A photovoltaic power generation participates in primary frequency modulation intelligent optimization power distribution control method

Abstract

The application discloses an intelligent optimization power distribution control method for photovoltaic power generation participating in primary frequency modulation, which comprises the following steps: firstly, judging according to a predetermined frequency modulation dead zone, if the system frequency exceeds the dead zone range, starting the algorithm; secondly, processing the collected relevant data, and calculating the frequency modulation target value by using a primary frequency modulation droop control formula; finally, judging whether the frequency modulation needs to be regulated by increasing power or by reducing power, and solving the predetermined target function by using an artificial operation algorithm, and finally, the obtained solution is used as an instruction to be issued to each inverter.

Description

Technical Field

[0001] This invention belongs to the field of power system technology, and more specifically, relates to an intelligent optimized power distribution control method for photovoltaic power generation participating in primary frequency regulation. Background Technology

[0002] With the reduction in the proportion of conventional hydropower and thermal power, the spinning reserve capacity is significantly weak, making it increasingly difficult and economically burdensome to maintain the frequency stability of a high-proportion renewable energy grid by relying on traditional frequency regulation methods. Currently, the power system clearly requires wind farms and photovoltaic power stations to have primary frequency regulation capabilities, and the primary frequency regulation function must be always engaged and ensured to operate normally during grid connection.

[0003] In pursuit of maximum power point operation (MPPT), renewable energy manufacturers are unwilling to provide active power reserves, resulting in renewable energy power plants being unable to provide auxiliary services such as frequency regulation similar to traditional units when the system frequency drops. Therefore, if photovoltaic power plants are to participate in frequency regulation when the system frequency drops, they must improve their active power allocation strategies and switch power control methods in a timely manner when participating in frequency regulation during system frequency drops.

[0004] For active power allocation strategies in photovoltaic (PV) power plants, the most commonly used basic methods are average allocation, fixed-ratio allocation, and variable-ratio allocation. Average allocation is dominant, but it fails to account for the varying power generation capacities of different inverters due to their different locations within the PV power plant, potentially leading to significant errors. Ratio allocation, on the other hand, considers the varying power generation capacities of each inverter and avoids errors during the allocation process, but it requires calculating the maximum power output of each individual inverter, resulting in a large computational load. Furthermore, neither average nor ratio allocation considers the impact of the inverter's operating status on the allocation results.

[0005] Existing allocation strategies that take into account the inverter's operating status are often improved based on average or proportional allocation, classifying the inverter into normal operating status, normal shutdown status, and communication failure status, etc. This approach compensates for the allocation error caused by the difference in inverter operating status. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide an intelligent optimized power distribution control method for photovoltaic power generation to participate in primary frequency regulation, so as to enable photovoltaic power plants to actively participate in primary frequency regulation and thus maintain the stability of the power system frequency.

[0007] To achieve the above-mentioned objectives, the present invention provides an intelligent optimized power distribution control method for photovoltaic power generation participating in primary frequency regulation, characterized by comprising the following steps:

[0008] (1) Set the frequency regulation dead zone range (f) for photovoltaic power plants to participate in primary frequency regulation. d1 ,f d2 ), where f d1 f d2 These are the upper and lower limits of the FM dead zone;

[0009] (2) Collect the frequency of the photovoltaic power station on the grid-connected side at the current time t, denoted as f. t Determine f t If it is within the frequency modulation dead zone, then no frequency modulation is needed at the current time t, and the process ends; otherwise, proceed to step (3).

[0010] (3) Based on the actual conditions of the photovoltaic power station, set the minimum starting power P for each photovoltaic inverter. miv,min ;

[0011] In a photovoltaic power station, the output power of each photovoltaic inverter is considered. If the output power of a certain photovoltaic inverter is equal to the minimum starting power P... miv,min If the condition is met, the photovoltaic inverter is determined to be in standby mode; otherwise, the photovoltaic inverter is determined to be in MPPT operation mode.

