A control method and device for a storage energy system participating in primary frequency modulation, and a medium

Abstract

The application provides a control method and device for energy storage system participating in primary frequency modulation and a medium. The control method for energy storage system participating in primary frequency modulation comprises the following steps: obtaining the current frequency of a power grid; when the difference between the current frequency of the power grid and the rated frequency of the power grid is greater than a preset frequency deviation, determining the inertial output and the droop output of the energy storage system according to the battery capacity of the energy storage system and the difference between the current frequency of the power grid and the rated frequency of the power grid; determining the inertial distribution coefficient and the droop distribution coefficient according to the difference between the current frequency of the power grid and the rated frequency of the power grid; determining the actual inertial output of the energy storage system according to the inertial output and the inertial distribution coefficient; determining the actual droop output of the energy storage system according to the droop output and the droop distribution coefficient; and controlling the energy storage system to modulate the frequency of the power grid according to the actual inertial output and the actual droop output. Through the application, smooth switching of the frequency modulation mode is realized, and overcharging and overdischarging of the energy storage system are avoided.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of electric power, and particularly relate to a control method, device and medium for a storage system participating in primary frequency modulation. BACKGROUND

[0002] The commonly used methods for battery storage participating in primary frequency modulation include virtual inertia control and droop control. The frequency change rate is large at the initial stage of load disturbance, and the frequency deviation is small, so the output of droop control alone cannot meet the frequency modulation demand, and the frequency deterioration speed is fast. The virtual inertia control can simulate the inertia response of the traditional synchronous generator, which corresponds to the process of releasing or absorbing kinetic energy of the generator rotor speed with the change of frequency, and can reduce the frequency change rate and the maximum frequency deviation at the initial stage of disturbance. However, during the process of the frequency deviation reaching the maximum value and gradually recovering to the steady-state deviation value, the frequency change rate polarity changes, and the inertia response output polarity also changes, which is opposite to the direction of frequency modulation demand, and is not conducive to the recovery of the grid frequency.

[0003] In the prior art, virtual inertia control is adopted in the frequency drop stage, and virtual droop control is adopted in the subsequent frequency recovery stage, and the maximum frequency deviation is used as the switching boundary. This comprehensive control mode to a certain extent coordinates the contradiction between the steady-state frequency deviation and the transient frequency drop speed and the maximum frequency deviation change rate, but the output control mode switching causes the jump of the storage battery from zero output to maximum output, which not only causes additional power and frequency change impact on the power grid, but also shortens the service life of the storage battery. SUMMARY

[0004] To realize smooth switching of the frequency modulation mode and avoid overcharging and overdischarging of the storage system, the present application provides a control method, device and medium for a storage system participating in primary frequency modulation.

[0005] In a first aspect, the present application provides a control method for a storage system participating in primary frequency modulation, which comprises:

[0006] obtaining the current frequency of the power grid;

[0007] when the difference between the current frequency of the power grid and the rated frequency of the power grid is greater than a preset frequency deviation, determining the inertia output and the droop output of the storage system according to the battery capacity of the storage system and the difference between the current frequency of the power grid and the rated frequency of the power grid;

[0008] determining the inertia distribution coefficient and the droop distribution coefficient according to the difference between the current frequency of the power grid and the rated frequency of the power grid;

[0009] determining the actual inertia output of the storage system according to the inertia output and the inertia distribution coefficient;

[0010] determining the actual droop output of the storage system according to the droop output and the droop distribution coefficient;

[0011] Control the frequency modulation of the energy storage system to the power grid according to the actual inertia output and the actual droop output.

[0012] Through the above method, when the difference between the current frequency of the power grid and the rated frequency of the power grid is greater than the preset frequency deviation, the energy storage system uses inertia control and droop control to modulate the frequency of the power grid, realizes smooth switching of the two frequency modulation modes (inertia control and droop control), avoids the jump of the energy storage system from zero output to maximum output when the energy storage system switches from inertia control to droop control, brings the impact of power and frequency change to the power grid, and at the same time, in combination with the battery capacity of the energy storage system, controls the output of the energy storage system to avoid the frequency secondary drop caused by overcharging and overdischarging of the energy storage system, and prolongs the service life of the energy storage system.

