4 It is a structural block diagram of an electronic device provided by an embodiment of the present application;

[0027] Figure 5 It is a structural block diagram of a computer-readable storage medium provided by an embodiment of the present application. Specific implementation manners

[0028] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part 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 efforts belong to the scope of protection of the present application.

[0029] Traditional stable control and generator tripping strategies include a generator tripping strategy based on active power capacity and a generator tripping strategy based on frequency threshold. Exemplarily, the generator tripping strategy based on active power capacity is manifested as preferentially tripping the units with large active power output, such as synchronous machines (as generators), believing that the tripping of the aforementioned units has a significant compensation effect on the active power deficit; the generator tripping strategy based on frequency threshold is manifested as triggering generator tripping when the frequency deviation exceeds the threshold, such as ±0.5 Hz, and preferentially tripping the units with low frequency sensitivity, such as new energy sources that do not participate in frequency modulation.

[0030] However, the traditional stable control and generator tripping strategies ignore the characteristic differences between synchronous machines and new energy sources, treat synchronous machines and new energy sources equally, and may mis-tripping high-inertia synchronous machines, resulting in a sudden drop in system inertia and an increased risk of frequency collapse; moreover, in the above traditional stable control and generator tripping strategies, high-priority units, such as synchronous machines that frequently participate in frequency modulation, often bear excessive generator tripping tasks, which may lead to increased wear and shortened life of their governors, while the adjustable margin of new energy sources is not reasonably utilized, which may cause an increase in the curtailment rate of electricity, and there are disadvantages such as lack of fairness in the distribution of generator tripping amount and uneven equipment losses; in addition, most traditional stable control and generator tripping strategies adopt a fixed priority table and cannot dynamically respond to changes in system inertia, such as fluctuations in the number of synchronous machines in operation and real-time changes in the output of new energy sources. In emergency scenarios such as passive islands, chain faults may be triggered due to generator tripping delays or improper distribution, and there are disadvantages such as insufficient dynamic response on multiple time scales and inability to adapt to complex scenarios.

[0031] The embodiment of this application proposes a multi-type power system stability control scheme based on double-sensitivity-Gini coefficient double-layer optimization decision-making. By taking into account the frequency stability efficiency and the fairness of generator tripping in double-layer optimization, it can achieve the coordinated optimization of frequency stability efficiency and generator tripping fairness, and provide a safer and more balanced stability control and generator tripping solution for a high-proportion new energy power system. Specifically, by introducing the double-sensitivity index of frequency sensitivity and active power sensitivity, it breaks through the limitations of a single index (such as active power capacity, frequency threshold), accurately quantifies the contribution differences of multi-type generators to frequency stability, such as the inertia support ability of synchronous machines and the active power regulation potential of new energy, etc., to accurately distinguish equipment characteristics and avoid the risk of frequency collapse caused by mis-tripping high-inertia units; further, a fairness optimization model can be constructed based on the Gini coefficient to optimize the generator tripping amount allocation in the objective function based on the Gini coefficient, obtain the target generator tripping amount allocation results for each generator set, realize the fairness optimization of the preliminary generator tripping amount allocation results, avoid a single unit from over-undertaking the generator tripping task, reduce the loss risk of a single unit, ensure the balance of the generator tripping burden, and is conducive to improving the long-term operation reliability of the system.

[0032] Referring to Figure 1 , a framework schematic diagram of a high-proportion new energy power system provided by the embodiment of this application is shown. A high-proportion new energy power system refers to a power system showing the characteristics of high-proportion new energy grid connection. As Figure 1 shown, a certain power grid sub-region of a high-proportion new energy power system can be composed of N generator sets (N is a positive integer) and loads. Among them, each generator set can include a generators that can be tripped (a is a positive integer), and each generator set can include at least one type of generator, and this type can be a synchronous machine, new energy, etc. Among them, new energy can be, for example, wind power, photovoltaic, etc., and the embodiment of this application does not limit this.

[0033] Among them, the active power output by the i-th generator set can be P i , and the rated power of the i-th generator set can be P rate,i , where i = [1, 2, 3,..., N], N is the number of generator sets in a certain power grid sub-region, and i is a positive integer; the surplus power P cut,total of a certain power grid sub-region of a high-proportion new energy power system. The aforementioned surplus power can be regarded as the active power that the generator set needs to trip, and generally refers to the part where the power generation power in a high-proportion new energy power system exceeds the load demand (including network losses).

[0034] Optionally, when the high-proportion new energy power system is operating normally, the power can be transmitted through the AC line. The transmitted power is usually the active power output by the generator set. However, there may be situations such as DC blocking, AC line tripping, and load fluctuations in the grid partition. When the AC transmission channel is disconnected, there will be a phenomenon of surplus active power.

[0035] In the embodiment of the present application, for the removal of the above surplus power, it can be achieved through the stable control generator tripping strategy based on the double-sensitivity-Gini coefficient double-layer optimization decision proposed in the embodiment of the present application.

[0036] Specifically, referring to Figure 2 , a step flowchart of a stable control method for a high-proportion new energy power system provided by an embodiment of the present application is shown. Applied to a high-proportion new energy power system as shown in Figure 1 , it may specifically include the following steps:

[0037] Step S201, obtain the unit information of each generator set in the high-proportion new energy power system.