[0012] Count the number N2 of photovoltaic inverters that are in the off state, and record the number and standby time of each photovoltaic inverter;

[0013] Count the number N1 of photovoltaic inverters in MPPT operation state, and record the output power, number and running time of each photovoltaic inverter;

[0014] (4) Calculate the total output power P of the photovoltaic power station at the current time t. t ;

[0015]

[0016] Where, p i,t This represents the output power of the i-th photovoltaic inverter in MPPT operation at time t;

[0017] (5) Sort the standby time and running time of the photovoltaic inverters in ascending order respectively;

[0018] After sorting all photovoltaic inverters in MPPT operation state in ascending order according to their operating time, the result is represented by array T1 as follows:

[0019]

[0020] Among them, t i This represents the operating time of the i-th photovoltaic inverter in MPPT operation state;

[0021] After sorting all photovoltaic inverters in standby mode in ascending order according to their standby time, the result is represented by array T2 as follows:

[0022]

[0023] Among them, t j This indicates the standby duration of the j-th photovoltaic inverter, which is in standby mode.

[0024] (6) Set the upper limit of the power generation of each photovoltaic inverter;

[0025] Sort all photovoltaic inverters in MPPT operation state by output power in ascending order, then select the photovoltaic inverter in the middle position as the sample inverter, and denote the output power of the sample inverter at time t as the maximum power generation P of each photovoltaic inverter. miv,max ,Right now:

[0026]

[0027] (7) Estimate the maximum power generation P of the photovoltaic power station at time t. MPPT,t ;

[0028] P MPPT,t = (N1+N2)*P miv,max

[0029] (8) Calculate the primary frequency regulation target value P of the photovoltaic power station at the next moment using the primary frequency regulation droop control function. t+1 ;

[0030] P t+1 =P t -k(f t -f d )

[0031]

[0032]

[0033] Among them, f d For the frequency modulation dead zone boundary value, if f t >f d2 Then f d =f d2 Otherwise, f d =f d1 ;f ref The rated frequency of the power grid; k is the droop characteristic parameter, k * δ is the droop ratio, and δ is the droop coefficient of the primary frequency modulation.

[0034] (9) Calculate the target value ΔP1(t) of the photovoltaic power station at time t;

[0035] ΔP1(t)=P t+1 -P miv,t

[0036] (10) Establish the objective function and constraints for the photovoltaic power station to participate in primary frequency regulation based on ΔP1(t);

[0037] The objective function is:

[0038]

[0039] Among them, P i_ref The target output power of the i-th photovoltaic inverter after the photovoltaic power station participates in frequency regulation is represented, and N represents the number of photovoltaic inverters in operation after the photovoltaic power station participates in frequency regulation.

[0040] The constraints are:

[0041]

[0042] (11) Photovoltaic power plants participate in primary frequency regulation;

[0043] (11.1) Calculate the primary frequency regulation target value P of the photovoltaic power station. t+1 The total output power P at the current time t t The deviation ΔP2(t):

[0044] ΔP2(t)=P t+1 -P t

[0045] (11.2) Compare the magnitude of ΔP2(t) with 0. If ΔP2(t) > 0, then adopt the power increase strategy and proceed to step (11.3); otherwise, adopt the power decrease strategy and proceed to step (11.4).

[0046] (11.3) Compare ΔP2(t) with P miv,t The magnitude of ΔP2(t) is determined by the fact that ΔP2(t) > P. miv,t If so, in array T2, turn on N3 standby photovoltaic inverters in sequence, and then proceed to step (12); otherwise, in array T2, turn on one standby photovoltaic inverter in sequence, and then proceed to step (12).

[0047] (11.4) Among the N1 photovoltaic inverters, after removing the sample photovoltaic inverters, calculate the mean value of ΔP1(t).

[0048]

[0049] (11.5), judgment Does it meet the following requirements: like If the condition is met, proceed directly to step (12); otherwise, proceed to step (11.6).

[0050] (11.6) In array T1, sequentially change one photovoltaic inverter in the running state to the standby state, then update the number of photovoltaic inverters in the running state in array T1, N1 = N1-1, and at the same time update ΔP1(t) = ΔP1(t)-p κ,t , where p κ,t This represents the output power of the κth photovoltaic inverter that has been switched to standby mode and is currently in operation at time t; after the update is complete, return to step (11.4);

[0051] (12) The objective function of the photovoltaic power station participating in primary frequency regulation is solved using the artificial fish swarm algorithm, and the target output power P of the photovoltaic inverter in operation after the photovoltaic power station participates in frequency regulation is obtained. i_ref The control terminal of the photovoltaic power station issues corresponding power commands to each photovoltaic inverter according to the target output power of each inverter, thus completing one frequency regulation.