[0013] In combination with the first aspect, in a first embodiment of the first aspect, the inertia output and the droop output of the energy storage system are determined according to the battery capacity of the energy storage system and the difference between the current frequency of the power grid and the rated frequency of the power grid, comprising:

[0014] When the energy storage system is in a discharging state, and the battery capacity of the energy storage system is in a first preset range, the maximum value of the droop coefficient is selected as the current droop coefficient of the energy storage system.

[0015] The inertia output and the droop output of the energy storage system are determined according to the current droop coefficient and the difference between the current frequency of the power grid and the rated frequency of the power grid.

[0016] In combination with the first aspect or the first embodiment of the first aspect, in a second embodiment of the first aspect, the inertia output and the droop output of the energy storage system are determined according to the battery capacity of the energy storage system and the difference between the current frequency of the power grid and the rated frequency of the power grid, comprising:

[0017] When the energy storage system is in a charging state, and the battery capacity of the energy storage system is in a second preset range, the maximum value of the droop coefficient is selected as the current droop coefficient of the energy storage system.

[0018] The inertia output and the droop output of the energy storage system are determined according to the current droop coefficient and the difference between the current frequency of the power grid and the rated frequency of the power grid.

[0019] In combination with the first aspect, in a third embodiment of the first aspect, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, comprising:

[0020] When the difference between the current frequency of the power grid and the rated frequency of the power grid does not reach the maximum frequency deviation, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, and the inertia distribution coefficient is greater than the droop distribution coefficient.

[0021] With reference to the third embodiment of the first aspect, in a fourth embodiment of the first aspect, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, including:

[0022] When the difference between the current frequency of the power grid and the rated frequency of the power grid is equal to the maximum frequency deviation, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, and the inertia distribution coefficient is equal to the droop distribution coefficient.

[0023] With reference to the fourth embodiment of the first aspect, in a fifth embodiment of the first aspect, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, including:

[0024] When the difference between the current frequency of the power grid and the rated frequency of the power grid reaches the maximum frequency deviation, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, and the inertia distribution coefficient is less than the droop distribution coefficient.

[0025] With reference to the third embodiment of the first aspect, in a sixth embodiment of the first aspect, when the difference between the current frequency of the power grid and the rated frequency of the power grid does not reach the maximum frequency deviation, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, and the inertia distribution coefficient is greater than the droop distribution coefficient, including:

[0026]

[0027] Wherein a1 is the inertia distribution coefficient, b1 is the droop distribution coefficient, N is the distribution adjustment coefficient, Δf is the difference between the current frequency of the power grid and the rated frequency of the power grid, Δf min is the preset frequency deviation, and Δf max is the maximum frequency deviation.

[0028] With reference to the fifth embodiment of the first aspect, in a seventh embodiment of the first aspect, when the difference between the current frequency of the power grid and the rated frequency of the power grid reaches the maximum frequency deviation, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, and the inertia distribution coefficient is less than the droop distribution coefficient, including:

[0029]

[0030] Wherein a2 is the inertia distribution coefficient, b2 is the droop distribution coefficient, N is the distribution adjustment coefficient, Δf is the difference between the current frequency of the power grid and the rated frequency of the power grid, Δf min is the preset frequency deviation, and Δf max is the maximum frequency deviation.

[0031] In a second aspect, the present application also provides a computer device comprising a memory and a processor, the memory and the processor being communicatively connected, and the memory storing computer instructions, and the processor executing the computer instructions to perform the steps of the control method of the energy storage system participating in primary frequency modulation according to the first aspect or any one of the embodiments of the first aspect.

[0032] In a third aspect, the present application also provides a computer readable storage medium storing a computer program, and the computer program is executed by a processor to implement the steps of the control method of the energy storage system participating in primary frequency modulation according to the first aspect or any one of the embodiments of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed in the description of the embodiments or the prior art will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0034] Figure 1 is a flow chart of a control method of an energy storage system participating in primary frequency modulation according to an exemplary embodiment;

[0035] Figure 2 is a specific flow chart of a control method of an energy storage system participating in primary frequency modulation in an example;

[0036] Figure 3 is a flow chart of solving a mixed optimization objective function using a carnivorous plant algorithm in an example;

[0037] Figure 4 is a hardware structure schematic diagram of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0038] The technical solutions of the present application will be described in detail below with reference to the drawings. Obviously, the described embodiments are some embodiments of the present application, not all embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0039] In addition, the technical features involved in different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0040] In order to realize smooth switching of frequency modulation mode and avoid overcharging and over-discharging of the energy storage system, the present application proposes a control method, device and medium of an energy storage system participating in primary frequency modulation.