[0038] Each generator set is a cuttable unit provided for the high-proportion new energy power system. Each generator set may include at least one generator, and the at least one generator may be at least one type of generator, such as a synchronous machine, new energy, etc. The embodiment of the present application does not limit this.

[0039] In some embodiments of the present application, the unit information of each generator set can be obtained for the calculation of the double-sensitivity index, so as to implement the stable control generator tripping strategy proposed in the embodiment of the present application.

[0040] Optionally, the unit information of each generator set may include the active power P a output by the a-th generator in each generator set, the starting capacity S n of the n-th generator in each generator set, and the rated power P rate,a of the a-th generator in each generator set. Specifically, the surplus power P cut,total of a certain grid partition in the high-proportion new energy power system can be calculated by comprehensively considering the starting capacity, active power, rated power, and load of each generator in the corresponding generator set. The embodiment of the present application does not limit this. Among them, the surplus power P cut,total may refer to the active power that needs to be removed by the generator set in a certain grid partition, or may refer to the total generator tripping amount of the high-proportion new energy power system.

[0041] Step S202, obtain the frequency sensitivity coefficient and active power sensitivity coefficient of each generator set according to the unit information of each generator set.

[0042] The dual-sensitivity index can include a frequency sensitivity coefficient and an active power sensitivity coefficient. Among them, the frequency sensitivity coefficient can be used to reflect the support intensity of each generator set for frequency stability, and the active power sensitivity coefficient can be used to reflect the impact degree of generator tripping on frequency stability, so as to accurately quantify the contribution differences of various types of generators to frequency stability based on the aforementioned dual-sensitivity index, such as the inertia support ability of synchronous machines, the active power regulation potential of new energy, etc., and accurately distinguish the equipment characteristics, thereby avoiding the risk of frequency collapse caused by mis-tripping high-inertia generator sets.

[0043] The dual-sensitivity index is used to accurately quantify the contribution differences of various types of generators to frequency stability. The two indexes of the frequency sensitivity coefficient and the active power sensitivity coefficient are linearized indexes, which can be obtained by solving through the idea of small disturbances. Specifically, when a high-proportion new energy system runs to a certain preset state, the small fluctuations generated by the equipment power will cause small disturbances to the system frequency, or the small disturbances existing in the system frequency will cause small fluctuations to the power output by the equipment.

[0044] In some embodiments of the present application, relevant data of a high-proportion new energy power system when running to a preset state can be obtained based on the unit information. In the case where the small fluctuations generated by the equipment power cause small disturbances to the system frequency, the first frequency deviation change amount of each generator set and the active power change value output by each generator set due to the frequency change can be obtained, so as to calculate the frequency sensitivity coefficient of the corresponding generator set based on the obtained first frequency deviation change amount and active power change value; in the case where the small disturbances existing in the system frequency cause small fluctuations to the power output by the equipment, the power change amount of each generator set and the second frequency deviation change amount generated by each generator set due to the power fluctuation can be obtained, so as to calculate the active power sensitivity coefficient of the corresponding generator set based on the obtained power change amount and second frequency deviation change amount.

[0045] It should be noted that for the solution methods of the above two linearized indexes, the time-domain simulation method can be adopted, or the state equation method, the measured method, etc. can be adopted. The embodiments of the present application do not limit this.

[0046] Exemplarily, in the embodiments of the present application, taking the solution of the locally linearized index as an example, the specific calculation process can be as follows:

[0047] The frequency sensitivity coefficient of the i-th generator set The calculation formula can be as follows:

[0048]

[0049] In the formula, is the bus voltage frequency deviation change amount of the i-th generator set; is the i-th generator set due to frequency change The active power change value of the output caused thereby; the frequency sensitivity coefficient of the i-th generating unit , which represents the change in the active power output by the i-th generating unit under a unit frequency deviation and can be used to reflect the support strength of each generating unit for frequency stability. Among them, i = [1, 2, 3,..., N], N is the number of generating units in a certain power grid partition, and i is a positive integer.

[0050] The active sensitivity coefficient of the i-th generating unit The calculation formula of can be shown as follows:

[0051]

[0052] In the formula, is the power change amount of the i-th generating unit; is the frequency deviation change amount generated by the i-th generating unit due to power fluctuation ; the active sensitivity coefficient of the i-th generating unit , which represents the frequency change amount caused by the i-th generating unit under a unit generator tripping amount and can be used to reflect the influence degree of generator tripping on frequency stability. Among them, i is a positive integer, N is the number of generating units in a certain power grid partition, and i = [1, 2, 3,..., N].[[]END]]

[0053] It should be noted that for the active power change value , the frequency deviation change amount , and the surplus power change value , the calculation method can be a time-domain simulation method or can be obtained by solving through a frequency linearized analytical model in related technologies. The embodiments of the present application focus on obtaining the above double sensitivity indicators, and the specific solution method is not limited in the embodiments of the present application.

[0054] Step S203, obtain the generator tripping priority coefficient of each generating unit according to the frequency sensitivity coefficient and the active sensitivity coefficient of each generating unit.

[0055] In some embodiments of the present application, after obtaining the frequency sensitivity coefficient and the active sensitivity coefficient of all generating units, in order to determine the generator tripping amount allocation in the stability control generator tripping strategy, the generator tripping priority coefficient of each generating unit can be determined.