[0052] The objective of this invention is achieved as follows:

[0053] This invention discloses an intelligent optimized power distribution control method for photovoltaic power generation participating in primary frequency regulation. First, a judgment is made according to the predefined frequency regulation dead zone. If the system frequency exceeds the dead zone range, the algorithm is started. Second, the collected relevant data is processed, and the frequency regulation target value is calculated using the primary frequency regulation droop control formula. Finally, it is determined whether the frequency regulation needs to be adjusted by increasing or decreasing power, and the predefined target function is solved using a manual algorithm. Finally, the obtained solution is sent as an instruction to each inverter.

[0054] Meanwhile, the intelligent optimized power distribution control method for photovoltaic power generation participating in primary frequency regulation of the present invention also has the following beneficial effects:

[0055] (1) When the system frequency fluctuates and does not meet the power quality requirements, the photovoltaic power station needs to participate in primary frequency regulation. However, at the internal control level of the photovoltaic power station, each sub-unit of the photovoltaic power station usually uses the maximum power point tracking (MPPT) operating mode, which means that the photovoltaic power station does not have the active power reserve capacity to participate in the primary frequency regulation of the power system. In order to enable the photovoltaic power station to have frequency regulation function, this method stipulates that when the photovoltaic power station participates in the primary frequency regulation of the system, the control strategy of some photovoltaic inverters inside the photovoltaic power station can be improved, switching back and forth between MPPT mode and rated power mode to cope with the power increase or decrease corresponding to the participation in the system frequency regulation.

[0056] (2) The present invention specifies the selection of sample inverters in the algorithm, which solves the defect that the average allocation strategy does not take into account the maximum power generation capacity of the inverter.

[0057] (3) Considering that traditional allocation methods do not take into account the error problem of allocation results, this invention uses the artificial fish swarm algorithm to solve the minimum error function and obtain a suitable instruction value. Attached Figure Description

[0058] Figure 1 This is a flowchart of an intelligent optimized power allocation control method for photovoltaic power generation participating in primary frequency regulation according to the present invention;

[0059] Figure 2 This is a flowchart of the dispatch center's rapid frequency response process for initiating a photovoltaic power station.

[0060] Figure 3 This is a flowchart of the artificial fish swarm algorithm for solving the objective function;

[0061] Figure 4 Comparison chart of frequency variations in power systems;

[0062] Figure 5 This is a comparison chart of the output power of photovoltaic power plants. Detailed Implementation

[0063] The specific embodiments of the present invention will now be described with reference to the accompanying drawings to enable those skilled in the art to better understand the invention. It should be particularly noted that in the following description, detailed descriptions of known functions and designs that might obscure the main content of the invention will be omitted here.

[0064] Example

[0065] Figure 1 This is a flowchart of an intelligent optimized power distribution control method for photovoltaic power generation participating in primary frequency regulation according to the present invention.

[0066] In this embodiment, as Figure 1 As shown, the present invention provides an intelligent optimized power allocation control method for photovoltaic power generation participating in primary frequency regulation, comprising the following steps:

[0067] (1) Set the frequency regulation dead zone range (f) for photovoltaic power plants to participate in primary frequency regulation. d1 ,f d2 ), where f d1 f d2 The upper and lower limits of the frequency modulation dead zone are defined as follows: In this embodiment, the frequency modulation dead zone range is set to (49.90, 50.10), with the unit being Hz.

[0068] (2) Collect the frequency of the photovoltaic power station on the grid-connected side at the current time t, denoted as f. tDetermine f t If it is within the frequency modulation dead zone, then no frequency modulation is needed at the current time t, and the process ends; otherwise, proceed to step (3).

[0069] In this embodiment, as Figure 2 As shown, before the photovoltaic power station's fast frequency response device is activated, the power distribution within the photovoltaic power station is handled by the energy management platform. When the dispatch center determines that the acquired frequency data exceeds the dead zone range of the active power-frequency droop control, it issues a network communication command to the fast frequency response device, and the primary frequency regulation algorithm begins to run.