[0041] Figure 1 is a flow chart of a control method of a power storage system participating in primary frequency modulation according to an exemplary embodiment. As shown in the figure, the method comprises the following steps S101-S106. Figure 1

[0042] In step S101, the current frequency of the power grid is obtained.

[0043] In step S102, when the difference between the current frequency of the power grid and the rated frequency of the power grid is greater than the preset frequency deviation, the inertial output and the droop output of the power storage system are determined according to the battery capacity of the power storage system and the difference between the current frequency of the power grid and the rated frequency of the power grid.

[0044] In an optional embodiment, the rated frequency of the power grid is 50 Hz, and the preset frequency deviation is determined according to the actual situation of the power grid, which is not limited here.

[0045] In an optional embodiment, when the power storage system is in inertial control, the output of the power storage system is the inertial output; when the power storage system is in droop control, the output of the power storage system is the droop output. The inertial control has better suppression effect on the change rate of the difference between the current frequency of the power grid and the rated frequency of the power grid, while the droop control has better suppression effect on the difference between the current frequency of the power grid and the rated frequency of the power grid.

[0046] In an optional embodiment, the current droop coefficient is determined according to the battery capacity of the power storage system, and the droop output of the power storage system is determined by the current droop coefficient and the difference between the current frequency of the power grid and the rated frequency of the power grid.

[0047] In an optional embodiment, when the difference between the current frequency of the power grid and the rated frequency of the power grid is less than or equal to the preset frequency deviation, the power storage system does not participate in frequency modulation of the power grid.

[0048] In step S103, the inertial distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid.

[0049] In an optional embodiment, the inertial output of the power storage system is equal to the droop output, and the size of the inertial distribution coefficient represents the influence degree of the inertial output on the power system; the size of the droop distribution coefficient represents the influence degree of the droop output on the power system. The larger the distribution coefficient is, the greater the influence degree of the corresponding output on the power system is.

[0050] In an optional embodiment, when the difference between the current frequency of the power grid and the rated frequency of the power grid is different, the relative sizes of the inertial distribution coefficient and the droop distribution coefficient are different.

[0051] In step S104, the actual inertial output of the power storage system is determined according to the inertial output and the inertial distribution coefficient. ​

[0052] In step S105, the actual droop output of the energy storage system is determined according to the droop output and the droop allocation coefficient.

[0053] In step S106, the energy storage system is controlled to frequency modulation of the power grid according to the actual inertia output and the actual droop output.

[0054] Through the above method, when the difference between the current frequency of the power grid and the rated frequency of the power grid is greater than the preset frequency deviation, the energy storage system simultaneously uses inertia control and droop control to frequency modulation of the power grid, realizes the smooth switching of the two frequency modulation modes (inertia control and droop control), avoids the jump of the energy storage system from zero output to maximum output when the energy storage system switches from inertia control to droop control, brings the impact of power and frequency change to the power grid, and at the same time, in combination with the battery capacity of the energy storage system, controls the output of the energy storage system to avoid the frequency secondary drop caused by overcharging and overdischarging of the energy storage system, and prolongs the service life of the energy storage system.

[0055] In the process of frequency modulation of the energy storage system, in order to prevent the battery capacity of the energy storage system from triggering the locking device when it is out of limit, the active power of the energy storage system occurs step change, and then causes the frequency secondary drop and oscillation. Therefore, in the process of frequency modulation of the energy storage system, different current droop coefficients and current inertia coefficients are set according to the battery charging and discharging state and the battery capacity.

[0056] In the embodiment of the present application, the loglog activation function is used to calculate the current inertia coefficient and the current droop coefficient. Compared with the commonly used sigmoid function, in addition to the same monotonicity and concave-convex characteristics, it meets the adaptability of the current droop coefficient and the current inertia coefficient with the battery capacity (i.e. the current droop coefficient and the current inertia coefficient are larger when the battery capacity is higher, and the current droop coefficient and the current inertia coefficient are smaller when the battery capacity is lower), and it is about point symmetry, without using the segmented form, only one function is needed in the adaptive interval, the coordinate transformation and parameter setting are simple, and the function also has the advantages of saturation and fast convergence speed.

[0057] In an example, the step S102 determines the inertia output and the droop output of the energy storage system by the following steps:

[0058] First, when the energy storage system is in the discharging state, and the battery capacity of the energy storage system is in the first preset range, the maximum value of the droop coefficient is selected as the current droop coefficient of the energy storage system.