[0056] Optionally, the determined generator tripping priority coefficient can be used to indicate the generator tripping order of each generating unit. Specifically, the larger the generator tripping priority coefficient, the corresponding generating unit is preferentially retained; the smaller the generator tripping priority coefficient, the corresponding generating unit is preferentially tripped.

[0057] Specifically, the ratio of the frequency sensitivity coefficient to the active power sensitivity coefficient of each generating unit can be used as the unit tripping priority coefficient of each generating unit. Exemplarily, the unit tripping priority coefficient of the i-th generating unit can be calculated as follows:

[0058]

[0059] In the formula, is the frequency sensitivity coefficient of the i-th generating unit, is the active power sensitivity coefficient of the i-th generating unit. Among them, i = [1, 2, 3,..., N], N is the number of generating units in a certain power grid partition, and i is a positive integer.

[0060] Step S204: Obtain the preliminary unit tripping amount allocation results of each generating unit according to the unit tripping priority coefficients of each generating unit.

[0061] In some embodiments of the present application, each generating unit can be sorted in descending order according to the unit tripping priority coefficient to generate a unit tripping sequence, so as to indicate the unit tripping order of each generating unit based on the generated unit tripping sequence.

[0062] Optionally, the generating unit at the head of the unit tripping sequence can be the most prioritized unit to be retained, and the generating unit at the end of the unit tripping sequence can be the most prioritized unit to be tripped. Exemplarily, assuming that the unit tripping sequence generated according to the unit tripping priority coefficients of all generating units is [i1, i2, i3…i N , where i1 is the most prioritized unit to be retained, and i N is the most prioritized unit to be tripped, and N is the number of generating units in a certain power grid partition.

[0063] In the embodiments of the present application, the unit tripping amounts of each generating unit can be preliminarily allocated according to the unit tripping priority coefficients of each generating unit. Optionally, the allocation method can be manifested as setting a priority ratio according to the unit tripping order of each generating unit, and allocating the unit tripping amount to each generating unit based on the set priority ratio, so as to obtain the preliminary unit tripping amount allocation results. It should be noted that the allocated unit tripping amount can be reflected as the active power that needs to be tripped and allocated to each generating unit, which belongs to the excess part of the generated power.

[0064] Specifically, the priority ratio can be determined based on the machine cutting priority weight, and the priority weight is negatively correlated with the machine cutting priority coefficient. Specifically, the larger the machine cutting priority coefficient, the lower the set priority weight, so that the priority ratio determined based on the machine cutting priority weight is lower, and thus the machine cutting amount of the corresponding generator set is less, so that the corresponding generator set is retained first; the smaller the machine cutting priority coefficient, the higher the set priority weight, so that the priority ratio determined based on the machine cutting priority weight is higher, and thus the machine cutting amount of the corresponding generator set is more, so that the corresponding generator set is removed first.

[0065] In some embodiments of the present application, the total off-load capacity of the high-proportion new energy power system can be obtained, and the total off-load capacity is the surplus power P of the high-proportion new energy power system. cut,total At this time, the surplus power of the high-proportion new energy power system and the priority weight of each generator set can be used to calculate the preliminary shutdown amount of each generator set and obtain the preliminary shutdown amount allocation result.

[0066] For example, the shutdown capacity of each generator set is preliminarily allocated according to the set priority ratio, and the shutdown capacity P of the i-th generator set is preliminarily allocated. cut,i The calculation formula can be shown as follows:

[0067]

[0068] Where, P cut,total is the total power cut-off capacity of the high-proportion renewable energy power system, that is, the surplus power of the high-proportion renewable energy power system; is the priority weight of the i-th generator set, is the priority ratio set for the i-th generator set, where The higher, The lower, The lower the P cut,i The smaller the value, the more favorable it is for the i-th generator set to be retained in the generator cutting strategy. Where i=[1,2,3,...,N], N is the number of generator sets in a certain grid partition, and i is a positive integer.

[0069] Step S205 : constructing an objective function based on the preliminary shutdown allocation results of each generator set.

[0070] In an embodiment of the present application, a fairness optimization model can be constructed based on the Gini coefficient. On the basis of obtaining the preliminary machine-cutting quantity allocation result, the aforementioned preliminary machine-cutting quantity allocation result can be further optimized to achieve fairness optimization of the preliminary machine-cutting quantity allocation result and avoid a single unit from excessively bearing the machine-cutting task.

[0071] Specifically, an objective function can be constructed based on the preliminary generator tripping amount allocation results of each generator set. By optimizing the generator tripping amount allocation in the objective function, the fairness optimization of the preliminary generator tripping amount allocation results can be achieved.

[0072] The preliminary generator tripping amount allocation results of each generator set include the preliminary generator tripping amounts of each generator set. Optionally, the number of generators tripped in each generator set can be obtained, and the average generator tripping amount of each generator set can be calculated using the total generator tripping amount of the high-proportion new energy power system and the number of generators tripped in each generator set. Then, the objective function can be constructed using the average generator tripping amount of each generator set, the allocated generator tripping amount of each generator set, and the number of generators tripped in each generator set.