[0070] (3) Based on the actual conditions of the photovoltaic power station, set the minimum starting power P for each photovoltaic inverter. miv,min In this embodiment, P miv,min It is 10kW;

[0071] When a photovoltaic power plant is not participating in the primary frequency regulation of the system, some photovoltaic inverters are in standby mode, while the remaining photovoltaic inverters generate electricity according to the MPPT (Minimum Power Response Time) mode. Therefore, we determine the status by measuring the output power of each photovoltaic inverter. If the output power of a certain photovoltaic inverter is equal to the minimum starting power P... miv,min If the condition is met, the photovoltaic inverter is determined to be in standby mode; otherwise, the photovoltaic inverter is determined to be in MPPT operation mode.

[0072] Count the number N2 of photovoltaic inverters in standby mode, and record the number and standby duration of each photovoltaic inverter;

[0073] Count the number N1 of photovoltaic inverters in MPPT operation state, and record the output power, number and running time of each photovoltaic inverter;

[0074] In this embodiment, the value of N2 is 46 and the value of N1 is 8. Table 1, which records the initial output power and number of the inverter in MPPT operation state, is as follows:

[0075] 1 915 600 2 925 610 3 905 550 4 925 590 5 925 620 6 935 570 7 925 580 8 945 560

[0076] Table 1(4) Calculate the total output power P of the photovoltaic power station at the current time t. t ;

[0077]

[0078] Where, p i,t The output power of the i-th photovoltaic inverter in MPPT operation state at time t is represented; from the table of inverter power recorded in step (3) and the above formula, the total output power of the photovoltaic power station at the current time t in this embodiment is 7.4MW.

[0079] (5) Sort the standby time and running time of the photovoltaic inverters in ascending order respectively;

[0080] After sorting all photovoltaic inverters in MPPT operation state in ascending order according to their operating time, the result is represented by array T1 as follows:

[0081]

[0082] Among them, t i This represents the runtime of the i-th photovoltaic inverter in MPPT operation state; after sorting all photovoltaic inverters in standby state in ascending order according to their standby time, it is represented by array T2 as follows:

[0083]

[0084] Among them, t j This indicates the standby time of the j-th photovoltaic inverter that is in a shutdown state;

[0085] In this embodiment, time data and inverter number are grouped together and stored in a hash table for easy retrieval and use.

[0086] (6) Set the upper limit of the power generation of each photovoltaic inverter;

[0087] Sort all photovoltaic inverters in MPPT operation state by output power in ascending order, then select the photovoltaic inverter in the middle position as the sample inverter, and denote the output power of the sample inverter at time t as the maximum power generation P of each photovoltaic inverter. miv,max ,Right now:

[0088]

[0089] In this embodiment, the upper and lower limits of the photovoltaic inverter's power generation range are (10, 925), with the unit being kW.

[0090] (7) Estimate the maximum power generation P of the photovoltaic power station at time t. MPPT,t ;

[0091] P MPPT,t = (N1+N2)*P miv,max

[0092] In this embodiment, the maximum power generation capacity of the photovoltaic power station is 50MW.

[0093] (8) Calculate the primary frequency regulation target value P of the photovoltaic power station at the next moment using the primary frequency regulation droop control function. t+1 ;

[0094] P t+1 =Pt -k(f t -f d )

[0095]

[0096]

[0097] Among them, f d For the frequency modulation dead zone boundary value, if f t >f d2 Then f d =f d2 Otherwise, f d =f d1 ;f ref The rated frequency of the power grid; k is the droop characteristic parameter, k * δ% represents the droop ratio, and δ% represents the droop coefficient of the primary frequency modulation.

[0098] In this embodiment, the primary frequency modulation droop coefficient δ% is specified as 4, then the droop ratio k * The value is 25, and the droop characteristic parameter k is 25.

[0099] (9) Calculate the target value ΔP1(t) of the photovoltaic power station at time t;

[0100] ΔP1(t)=P t+1 -P miv,t

[0101] In this embodiment, the allocation target value is 4MW.

[0102] (10) Establish the objective function and constraints for the photovoltaic power station to participate in primary frequency regulation based on ΔP1(t);

[0103] The objective function is:

[0104]

[0105] Among them, P i_ref The target output power of the i-th photovoltaic inverter after the photovoltaic power station participates in frequency regulation is represented, and N represents the number of photovoltaic inverters in operation after the photovoltaic power station participates in frequency regulation.