[0059] In an optional embodiment, when the energy storage system is in the discharging state, the current droop coefficient is realized by the following formula:

[0060]

[0061] wherein K D_dis is a current droop coefficient, K D_max is a maximum value of the droop coefficient, n is an adaptive coefficient, S SOC is a battery capacity of the energy storage system, (S dis_bound , S dis_max ] is a first preset range. When S SOC ∈ [S dis_bound , S dis_max ], the battery capacity is sufficient, and the droop coefficient takes the maximum value to preferentially ensure the frequency modulation effect; when S SOC ∈ [S dis_min , S dis_bound ], the energy storage system should consider both the battery capacity and the frequency modulation effect.

[0062] Then, the inertial output and the droop output of the energy storage system are determined according to the current droop coefficient, the difference between the current grid frequency and the rated grid frequency.

[0063] In an optional embodiment, the droop output of the energy storage system can be obtained by the following formula:

[0064] ΔP D = -K D Δf

[0065] wherein ΔP D is the droop output, K D is the current droop coefficient, and Δf is the difference between the current grid frequency and the rated grid frequency.

[0066] The calculation formula of the inertial output is:

[0067]

[0068] wherein ΔP I is the inertial output, and K I is the current inertial coefficient. In the embodiment of the present application, the current inertial coefficient can be determined according to the obtained droop output so that the inertial output is equal to the droop output.

[0069] In an example, the above step S102 can also determine the inertial output and the droop output of the energy storage system by the following steps, comprising:

[0070] First, when the energy storage system is in the charging state, and the battery capacity of the energy storage system is in the second preset range, the maximum value of the droop coefficient is selected as the current droop coefficient of the energy storage system.

[0071] In an optional embodiment, when the energy storage system is in the charging state, the current droop coefficient is realized by the following formula:

[0072]

[0073] Among them, K D_cha K represents the current droop coefficient. D_max The maximum value of the droop coefficient is n, where n is the adaptive coefficient, and S is the maximum value of the droop coefficient. SOC For the battery capacity of the energy storage system, [S cha_min S cha_bound [This refers to the second preset range.] When S SOc ∈[S cha_min S cha_bound When the battery capacity is insufficient, the droop coefficient is set to the maximum value to ensure that the battery capacity of the energy storage system recovers quickly; when S SOC ∈[S cha_bound S cha_max Energy storage systems should balance battery capacity and frequency regulation performance.

[0074] Then, based on the current droop coefficient and the difference between the current grid frequency and the grid rated frequency, the inertial output and droop output of the energy storage system are determined.

[0075] like Figure 2 As shown, in step S103 above, when the difference between the current frequency of the power grid and the rated frequency of the power grid has not reached the maximum frequency deviation, the power system frequency regulation requirement is mainly to suppress the rate of change of the difference between the current frequency of the power grid and the rated frequency of the power grid. Therefore, the actual inertial output should be greater than the actual droop output, that is, the inertial distribution coefficient should be greater than the droop distribution coefficient. At this time, the inertial distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid, and the specific formulas are as follows:

[0076]

[0077] Where a1 is the inertia distribution coefficient, b1 is the droop distribution coefficient, N is the distribution adjustment coefficient, and Δf is the difference between the current grid frequency and the grid rated frequency. min For the preset frequency deviation, Δf max This represents the maximum frequency deviation.

[0078] like Figure 2 As shown, in step S103 above, when the difference between the current frequency of the power grid and the rated frequency of the power grid is equal to the maximum frequency deviation, the inertia distribution coefficient and the droop distribution coefficient are determined according to the difference between the current frequency of the power grid and the rated frequency of the power grid. The inertia distribution coefficient is equal to the droop distribution coefficient, and at this time the actual inertial output is equal to the actual droop output.

[0079] like Figure 2As shown, in the step S103 above, when the difference between the current grid frequency and the rated grid frequency reaches the maximum frequency deviation, the power system frequency regulation requires to mainly suppress the difference between the current grid frequency and the rated grid frequency, therefore, the actual inertia output should be less than the actual droop output, i.e. the inertia distribution coefficient is less than the droop distribution coefficient. At this time, according to the difference between the current grid frequency and the rated grid frequency, the inertia distribution coefficient and the droop distribution coefficient are determined, and the specific formula is as follows:

[0080]

[0081] wherein a2 is the inertia distribution coefficient, b2 is the droop distribution coefficient, N is the distribution adjustment coefficient, Δf is the difference between the current grid frequency and the rated grid frequency, Δf min is the preset frequency deviation, and Δf max is the maximum frequency deviation.