[0073] It should be noted that the number of generators tripped refers to the number of generators used to cut the power generation in each generator set, which can be specifically set according to the actual situation. For example, it can be determined according to the preliminary generator tripping amount of each generator set. When all the generators in a certain or certain generator sets participate in power cutting, the number of generators tripped can be understood as the number of generators included in that generator set. The embodiments of the present application do not limit this.

[0074] Exemplarily, the constructed objective function can be shown as follows:

[0075]

[0076] In the formula, G is the value of the objective function, which can be called the Gini coefficient; n is the number of generators tripped. Assuming that the i-th generator set contains a generators, n = [1, 2, 3,..., a], and a is a positive integer; μ is the average generator tripping amount, which represents the average generator tripping amount of each generator set. Specifically, ; All combinations of i and j are traversed, where i = [1, 2, 3,..., N], j = [1, 2, 3,..., N], N is the number of generator sets in a certain power grid partition, and i and j are positive integers.

[0077] Step S206: Optimize the Gini coefficient to obtain the target generator tripping amount allocation results of each generator set.

[0078] The optimization of the generator tripping amount allocation in the objective function can be manifested as optimizing the preliminary generator tripping amount in the objective function with the goal of minimizing the Gini coefficient, so as to obtain the adjusted generator tripping amount of each generator set. In practical applications, to balance the fairness of the generator tripping amount allocation, based on the principle of minimizing the Gini coefficient G, on the basis of the preliminary generator tripping amount of the initial allocation, the generator tripping amount is further optimized to obtain the secondary allocation generator tripping amount, that is, the adjusted generator tripping amount, and then the target generator tripping amount allocation results are obtained.

[0079] Optionally, during the optimization process, assume that the adjusted amount of generator tripping is , and the sum of the adjusted amounts of generator tripping for each generator set is equal to the total amount of generator tripping in the high-proportion new energy power system, that is, it satisfies ; and the adjusted amounts of generator tripping for each generator set are required to satisfy the tripping sequence, that is, to satisfy the sorting obtained by the above-mentioned double-sensitivity index analysis: , which is not limited in the embodiments of the present application.

[0080] In some embodiments of the present application, the adjusted amounts of generator tripping for each generator set can also be constrained by preset constraint conditions to obtain the target generator tripping amount allocation results for each generator set.

[0081] Among them, the preset constraint conditions can include sensitivity retention constraints and maximum type constraints. The sensitivity retention constraints can be used to limit the adjusted amounts of generator tripping for each generator set not to exceed a preset threshold to avoid excessive deviation from the frequency stability requirements; the maximum type constraints can be used to limit the maximum tripping capacity to reduce the loss risk of the generator set.

[0082] Exemplarily, the preset threshold of the adjusted amount of generator tripping can be determined based on the percentage of the preliminary amount of generator tripping, and the sensitivity retention constraint can be expressed as , where β is a percentage in decimal format. For example, when β = 1.2, it means that the adjusted amount of generator tripping is limited not to exceed 120% of the preliminary amount of generator tripping, so as to avoid excessive deviation from the frequency stability requirements.

[0083] As an example, for the synchronous machine type, its maximum type constraint can be expressed as ; as another example, for the new energy type, its maximum type constraint can be expressed as , where represents the rated capacity of the generator, and represents the maximum tripping capacity determined from factors such as protection equipment. It should be noted that the aforementioned 0.3 and 0.6 are for illustration, and different values can be set based on actual needs, which is not limited in the embodiments of the present application.

[0084] In practical applications, the objective function can be solved with the minimum Gini coefficient as the objective under the constraint conditions to obtain the adjusted amount of generator tripping. Optionally, the optimization solution of the objective function with the minimum Gini coefficient as the objective and based on the preset constraint conditions can be achieved by using linear programming to solve. It should be noted that the specific linear programming solution method is not limited in the embodiments of the present application.

[0085] After obtaining the adjusted generator tripping amounts for each generator unit, the generated power of the corresponding generator units can be cut according to the tripping sequence and the target generator tripping amount allocation result, achieving the collaborative optimization of frequency stability efficiency and tripping fairness, and providing a safer and more balanced stable control tripping solution for a high-proportion new energy power system.

[0086] In some embodiments of the present application, for the convenience of those skilled in the art to further understand the stable control method of the high-proportion new energy power system provided by the embodiments of the present application, the following description is given in combination with examples:

[0087] As Figure 1 shown, the high-proportion new energy power system includes N generator sets. Assuming that the number of generator sets N = 3, and in the case where each power generation group contains one generator, the types of generator sets and unit information are shown in Table 1 below:

[0088] Table 1 Types of generator sets and unit information

[0089]

[0090] Assuming that the surplus power of the high-proportion new energy power system composed of the generator sets shown in Table 1, that is, the total generator tripping amount = 100 MW. At this time, the frequency sensitivity coefficient, active power sensitivity coefficient, and generator tripping priority coefficient of generator set 1, generator set 2, and power generation group 3 in the high-proportion new energy power system can be calculated respectively.

[0091] As shown in Table 1 above, the generator type of generator set 1 is a hydropower type. Assuming that the primary frequency regulation control droop rate of the hydropower type generator, that is: where is the frequency deviation change amount (belonging to the per-unit value), is the mechanical power change amount (belonging to the per-unit value), and the rotor motion equation of generator set 1 can be: where H1 is the generator rotor inertia time constant, for example , is the mechanical power, is the electromagnetic power.