[0106] The constraints are:

[0107]

[0108] (11) Photovoltaic power plants participate in primary frequency regulation;

[0109] (11.1) Calculate the primary frequency regulation target value P of the photovoltaic power station. t+1 The total output power P at the current time tt The deviation ΔP2(t):

[0110] ΔP2(t)=P t+1 -P t

[0111] (11.2) Compare the magnitude of ΔP2(t) with 0. If ΔP2(t) > 0, then adopt the power increase strategy and proceed to step (11.3); otherwise, adopt the power decrease strategy and proceed to step (11.4).

[0112] (11.3) Compare ΔP2(t) with P miv, The magnitude of t, if ΔP2(t)>P miv,t If N3 standby photovoltaic inverters are turned on sequentially in array T2, then proceed to step (12); otherwise, one standby photovoltaic inverter is turned on sequentially in array T2, then proceed to step (12); where N3 satisfies:

[0113] N3=ΔP2 / P miv_max +1

[0114] (11.4) Among the N1 photovoltaic inverters, after removing the sample photovoltaic inverters, calculate the mean value ΔP1(t) of ΔP1(t);

[0115]

[0116] (11.5), judgment Does it meet the following requirements: like If the condition is met, proceed directly to step (12); otherwise, proceed to step (11.6).

[0117] (11.6) In array T1, sequentially change one photovoltaic inverter in the running state to the standby state, then update the number of photovoltaic inverters in the running state in array T1, N1 = N1-1, and at the same time update ΔP1(t) = ΔP1(t)-p κ,t , where p κ,t This represents the output power of the κth photovoltaic inverter that has been switched to standby mode and is currently in operation at time t; after the update is complete, return to step (11.4);

[0118] (12) The objective function of the photovoltaic power station participating in primary frequency regulation is solved using the artificial fish swarm algorithm, and the target output power P of the photovoltaic inverter in operation after the photovoltaic power station participates in frequency regulation is obtained. i_ref The control terminal of the photovoltaic power station issues corresponding power commands to each photovoltaic inverter according to the target output power of each inverter, thus completing one frequency regulation.

[0119] Among them, such as Figure 3 As shown, the specific process of solving the objective function using the artificial fish swarm algorithm is as follows:

[0120] (12.1) The objective function and constraints of step (10) are used as the objective function and constraints of the artificial fish swarm algorithm. The inverter power command P obtained in step (11) participating in the primary frequency regulation of the photovoltaic power station is used. i_ref As the optimization variable for the artificial fish swarm algorithm, i = 1, 2, ..., N, where N is the number of photovoltaic inverters in operation after the photovoltaic power station participates in frequency regulation;

[0121] (12.2) Setting the parameters of the artificial fish swarm algorithm: In an N-dimensional search space, the state of an individual artificial fish is represented by a vector X = (P 1_ref ,P 2_ref ,…,P i_ref ,…,P N_ref ), where P i_ref Let X be the independent variable to be optimized, and let X be the state vector when the power command independent variable takes different values;

[0122] The food concentration at the current location of the artificial fish is represented by Y = f(X), where f(X) is the objective function; the distance between individual artificial fish is represented by d = ||X||. i -X j ||;

[0123] Set visual to the perception range of the artificial fish, Step to the step size of the artificial fish, δ to the crowding factor; trynumber to the maximum number of attempts the artificial fish makes each time it forages for food, and set the size of the artificial fish swarm to N;

[0124] In this embodiment, the parameters of the artificial fish swarm algorithm are shown in Table 2;

[0125] Number of artificial fish N 100 Perceived Distance 2.5 Maximum number of iterations MAXGEN 50 Crowding factor 0.618 Maximum number of iterations for foraging (trynumber) 100 Movement step size 0.3

[0126] Table 2

[0127] (12.3) Start traversing each artificial fish, and optimize each artificial fish according to the constraints and different behaviors of the artificial fish swarm algorithm. If the fitness value of the current artificial fish is better than the historical best value, then replace the historical best value with the currently optimized value.