[0082] The specific values of the inertia distribution coefficient and the droop distribution coefficient and their change speed are related to the distribution adjustment coefficient N. The current droop coefficient and the current inertia coefficient are related to the adaptive coefficient n. In an example, N and n are calculated by establishing a hybrid optimization objective function. The specific implementation steps are as follows:

[0083] First, the hybrid optimization objective function is established, and the specific formula is as follows:

[0084] I = I1 + I2 + I3 + I4

[0085] I1 = k1 [n(t) - n(t-1)]

[0086] I2 = k2 [N(t) - N(t-1)]

[0087]

[0088]

[0089] wherein I is the hybrid optimization objective function composed of I1, I2, I3 and I4, I1 is the objective function for the adaptive coefficient n to fluctuate within the allowed range, I2 is the objective function for the distribution adjustment coefficient N to fluctuate within the allowed range, I3 is the objective function for the change rate of the inertia distribution coefficient a, and I4 is the objective function for the change rate of the droop distribution coefficient b. k1, k2, k3 and k4 are calculation parameters.

[0090] Then, the constraint conditions of the hybrid optimization objective function are determined. For example, the change ranges of the current droop coefficient and the current inertia coefficient are both less than the respective maximum allowed values.

[0091] Finally, the Carnivorous Plant Algorithm (CPA) is used to optimize and solve the mixed optimization objective function, to obtain the adaptive coefficient and the distribution adjustment coefficient.

[0092] Figure 3 is a flowchart of solving the mixed optimization objective function by using the CPA, and the specific steps are as follows:

[0093] In step S301, the number of iterations within a group group_iter, the maximum number of iterations max_iter, the attraction rate attraction_rate, the growth rate growth_rate, the reproduction rate reproduction_rate, the number of carnivorous plants nCPlant, and the number of prey n Prey are defined.

[0094] In step S302, the population is initialized. A population with a size of n and a dimension of d is randomly generated. The position of each individual is represented by the following matrix.

[0095]

[0096] wherein Pop is the population, n is the sum of the number of carnivorous plants nCPlant and the number of prey n Prey, d is the dimension, i.e., the number of variables, in the embodiment of the present application, d is equal to 2, individual n，1 is the distribution adjustment coefficient, and individual n，2 is the adaptive coefficient. Each individual is randomly initialized using the following formula.

[0097] individual i，j =Lb j +(Ub j -Lb j )×rand

[0098] wherein Lb j and Ub j are the lower bound and the upper bound of the search domain, i.e., the minimum value and the maximum value of the independent variable, m∈[1, 2,..., n], j∈[1, 2,..., d], and rand is a random number between 1 and 0.

[0099] In step S303, the fitness value of each individual is calculated according to the mixed optimization objective function. For the mth individual, the fitness value is evaluated by taking each row (i.e., all dimensions) as the input of the fitness function, and the calculated fitness value is stored in the following matrix.

[0100]

[0101] where Fit is the fitness value matrix, and f is the fitness function value, i.e. the hybrid optimization objective function value.

[0102] In step S304, the carnivorous plants and prey are classified: each individual in the population is sorted in ascending order of fitness value, and the optimal individual g* is found as the first ranked carnivorous plant. The individuals ranked in the top nC Plant are classified as carnivorous plants, and the remaining n Prey individuals are classified as prey. The sorted fitness values and the population are as follows.

[0103]

[0104] where Sorted_Fit is the sorted fitness value matrix, and f CP is the fitness function value of the carnivorous plant, and f Prey is the fitness function value of the prey.

[0105]

[0106] where Sorted Pop is the sorted population matrix.

[0107] In step S305, the carnivorous plants and prey are grouped: in the grouping process, the prey with the highest fitness value is assigned to the first ranked carnivorous plant, and so on, with the second and third ranked prey belonging to the second and third ranked carnivorous plants, respectively. This process is repeated until the prey ranked nC Plant is assigned to the prey ranked n Prey, and the prey ranked nC Plant+1 is assigned to the first ranked carnivorous plant. Finally, there is only 1 carnivorous plant in each population, and the number of prey is greater than 2.