[0092] Exemplarily, in combination with the frequency response characteristics of the generator and according to the above definitions of the frequency sensitivity coefficient and the active power sensitivity coefficient, the calculation process of the frequency sensitivity coefficient M f,1 and the active power sensitivity coefficient M p,1 of generator set 1 can be as follows:

[0093]

[0094]

[0095] Among them, is a per-unit value and can be converted to a nominal value of .

[0096] As shown in Table 1 above, the generator type of generator set 2 is a grid-connected new energy source. Assuming that generator set 3 adopts a grid-connected control with inertia support and primary frequency modulation control, that is, on the basis of constant active power control, the reference value of new energy active power can be set to , where it is assumed that . , similar to a synchronous generator, at this time generator set 2 has an inertial response, and the virtual inertia parameter and droop coefficient of generator set 2 can be obtained. Among them, the virtual inertia parameter can be expressed as the frequency sensitivity coefficient M f,2 , and the droop coefficient can be expressed as the active sensitivity coefficient M p,2 . The specific calculation process is as follows:

[0097]

[0098]

[0099] Among them, is a per-unit value and can be converted to a nominal value of .

[0100] As shown in Table 1 above, the generator type of generator set 3 is a network-forming new energy source. Assuming that generator set 2 adopts virtual synchronous control (Virtual Synchronous Generator, abbreviated as VSG), VSG control can simulate the frequency response characteristics of a synchronous generator. At this time, it also has a virtual inertia parameter and a droop coefficient . Assuming that , , then, the frequency sensitivity coefficient M f,3 and the active sensitivity coefficient M p,3 of generator set 3 can be calculated as follows:

[0101]

[0102]

[0103] Among them, is a per-unit value and can be converted to a nominal value of .

[0104] After obtaining the frequency sensitivity coefficients and active power sensitivity coefficients of generator set 1, generator set 2, and generator set 3, the generator tripping priority coefficients of each of the aforementioned generator sets can be solved.

[0105] Exemplarily, according to the definition of the generator tripping priority coefficient above, the calculation process of the generator tripping priority coefficients of generator set 1, generator set 2, and generator set 3 can be shown as follows:

[0106] , ,

[0107] In the formula, Q1 is the generator tripping priority coefficient of generator set 1, Q2 is the generator tripping priority coefficient of generator set 2, and Q3 is the generator tripping priority coefficient of generator set 3.

[0108] Arrange the generator sets in descending order according to the generator tripping priority coefficients of each of the aforementioned generator sets. The generator tripping order of the above 3 generator sets can be expressed as generator 2, generator 3, and generator 1.

[0109] According to the calculation results of the priority coefficients of generator set 1, generator set 2, and generator set 3 preliminarily allocate the preliminary generator tripping amounts of generator set 1, generator set 2, and generator set 3 according to the set priority ratio.

[0110] Exemplarily, the generator tripping priority weights of generator set 1, generator set 2, and generator set 3 can be respectively: , , , then, the calculation process of the preliminary generator tripping amounts of generator set 1, generator set 2, and generator set 3 can be shown as follows:

[0111]

[0112]

[0113]

[0114] In the formula, P cut,1 is the preliminary generator tripping amount of generator set 1, P cut,2 is the preliminary generator tripping amount of generator set 2, P cut,3 is the preliminary generator tripping amount of generator set 3.

[0115] Optionally, taking the minimum Gini coefficient as the objective function, further optimize the preliminary generator tripping amounts of generator set 1, generator set 2, and generator set 3 in the high-proportion new energy power system.

[0116] Exemplarily, the objective function can be min G, where G is the Gini coefficient. For the optimization of the load shedding amount allocation of the above three generator sets, the foregoing formula can be equivalent to min ( ); assuming the preset constraint conditions are: (β = 1.2) and , , , at this time, under the preset constraint conditions, the initial load shedding amounts of generator set 1, generator set 2, and generator set 3 can be optimized with min G as the objective to obtain the adjusted load shedding amounts , where the adjusted load shedding amounts need to satisfy , and satisfy the sorting obtained based on the double sensitivity index analysis .

[0117] Solving the above linear constraint problem can obtain the optimal solution, that is, the adjusted load shedding amounts of the above three generator sets, which can be specifically expressed as: , , .

[0118] In the embodiment of the present application, by obtaining the unit information of each generator set including at least one type of generator in a high-proportion new energy power system, the frequency sensitivity coefficient and the active power sensitivity coefficient of each generator set are obtained according to the unit information of each generator set. Among them, the frequency sensitivity coefficient can be used to reflect the support intensity of each generator set for frequency stability, and the active power sensitivity coefficient can be used to reflect the influence degree of load shedding on frequency stability. By introducing the double indexes of frequency sensitivity and active power sensitivity, the limitation of a single index is broken through, the contribution differences of multiple types of generators to frequency stability are accurately quantified, and the risk of frequency collapse caused by mis-shedding high-inertia units is avoided; further, the load shedding priority coefficient of each generator set can be obtained according to the frequency sensitivity coefficient and the active power sensitivity coefficient of each generator set, the initial load shedding amount allocation result of each generator set is obtained according to the load shedding priority coefficient of each generator set, and then the objective function is constructed according to the initial load shedding amount allocation result of each generator set, and the value of the objective function, that is, the Gini coefficient, is optimized to optimize the load shedding amount allocation in the objective function based on the Gini coefficient, so as to obtain the target load shedding amount allocation result of each generator set, realize the fairness optimization of the initial load shedding amount allocation result, avoid a single unit from over-undertaking the load shedding task, reduce the loss risk of a single unit, and improve the long-term operation reliability of the system. The embodiment of the present application can realize the collaborative optimization of frequency stability efficiency and load shedding fairness, and provide a safer and more balanced load shedding control solution for a high-proportion new energy power system.

