Large photovoltaic power station dynamic equivalent control method based on fault ride-through behavior difference

Abstract

The application discloses a large photovoltaic power station dynamic equivalent control method based on fault ride-through behavior difference, which comprises the following steps: calculating the pre-fault output active power of each photovoltaic unit, the pre-fault machine terminal voltage, the machine terminal voltage during the fault and the machine terminal voltage drop degree during the fault in the standard form; dividing the photovoltaic units in the photovoltaic power station based on the pre-fault active power of the photovoltaic units, the pre-fault machine terminal voltage, the machine terminal voltage during the fault and the machine terminal voltage drop degree during the fault, and dividing the units with similar fault ride-through behaviors into the same group; calculating the aggregation parameters of each group of photovoltaic units respectively, establishing the equivalent model of each group of photovoltaic units, and obtaining the equivalent model of the whole photovoltaic power station; connecting the photovoltaic power station equivalent model to the grid model to be analyzed, and researching the specific influence of large-scale photovoltaic access on the safety and stability of the system under the fault scene. The application provides technical support for high-precision simulation and safe production and operation of the power system.

Description

Technical Field

[0001] This invention relates to an equivalent control method for large-scale photovoltaic power plants based on differences in fault ride-through behavior, belonging to the field of power systems. Background Technology

[0002] In recent years, with the increasing maturity of photovoltaic technology and the gradual reduction in the cost of photovoltaic power generation, photovoltaics has achieved significant development in my country. [1] By the end of 2022, my country's cumulative installed photovoltaic capacity had reached 392.04 GW, ranking first in the world, with large-scale photovoltaic power plants accounting for nearly 60%. [2] Large-scale photovoltaic power plants have large installed capacity, high voltage levels, and large land areas. Their connection to the power grid significantly affects the dynamic characteristics of the grid, posing a severe challenge to the safe and stable operation of the grid. [3] .

[0003] The design, operation, and control of power systems rely heavily on simulation; therefore, the modeling and simulation of large-scale photovoltaic power plants are of great significance. [4] Large-scale photovoltaic power plants typically consist of dozens or even hundreds of photovoltaic power generation units. Modeling each unit individually would result in an extremely high model order for the entire plant, severely slowing down simulation calculations. Therefore, it is urgent to establish an equivalent model that can accurately describe the dynamic characteristics of large-scale photovoltaic power plants, such as fault ride-through, while ensuring accuracy. [5] .

[0004] There are two main types of equivalent modeling methods for large-scale photovoltaic power plants: single-unit equivalent methods and multi-unit equivalent methods. [6] The single-unit equivalent method replaces the entire photovoltaic power station with a single photovoltaic power generation unit. The parameters of the equivalent photovoltaic unit are usually obtained through the capacity-weighted method. [7] To achieve higher equivalence accuracy, an improved single-machine equivalence model based on dynamic behavior correction is proposed. [8] Furthermore, an equivalent model parameter optimization method using artificial intelligence was proposed. [9] It has applications, but this method brings a heavy computational burden, and its practicality in engineering is questionable.

[0005] Among them, the multi-unit equivalent method uses multiple equivalent photovoltaic power generation units to represent the dynamic characteristics of the entire power station. Compared with the single-unit equivalent method, it can reflect the differences in dynamic behavior between units. In this method, it is usually necessary to select one or a set of characteristic quantities that can reflect the operating status of the photovoltaic unit as a clustering index to achieve the division of photovoltaic units within the station. Environmental parameters such as irradiance and temperature are directly related to the output of the photovoltaic system.

[10] However, its volatility and randomness make the clustering results complex and varied, posing difficulties for practical applications. The control parameters of the photovoltaic inverter are the fundamental reason affecting the dynamic characteristics of the photovoltaic system. Using the control parameters as the clustering index can obtain higher equivalence accuracy.

[11] -

[12] However, due to limitations such as commercial protection, inverter control parameters are not easily obtained, and when inverters of the same model are used in the same station, clustering indicators represented by control parameters will lose their distinguishability; utilizing the operating status of the protection circuit under fault conditions...

[13] Transient and steady-state output characteristics

[14] Using key dividing points such as the degree of voltage drop at the generator terminal to classify photovoltaic units has been a research hotspot in recent years. Using these as clustering indicators can eliminate the dependence on clustering algorithms and has more explicit physical meaning and better recognizability. However, the differences in fault behavior among photovoltaic power generation units are affected by the coupling of multiple factors such as light intensity distribution, fault severity, and fault ride-through control strategies. The complex problem of quantitative analysis of their operating status seriously restricts the use of this method.