[0108] In step S306, the growth of the carnivorous plants and prey is simulated: CP i，j is the carnivorous plant ranked in the i-th position, and a prey Prey v，j is randomly selected from each population, and rand i，j is a randomly generated number between 0 and 1. The attraction rate and the random number of each population are compared until the number of group iterations group_iter is reached.

[0109] If the attraction rate is greater than the random number, a new carnivorous plant is formed according to the following formula.

[0110] NewCP i，j = growth × CP i，j + (1-growth) × Prey v，j

[0111] growth = growth_rate × randi，j

[0112] where growth is the attraction rate of the carnivorous plant CP i，j , growth_rate is a pre-set value of the attraction rate, and rand i，j is a random number.

[0113] If the attraction rate is less than the random number rand i，j , a new prey is formed according to the following formula, where Prey u，j is another prey randomly selected from the mth population.

[0114] NewPrey i，j = growth x Prey u，j + (1 - growth) x Prey v，j , u≠v

[0115]

[0116] where NewPrey i，j is the new prey.

[0117] In step S307, the reproduction process of the optimal carnivorous plant is simulated: only the first-ranked carnivorous plant, i.e., the best solution in the population, is allowed to reproduce. In the reproduction process, a carnivorous plant v is randomly selected for each dimension j, and the reproduction model of the optimal carnivorous plant is as follows: according to the formula, a new carnivorous plant is generated for each population based on the optimal carnivorous plant.

[0118] NewCP i，j = CP 1，j + Reproduction_rate x rand i，j x mate i，j

[0119]

[0120] where CP 1，j is the optimal solution, CP v，j is the randomly selected carnivorous plant, Reproduction_rate is the reproduction rate, and mate i，j is the mating value.

[0121] In step S308, the fitness of each newly generated carnivorous plant and prey is evaluated, and the fitness function is a hybrid optimization objective function.

[0122] In step S309, the newly generated carnivorous plants and prey are combined with the initial population to obtain a new population with a dimension of [n+nC Plantx(group_iter+nC Plant)]xd, i.e., the new population has n original individuals, (nC Plantxgroup_iter) newly generated individuals and (nC Plant) 2 newly reproduced individuals.

[0123] In step S310, each individual in the new population is sorted in ascending order according to the fitness value, and the top n individuals are selected into the next generation, i.e., the top n individuals are selected as new candidate solutions, ensuring that the population size remains unchanged.

[0124] In step S311, the current optimal individual g * is determined as the first ranked carnivorous plant, and the process proceeds to step S304 to repeat the simulation of the classification grouping, growth and reproduction of the carnivorous plant until the maximum number of iterations max_iter is reached.

[0125] In step S312, after the maximum number of iterations is reached, the current optimal solution g * is output, i.e., the optimal values of the adaptive coefficient and the adjustment parameter are output.

[0126] Figure 4 is a hardware structure diagram of a computer device according to an exemplary embodiment. As shown in Figure 4 , the device includes one or more processors 410 and a memory 420, which includes a persistent memory, a volatile memory and a hard disk, Figure 4 and the processor 410 is taken as an example. The device can also include an input device 430 and an output device 440.

[0127] The processor 410, the memory 420, the input device 430 and the output device 440 can be connected by a bus or other means, Figure 4 and the connection by the bus is taken as an example.

[0128] The processor 410 can be a central processing unit (CPU). The processor 410 can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic components, discrete hardware components, or a combination thereof. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0129] The memory 420, as a non-transitory computer-readable storage medium, includes a persistent memory, a volatile memory and a hard disk, and can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions / modules corresponding to the control method of the energy storage system participating in primary frequency modulation. The processor 410 executes various functions and data processing of the server by running the non-transitory software programs, instructions and modules stored in the memory 420, that is, implements any one of the above-mentioned control methods of the energy storage system participating in primary frequency modulation.

[0130] The memory 420 can include a program storage area and a data storage area. The program storage area can store an operating system and at least one application required by a function. The data storage area can store data required by the application. In addition, the memory 420 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory 420 can optionally include a memory remotely arranged with respect to the processor 410, and these remote memories can be connected to the data processing device through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0131] The input device 430 can receive input digital or character information, and generate signal input related to user settings and function control. The output device 440 can include a display device such as a display screen.

[0132] One or more modules are stored in the memory 420, and when executed by the one or more processors 410, perform the method as shown in Figure 1 .