[0119] It should be noted that for the method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present application are not limited by the described action sequence, because according to the embodiments of the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential for the embodiments of the present application.

[0120] Referring to Figure 3 , a structural block diagram of a stable control device for a high-proportion new energy power system provided by an embodiment of the present application is shown, which may specifically include the following modules:

[0121] The unit information acquisition module 301 is configured to acquire the unit information of each generating unit in the high-proportion new energy power system; wherein, each generating unit includes at least one type of generator;

[0122] The sensitivity coefficient generation module 302 is configured to obtain the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit according to the unit information of each generating unit; wherein, the frequency sensitivity coefficient is used to reflect the support strength of each generating unit for frequency stability, and the active power sensitivity coefficient is used to reflect the influence degree of generator tripping on frequency stability;

[0123] The priority coefficient generation module 303 is configured to obtain the generator tripping priority coefficient of each generating unit according to the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit;

[0124] The preliminary allocation result generation module 304 is configured to obtain the preliminary generator tripping amount allocation result of each generating unit according to the generator tripping priority coefficient of each generating unit;

[0125] The objective function construction module 305 is configured to construct an objective function according to the preliminary generator tripping amount allocation result of each generating unit; the value of the objective function is the Gini coefficient;

[0126] The target allocation result generation module 306 is configured to optimize the Gini coefficient to obtain the target generator tripping amount allocation result of each generating unit.

[0127] In some embodiments of the present application, the sensitivity coefficient generation module 302 may include the following sub-modules:

[0128] A disturbance data acquisition sub-module, configured to obtain, based on the unit information, the first frequency deviation change of each generating unit and the active power change value of the output of each generating unit due to frequency change when the high-proportion new energy power system operates to a preset state, and / or, the power change of each generating unit and the second frequency deviation change generated by each generating unit due to power fluctuation;

[0129] A frequency sensitivity coefficient calculation sub-module, configured to calculate the frequency sensitivity coefficient of a generating unit by using the active power change value output by the generating unit and the first frequency deviation change of the generating unit; the frequency sensitivity coefficient represents the change amount of the active power output by the generating unit under a unit frequency deviation;

[0130] An active power sensitivity coefficient calculation sub-module, configured to calculate the active power sensitivity coefficient of a generating unit by using the second frequency deviation change of the generating unit and the power change of the generating unit; the active power sensitivity coefficient represents the frequency change amount caused by a unit amount of generator tripping.

[0131] In some embodiments of the present application, the priority coefficient generation module 303 may include the following sub-modules:

[0132] A priority coefficient calculation sub-module, configured to use the ratio of the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit as the generator tripping priority coefficient of each generating unit.

[0133] In some embodiments of the present application, the preliminary allocation result generation module 304 may include the following sub-modules:

[0134] A generator tripping amount allocation sub-module, configured to sort each generating unit in descending order according to the generator tripping priority coefficient of each generating unit to generate a generator tripping sequence; the generator tripping sequence is used to indicate the generator tripping order of each generating unit, where the generating unit located at the head of the generator tripping sequence is the unit to be preferentially retained, and the generating unit located at the end of the generator tripping sequence is the unit to be preferentially tripped; set a priority ratio according to the generator tripping order of each generating unit, and allocate the generator tripping amount to each generating unit based on the set priority ratio to obtain a preliminary generator tripping amount allocation result.

[0135] In some embodiments of the present application, the priority ratio is determined based on the generator tripping priority weight, and the priority weight is negatively correlated with the generator tripping priority coefficient; the preliminary generator tripping amount allocation result includes the preliminary generator tripping amount of each generating unit; the generator tripping amount allocation sub-module may include the following units:

[0136] A generator tripping amount calculation unit, configured to obtain the total generator tripping amount of the high-proportion new energy power system; the total generator tripping amount is the surplus power of the high-proportion new energy power system; calculate the preliminary generator tripping amount of each generating unit by using the surplus power and the priority weight of each generating unit.

[0137] In some embodiments of the present application, the preliminary generator tripping amount allocation results of each generator set include the preliminary generator tripping amounts of each generator set; the objective function construction module 305 may include the following sub-modules:

[0138] The objective function construction sub-module is configured to obtain the number of tripped generators of each generator set, and calculate the average tripping amount of each generator set by using the total tripping amount of the high-proportion new energy power system and the number of tripped generators of each generator set; and construct an objective function by using the average tripping amount of each generator set, the allocated tripping amount of each generator set, and the number of tripped generators of each generator set.