[0128] The artificial fish swarm algorithm has the following behavior:

[0129] Foraging behavior: refers to the behavior of fish swimming towards areas with abundant food. (Artificial fish X) i Randomly select a state X within its field of vision j Calculate their objective functions separately and compare them. If Y is found to be... j Compared to Yi Excellent (Y) j and Y i X j and X i (the fitness value), then X i To X j Move one step in the direction of X; otherwise, X i Continue selecting state X within its field of view. j Determine if the moving condition is met. If the moving condition is not met after trying `trynumber` times, then move X one step randomly. i A new state has been reached. The expression is as follows:

[0130] X j =X i +rand()*visual

[0131]

[0132] X next =X i +rand()*step

[0133] Schooling behavior: Fish naturally gather in groups while swimming to ensure their survival and avoid harm. (Artificial fish X) i Search within its field of vision (d) ij The number of partners n (visual) f and center position X c If Y c / n f <δY i (Use the less than sign when finding the minimum value, and the opposite when finding the maximum value; Y) c and Y i X c and X i The fitness value indicates that the partner center position is in a better state and less crowded, then X i Move one step toward the center of your companions; otherwise, perform foraging behavior.

[0134]

[0135] Tail-chasing behavior: refers to the behavior of a fish moving in the optimal direction within its field of vision. (Artificial fish X) i Search within its field of vision (d) ij The individual with the highest fitness (visual) X j Its fitness value is Y j And explore artificial fish X j The number of partners within the field of vision n f If Y j / n f<δY i This indicates that X j If the condition is favorable and not too crowded, then X i Chao X j Move one step to the new location; otherwise, perform foraging behavior.

[0136]

[0137] During the algorithm's operation, both swarming and tail-chasing behaviors are performed simultaneously. Foraging behavior is the action chosen by the artificial fish when excessive crowding is detected near either swarming or tail-chasing targets. If no artificial fish with higher fitness is found during foraging, the fish moves randomly by a step size. Finally, the fitness values ​​obtained from swarming and tail-chasing behaviors are compared, and the best artificial fish are selected for the next generation. Therefore, by combining the modules of the artificial fish swarm algorithm described above with the defined objective function and constraints, the optimal solution can be obtained, yielding the power command for N inverters.

[0138] Simulation verification

[0139] To verify the effectiveness of the primary frequency regulation optimized power allocation strategy for photovoltaic power generation proposed in the above invention, the contents of the invention, excluding step 9, were verified at a photovoltaic power station in Southwest China. The standard environment for the photovoltaic power station was 1000 W / m². 2 The photovoltaic cell temperature is 25℃, and the capacity is 50MW. There are 54 sub-unit inverters, one of which is shut down due to a fault. The initial output is 7.4MW. The environmental conditions do not change within the specified simulation time.

[0140] During normal operation, the system frequency is 50Hz. At the 60s simulation time, a frequency disturbance is introduced, and the changes in system frequency and photovoltaic power plant output power are observed. Different control strategies are used to simulate and compare the frequency regulation effects. A comparison graph of power system frequency changes is shown below. Figure 4 As shown in the diagram, a comparison of the output power of photovoltaic power plants is presented. Figure 5 As shown.

[0141] Depend on Figure 4 It can be seen that when the photovoltaic power station does not participate in the primary frequency regulation of the system, the maximum frequency deviation and the steady-state deviation of the system are the largest. When the photovoltaic power station participates in the system frequency regulation using the proportional allocation method, both the maximum frequency deviation and the steady-state deviation of the system are reduced. When the photovoltaic power station adopts the strategy proposed in this invention, both the maximum frequency deviation and the steady-state deviation of the system are better than those of the proportional allocation method.

[0142] from Figure 5 As can be seen from the comparison of the strategy and proportional allocation of the present invention, the photovoltaic power station outputs more power when the strategy of the present invention is adopted.

[0143] Although the illustrative specific embodiments of the present invention have been described above to enable those skilled in the art to understand the invention, it should be understood that the invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions utilizing the concept of the present invention are protected.