[0006] How to accurately construct a dynamic equivalent model of a large-scale photovoltaic power plant that balances computational simplicity and accuracy remains a current research focus. Summary of the Invention

[0007] This invention provides a dynamic equivalent control method for large-scale photovoltaic power plants based on differences in fault ride-through behavior. It establishes a mathematical relationship between the output active power of a photovoltaic power generation system and solar irradiance under maximum power point tracking control. Furthermore, it presents a calculation method for estimating the terminal voltage of each photovoltaic power generation unit within the plant based on the grid connection point voltage during a fault. The equivalent model obtained using this method has a fixed number of equivalent units and high equivalence, providing technical support for high-precision simulation and safe operation of power systems. See the description below for details.

[0008] A dynamic equivalent control method for large-scale photovoltaic power plants based on differences in fault ride-through behavior, the method comprising:

[0009] Step 1: Obtain the operating irradiance of each photovoltaic power generation unit in the photovoltaic power station under the expected fault scenario and the voltage of the common collection point during the fault period. Calculate the output active power P of each photovoltaic unit before the fault in per-unit form. 0_i Before the fault, the terminal voltage U gi_0 Terminal voltage U during the fault gi_fault The degree of voltage drop at the machine terminals during the fault, α i ;

[0010] Step 2: Based on the active power P output before the photovoltaic unit fault 0_i Before the fault, the terminal voltage U gi_0 Terminal voltage U during the fault gi_fault The degree of voltage drop at the machine terminals during the fault, αi The photovoltaic units within the photovoltaic power station are divided into groups, and units with similar fault-crossing behaviors are grouped together.

[0011] Step 3: Calculate the aggregation parameters of each group of photovoltaic units, establish the equivalent model of each group of photovoltaic units, and thus obtain the equivalent model of the entire photovoltaic power station.

[0012] Step 4: Connect the equivalent model of the photovoltaic power station to the grid model to be analyzed, and study the specific impact of large-scale photovoltaic access on the system's safety and stability under fault scenarios.

[0013] Furthermore, in step 1, the output power of the photovoltaic unit can be calculated as follows:

[0014] P PV =ηP array

[0015] In the formula, η represents the inverter's power generation efficiency, and P PV Injecting power into the photovoltaic system, P array Photovoltaic array output power. Furthermore, the photovoltaic array output power can be calculated as follows:

[0016] P array =N p N s P max

[0017] In the formula, P max N represents the maximum output power of the photovoltaic cell. s N represents the number of photovoltaic cells connected in series within the photovoltaic array. p This represents the number of photovoltaic cells connected in parallel within the photovoltaic array.

[0018] Furthermore, the maximum output power P of the photovoltaic cell max With light intensity I rr The relationship between them is:

[0019]

[0020]

[0021]

[0022] In the formula, I sc U oc I m U m These represent standard operating conditions (1000W / m). 2 The short-circuit current, open-circuit voltage, maximum power point current, and maximum power point voltage of photovoltaic cells at 25℃.

[0023] Furthermore, in step 1, the photovoltaic unit terminal voltage U during the fault period g_fault The calculation formula is:

[0024]

[0025] In the formula, A is the node-branch correlation matrix of each feeder in the photovoltaic power station, and Z... b Z is the branch impedance matrix of each feeder in the photovoltaic power plant. b , The voltage vector at point PCC. This represents the column vector of photovoltaic unit terminal voltages during a fault. This is the column vector of output current for the photovoltaic unit.

[0026] Furthermore, in step 1, the node-branch correlation matrix A is established as follows: Each photovoltaic unit's connection point with the feeder is considered a node, and the collector line connecting the two units is considered a branch. Let A be the node-branch correlation matrix of feeder 1. Then, the rows of matrix A represent nodes, and the columns represent branches. ij Let A be the element in the i-th row and j-th column of matrix A. If the current in branch j flows out of node i, then give a ij If the value is assigned to 1, and the flow into node i is a, then a is assigned a value of 1. ij Assign a value of -1, otherwise assign a ij The value is assigned to 0.

[0027] Furthermore, in step 1, the branch impedance matrix Z b The establishment method is as follows: the collector line connecting the two photovoltaic power generation units is regarded as a branch, and the mutual inductance between the branches is ignored. b It is a diagonal matrix, and the elements on the diagonal are the impedances of the corresponding branches.

[0028] Furthermore, in step 1, the output current equation of the photovoltaic unit is:

[0029]

[0030] In the formula, P i For the i-th photovoltaic unit to output active power, Q i To output reactive power for the i-th photovoltaic unit, Let i be the terminal voltage vector of the i-th photovoltaic unit. dholdi To ensure that the active current does not drop during the failure of the i-th photovoltaic unit, i dmaxi This represents the active current margin of the i-th photovoltaic unit during the fault period.