[0139] In some embodiments of the present application, the generator tripping priority coefficient is used to indicate the tripping order of each generator set; the target generator tripping amount allocation results include the adjusted generator tripping amounts of each generator set; the target allocation result generation module 306 may include the following sub-modules:

[0140] The allocation result optimization sub-module is configured to optimize the objective function with the goal of minimizing the Gini coefficient under preset constraint conditions, and solve to obtain the adjusted generator tripping amounts of each generator set; wherein, the sum of the adjusted generator tripping amounts of each generator set is equal to the total tripping amount of the high-proportion new energy power system, and the tripping order is satisfied.

[0141] In the embodiments of the present application, by obtaining the unit information of each generator set including at least one type of generator in the high-proportion new energy power system, the frequency sensitivity coefficient and the active power sensitivity coefficient of each generator set are obtained according to the unit information of each generator set. The frequency sensitivity coefficient can be used to reflect the support strength of each generator set for frequency stability, and the active power sensitivity coefficient can be used to reflect the influence degree of generator tripping on frequency stability. By introducing the dual indexes of frequency sensitivity and active power sensitivity, the limitation of a single index is broken through, the contribution differences of multi-type generators to frequency stability are accurately quantified, and the risk of frequency collapse caused by mis-tripping high-inertia units is avoided; further, the generator tripping priority coefficient of each generator set can be obtained according to the frequency sensitivity coefficient and the active power sensitivity coefficient of each generator set, the preliminary generator tripping amount allocation results of each generator set are obtained according to the generator tripping priority coefficient of each generator set, and then an objective function is constructed according to the preliminary generator tripping amount allocation results of each generator set, and the value of the objective function, that is, the Gini coefficient, is optimized to optimize the generator tripping amount allocation in the objective function based on the Gini coefficient, so as to obtain the target generator tripping amount allocation results of each generator set, realize the fairness optimization of the preliminary generator tripping amount allocation results, avoid a single unit from over-undertaking the generator tripping task, reduce the loss risk of a single unit, and improve the long-term operation reliability of the system. The embodiments of the present application can realize the collaborative optimization of frequency stability efficiency and generator tripping fairness, and provide a safer and more balanced stability control and generator tripping solution for the high-proportion new energy power system.

[0142] For the apparatus embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, please refer to the corresponding descriptions in the method embodiments.

[0143] The embodiments of the present application also provide an electronic device. Referring to Figure 4 , the provided electronic device 400 includes a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and capable of running on the processor 420. When the computer program 411 is executed by the processor, it implements each process of the above-mentioned method embodiment for the stable control of a high-proportion new energy power system and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0144] The embodiments of the present application also provide a computer-readable storage medium. Referring to Figure 5 , the computer-readable storage medium 500 stores a computer program 411. When the computer program 411 is executed by the processor, it implements each process of the above-mentioned method embodiment for the stable control of a high-proportion new energy power system and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0145] Each embodiment in this specification is described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the embodiments, reference can be made to each other.

[0146] It should be noted that the terms "first", "second", etc. in the description, claims and the above-mentioned drawings of the embodiments of the present application are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments described here can be implemented in an order different from that shown or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or modules does not necessarily have to be limited to those steps or modules clearly listed, but may include other steps or modules not clearly listed or inherent to these processes, methods, products or devices. The division of modules in the embodiments of the present application is only a logical division, and there may be other division methods in actual implementation. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed couplings or direct couplings or communication connections to each other may be through some interfaces, and the indirect couplings or communication connections between modules may be electrical or other similar forms, which are not limited in the embodiments of the present application. And the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed to multiple circuit modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present application.

[0147] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0148] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described system, device and module can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0149] In several embodiments provided by the embodiments of the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed to each other may be through some interfaces, and the indirect couplings or communication connections of the devices or modules may be electrical, mechanical or other forms.

[0150] The module described as a separation component may or may not be physically separated. The component shown as a module may or may not be a physical module, that is, it may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0151] In addition, in each embodiment of this application, each functional module can be integrated into a processing module, or each module can exist physically alone, or two or more modules can be integrated into one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0152] In the above embodiment, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product.

[0153] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from a website, computer, server, or data center to another website, computer, server, or data center in a wired (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a Solid State Disk (SSD)).

[0154] Embodiments of the present application are described with reference to the flowcharts and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal devices generate a device for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or in multiple blocks.

[0155] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or in multiple blocks; these computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable terminal device provide steps for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or in multiple blocks.

[0156] Although the preferred embodiments of the embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they know the basic creative concepts. Therefore, the appended claims are intended to be construed as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0157] Finally, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties. And the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0158] The above has introduced the technical solutions provided by the embodiments of the present application in detail. Specific examples are used in the embodiments of the present application to elaborate on the principles and implementation manners of the embodiments of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the embodiments of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the embodiments of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the embodiments of the present application.

Claims

1. A stable control method for a high-proportion new energy power system, characterized in that, The method includes: Obtaining the unit information of each generating unit in the high-proportion new energy power system; wherein, each generating unit includes at least one type of generator; Based on the unit information of each generating unit, obtaining the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit; wherein, the frequency sensitivity coefficient is used to reflect the support strength of each generating unit for frequency stability, and the active power sensitivity coefficient is used to reflect the influence degree of generator tripping on frequency stability; Based on the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit, obtaining the generator tripping priority coefficient of each generating unit; Based on the generator tripping priority coefficient of each generating unit, obtaining the preliminary generator tripping amount allocation result of each generating unit; Constructing an objective function based on the preliminary generator tripping amount allocation result of each generating unit; the value of the objective function is the Gini coefficient; Optimizing the Gini coefficient to obtain the target generator tripping amount allocation result of each generating unit.