[0133] The product can execute the method provided by the embodiment of the application, has the function module and beneficial effect corresponding to the execution method. The technical details not described in detail in the embodiment can be specifically referred to the related description in the embodiment shown in Figure 1

[0134] The embodiment of the application further provides a non-transient computer storage medium, and the computer storage medium stores computer executable instructions. The computer executable instructions can execute the control method in any method embodiment. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD), etc. The storage medium can also include a combination of the above-mentioned storage devices.

[0135] It should be noted that, in this document, relational terms such as“first” and“second”, and the like, are used solely to distinguish one entity or action from another entity or action, without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms“comprises”,“comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without more limitations, an element preceded by“comprises... a” does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0136] The above is only a specific embodiment of the application, which enables those skilled in the art to understand or implement the application. Various modifications of these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the application. Therefore, the application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features applied herein.​

Claims

1. A control method for an energy storage system participating in primary frequency regulation, characterized in that, The method includes: Obtain the current frequency of the power grid; When the difference between the current frequency of the power grid and the rated frequency of the power grid is greater than the preset frequency deviation, the inertial output and droop output of the energy storage system are determined based on the battery capacity of the energy storage system and the difference between the current frequency of the power grid and the rated frequency of the power grid. The inertia distribution coefficient and droop distribution coefficient are determined based on the difference between the current frequency of the power grid and the rated frequency of the power grid. The actual inertial output of the energy storage system is determined based on the inertial output and the inertial distribution coefficient. The actual droop output of the energy storage system is determined based on the droop output and the droop distribution coefficient. Based on the actual inertial output and the actual droop output, the energy storage system is controlled to regulate the frequency of the power grid; When the difference between the current frequency of the power grid and the rated frequency of the power grid does not reach the maximum frequency deviation, an inertia distribution coefficient and a droop distribution coefficient are determined based on the difference between the current frequency of the power grid and the rated frequency of the power grid. The inertia distribution coefficient is greater than the droop distribution coefficient, including: in, The inertia distribution coefficient, Where is the drooping distribution coefficient, and N is the distribution adjustment coefficient. The difference between the current frequency of the power grid and the rated frequency of the power grid. For the preset frequency deviation, This represents the maximum frequency deviation. When the difference between the current frequency and the rated frequency of the power grid reaches the maximum frequency deviation, an inertia distribution coefficient and a droop distribution coefficient are determined based on the difference between the current frequency and the rated frequency of the power grid. The inertia distribution coefficient is less than the droop distribution coefficient, including: in, The inertia distribution coefficient, Where is the drooping distribution coefficient, and N is the distribution adjustment coefficient. The difference between the current frequency of the power grid and the rated frequency of the power grid. For the preset frequency deviation, This represents the maximum frequency deviation.

2. The method according to claim 1, characterized in that, Based on the battery capacity of the energy storage system and the difference between the current frequency and the rated frequency of the power grid, the inertial output and droop output of the energy storage system are determined, including: When the energy storage system is in a discharging state and the battery capacity of the energy storage system is within the first preset range, the maximum value of the droop coefficient is selected as the current droop coefficient of the energy storage system. The inertial output and droop output of the energy storage system are determined based on the current droop coefficient and the difference between the current frequency and the rated frequency of the power grid.

3. The method according to claim 1 or 2, characterized in that, Based on the battery capacity of the energy storage system and the difference between the current frequency and the rated frequency of the power grid, the inertial output and droop output of the energy storage system are determined, including: When the energy storage system is in a charging state and the battery capacity of the energy storage system is within the second preset range, the maximum value of the droop coefficient is selected as the current droop coefficient of the energy storage system. The inertial output and droop output of the energy storage system are determined based on the current droop coefficient and the difference between the current frequency and the rated frequency of the power grid.

4. The method according to claim 1, characterized in that, Based on the difference between the current frequency and the rated frequency of the power grid, the inertia distribution factor and droop distribution factor are determined, including: When the difference between the current frequency of the power grid and the rated frequency of the power grid is equal to the maximum frequency deviation, the inertia distribution coefficient and the droop distribution coefficient are determined based on the difference between the current frequency of the power grid and the rated frequency of the power grid, and the inertia distribution coefficient is equal to the droop distribution coefficient.

5. A computer device, characterized in that, The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the steps of the control method for the energy storage system participating in primary frequency regulation as described in any one of claims 1-4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the control method for the energy storage system participating in primary frequency regulation as described in any one of claims 1-4.

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