Claims

1. A method for intelligent optimized power distribution control of photovoltaic power generation participating in primary frequency regulation, characterized in that, Includes the following steps: (1) Set the frequency regulation dead zone range for photovoltaic power plants participating in primary frequency regulation. ,in, , These are the upper and lower limits of the FM dead zone; (2) Collect the current time The frequency on the grid-connected side of the photovoltaic power station is denoted as... ,judge Is it within the FM dead zone? If it is within the FM dead zone, then the current... If no frequency adjustment is needed at any time, then end; otherwise, proceed to step (3). (3) Set the minimum starting power of each photovoltaic inverter according to the actual situation of the photovoltaic power station. ; In a photovoltaic power station, the output power of each photovoltaic inverter is considered. If the output power of a certain photovoltaic inverter is the minimum starting power... If the condition is met, the photovoltaic inverter is determined to be in standby mode; otherwise, the photovoltaic inverter is determined to be in MPPT operation mode. Count the number of photovoltaic inverters that are currently shut down. Record the serial number and standby time of each photovoltaic inverter; Count the number of photovoltaic inverters in MPPT operation mode. Record the output power, serial number, and operating time of each photovoltaic inverter; (4) Calculate the photovoltaic power station at the current moment. Total output power at time ; ； in, This indicates the first [unit / item] in the MPPT running state. Taiwanese photovoltaic inverters Output power at any given moment; (5) Sort the standby time and running time of the photovoltaic inverters in ascending order respectively; After sorting all photovoltaic inverters in MPPT operation state in ascending order according to their operating time, an array is used. Represented as: ； in, This indicates the first [unit / item] in the MPPT running state. Operating time of the photovoltaic inverter; After sorting all photovoltaic inverters in standby mode in ascending order of standby time, an array is used. Represented as: ； in, The first one is in standby status. Backup time of a photovoltaic inverter; (6) Set the upper limit of power generation for each photovoltaic inverter; Sort all photovoltaic inverters in MPPT (Multi-Power Trigger) operation state by output power in ascending order, then select the photovoltaic inverter located in the middle position as the sample inverter, and denote the sample inverter's position as... The output power at any given time is the maximum power generation of each photovoltaic inverter. ,Right now: ； (7) Estimate the photovoltaic power station in Maximum power generation at any time ; ； (8) Calculate the primary frequency regulation target value of the photovoltaic power station at the next moment using the primary frequency regulation droop control function. ; ； ； ； in, For the frequency modulation dead zone boundary value, if ,but ,otherwise, ; The rated frequency of the power grid; For drooping characteristic parameters, The percentage of the difference is the percentage of the difference. The droop coefficient for primary frequency modulation; (9) Calculate the photovoltaic power station's performance. Time-based target value ; ； (10) According to Establish the objective function and constraints for photovoltaic power plants to participate in primary frequency regulation; The objective function is: ； in, This indicates the number of photovoltaic power plants participating in frequency regulation. The target output power of the photovoltaic inverter. This indicates the number of photovoltaic inverters in operation after the photovoltaic power station participates in frequency regulation; The constraints are: ； (11) Photovoltaic power plants participate in primary frequency regulation; (11.1) Calculate the primary frequency regulation target value of the photovoltaic power station. With the current moment Total output power at time deviation : ； (11.2) Comparison The magnitude of 0, if If the power is increased, the power increase strategy is adopted, and the process proceeds to step (11.3); otherwise, the power decrease strategy is adopted, and the process proceeds to step (11.4). (11.3) Comparison and The size, if Then in the array In the middle, open in sequence The photovoltaic inverter is in standby mode, then proceed to step (12); otherwise, in the array In the middle, turn on one standby photovoltaic inverter in sequence, and then proceed to step (12). (11.4) In In the photovoltaic inverters of Taiwan, after excluding the sample photovoltaic inverters, the calculation is... mean ; ； (11.5), judgment Does it meet the following requirements: ,like If the condition is met, proceed directly to step (12); otherwise, proceed to step (11.6). (11.6) In the array In the process, one photovoltaic inverter that is in operation is sequentially switched to standby mode, and then the array is updated. The number of photovoltaic inverters in operation Simultaneously update ,in, The first one indicates that the status has been changed to standby. A photovoltaic inverter that is currently in operation Output power at any given time; return to step (11.4) after update. (12) The objective function of the photovoltaic power station participating in primary frequency regulation is solved using the artificial fish swarm algorithm to obtain the target output power of the photovoltaic inverter in operation after the photovoltaic power station participates in frequency regulation. The control terminal of the photovoltaic power station issues corresponding power commands to each photovoltaic inverter according to the target output power of each photovoltaic inverter, thus completing one frequency regulation. Among them, the satisfy: 。

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