2. The method according to claim 1, wherein The obtaining the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit based on the unit information of each generating unit includes: Based on the unit information, obtaining the first frequency deviation change amount of each generating unit and the active power change value of the output of each generating unit due to frequency change when the high-proportion new energy power system runs to a preset state, and / or, the power change amount of each generating unit and the second frequency deviation change amount generated by each generating unit due to power fluctuation; Using the active power change value of the output of the generating unit and the first frequency deviation change amount of the generating unit to calculate the frequency sensitivity coefficient of the generating unit; the frequency sensitivity coefficient represents the change amount of the active power output by the generating unit under unit frequency deviation; Using the second frequency deviation change amount of the generating unit and the power change amount of the generating unit to calculate the active power sensitivity coefficient of the generating unit; the active power sensitivity coefficient represents the frequency change amount caused by unit generator tripping amount.

3. The method according to claim 1, characterized in that, The obtaining the generator tripping priority coefficient of each generating unit based on the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit includes: Taking the ratio of the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit as the generator tripping priority coefficient of each generating unit.

4. The method according to claim 1 or 3, characterized in that, The obtaining the preliminary generator tripping amount allocation result of each generating unit based on the generator tripping priority coefficient of each generating unit includes: Sorting each generating unit in descending order according to the generator tripping priority coefficient of each generating unit to generate a generator tripping sequence; the generator tripping sequence is used to indicate the generator tripping order of each generating unit, wherein, the generating unit located at the head of the generator tripping sequence is the unit to be preferentially retained, and the generating unit located at the end of the generator tripping sequence is the unit to be preferentially tripped; Setting a priority ratio according to the generator tripping order of each generating unit, and allocating the generator tripping amount to each generating unit based on the set priority ratio to obtain the preliminary generator tripping amount allocation result.

5. The method according to claim 4, wherein The priority ratio is determined based on the load shedding priority weight, and the priority weight is negatively correlated with the load shedding priority coefficient; the preliminary load shedding amount allocation result is the preliminary load shedding amount of each generating unit; Allocating the load shedding amount to each generating unit based on the set priority ratio to obtain a preliminary load shedding amount allocation result, including: Obtaining the total load shedding amount of the high-proportion new energy power system; the total load shedding amount is the surplus power of the high-proportion new energy power system; Using the surplus power and the priority weights of each generating unit, calculating the preliminary load shedding amount of each generating unit.

6. The method according to claim 1, wherein The preliminary load shedding amount allocation result of each generating unit includes the preliminary load shedding amount of each generating unit; constructing an objective function according to the preliminary load shedding amount allocation result of each generating unit, including: Obtaining the number of load shedding units of each generating unit, and using the total load shedding amount of the high-proportion new energy power system and the number of load shedding units of each generating unit to calculate the average load shedding amount of each generating unit; Constructing an objective function using the average load shedding amount of each generating unit, the allocated load shedding amount of each generating unit, and the number of load shedding units of each generating unit.

7. The method according to claim 1 or 6, characterized in that The load shedding priority coefficient is used to indicate the load shedding order of each generating unit; the target load shedding amount allocation result is the adjusted load shedding amount of each generating unit; Optimizing the Gini coefficient to obtain the target load shedding amount allocation result of each generating unit, including: Under preset constraint conditions, taking the minimization of the Gini coefficient as the goal, optimizing and solving the objective function to obtain the adjusted load shedding amount of each generating unit; wherein, the sum of the adjusted load shedding amounts of each generating unit is equal to the total load shedding amount of the high-proportion new energy power system and satisfies the load shedding order.

8. A stable control device for a high-proportion new energy power system, characterized in that, The device includes: A unit information acquisition module, configured to acquire the unit information of each generating unit in the high-proportion new energy power system; wherein, each generating unit includes at least one type of generator; A sensitivity coefficient generation module, configured to obtain the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit according to the unit information of each generating unit; wherein, the frequency sensitivity coefficient is used to reflect the support strength of each generating unit for frequency stability, and the active power sensitivity coefficient is used to reflect the influence degree of load shedding on frequency stability; A priority coefficient generation module, configured to obtain the load shedding priority coefficient of each generating unit according to the frequency sensitivity coefficient and the active power sensitivity coefficient of each generating unit; A preliminary allocation result generation module, configured to obtain the preliminary load shedding amount allocation result of each generating unit according to the load shedding priority coefficient of each generating unit; An objective function construction module, configured to construct an objective function according to the preliminary load shedding amount allocation result of each generating unit; the value of the objective function is the Gini coefficient; A target allocation result generation module, configured to optimize the Gini coefficient to obtain the target load shedding amount allocation result of each generating unit.

9. An electronic device, characterized in that, Including: A processor, a memory, and a computer program stored on the memory and capable of running on the processor, wherein when the computer program is executed by the processor, it implements the stable control method of the high-proportion new energy power system according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, it implements the stable control method of the high-proportion new energy power system according to any one of claims 1 to 7.

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