[0031] Furthermore, in step 2, the specific method for grouping units with similar fault-crossing behavior into the same group is as follows: using the fault-preceding terminal voltage U of each photovoltaic unit... gi_0 Terminal voltage U during the faultgi_fault The degree of voltage drop at the machine terminals during the fault, α i Calculate the clustering criteria, combined with the active power P output of each photovoltaic unit before the fault. 0_i The corresponding clustering criteria are used to divide the photovoltaic unit.

[0032] Furthermore, in step 2, the formula for calculating the clustering criterion is:

[0033] Criterion 1:

[0034] Criterion 2:

[0035] Furthermore, in step S2, the application method of the clustering criterion is as follows:

[0036] like The photovoltaic unit is then classified into Group I.

[0037] like The photovoltaic unit will then be classified into group II.

[0038] like The photovoltaic unit will then be classified into group III.

[0039] The beneficial effects of the technical solution provided by this invention are:

[0040] 1. Based on the output relationship of photovoltaic cells used in engineering, this invention derives the mathematical relationship (light-power curve) between the output active power of a photovoltaic power generation system and the light intensity under maximum power point tracking control, which has high engineering practical value;

[0041] 2. This invention designs a calculation method for the terminal voltage of each photovoltaic power generation unit in a photovoltaic power station based on the iterative solution of the terminal voltage of the grid connection point during a fault. This solves the problem of incomplete information inside the power station during actual operation and reduces the challenges faced by the safe and stable operation of the power grid.

[0042] 3. This invention clarifies all the dynamic response characteristics that may occur in a photovoltaic power generation unit during a fault, constructs the corresponding active dynamic response curve classification boundary, and achieves a reasonable division of photovoltaic units with different fault ride-through behaviors.

[0043] 4. The method of the present invention is simple and convenient to calculate, with clear physical meaning, easy-to-obtain required parameters, and low computational load, making it easy for relevant technical personnel to master and apply. The present invention has high equivalent accuracy while taking into account the computational load requirements, which can greatly improve the efficiency of power system simulation calculation and provide strong technical support for high-precision simulation and safe production operation of the power grid. Attached Figure Description

[0044] Figure 1A flowchart of a dynamic equivalent method for large-scale photovoltaic power plants based on differences in fault ride-through behavior;

[0045] Figure 2 This is a topology diagram of an actual photovoltaic power station;

[0046] Figure 3 This is a control flowchart for the entire low-voltage ride-through process of a photovoltaic system.

[0047] Figure 4 This is a schematic diagram of the three types of active power dynamic response;

[0048] Figure 5 A schematic diagram of the classification boundaries for active power dynamic response curves;

[0049] Figure 6 Here are schematic diagrams of 10 lighting scenarios for the photovoltaic power station under study.

[0050] Figure 7 This is a comparison chart of simulation results.

[0051] Among them, (a) is a comparison chart of the active power simulation results of the detailed model, the single-machine equivalent model, and the three-machine equivalent model when the voltage at point PCC drops to 0.2675 pu; (b) is a comparison chart of the reactive power simulation results of the detailed model, the single-machine equivalent model, and the three-machine equivalent model when the voltage at point PCC drops to 0.2675 pu; (c) is a comparison chart of the active power simulation results of the detailed model, the single-machine equivalent model, and the three-machine equivalent model when the voltage at point PCC drops to 0.364 pu. Comparison charts: (d) shows the reactive power simulation results of the detailed model, single-machine equivalent model, and three-machine equivalent model when the PCC point voltage drops to 0.364 pu; (e) shows the active power simulation results of the detailed model, single-machine equivalent model, and three-machine equivalent model when the PCC point voltage drops to 0.605 pu; (f) shows the reactive power simulation results of the detailed model, single-machine equivalent model, and three-machine equivalent model when the PCC point voltage drops to 0.605 pu. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below.

[0053] Example 1

[0054] To construct an equivalent model that can accurately describe the dynamic characteristics of a photovoltaic power plant, this invention provides a dynamic equivalent control method for large-scale photovoltaic power plants based on differences in fault ride-through behavior. This method includes the following steps:

[0055] 101: Obtain the operating irradiance of each photovoltaic power generation unit in the photovoltaic power station under the expected fault scenario and the voltage of the common collection point during the fault period, and calculate the output active power P of each photovoltaic unit before the fault in per-unit form. 0_i Before the fault, the terminal voltage U gi_0 Terminal voltage U during the fault gi_fault The degree of voltage drop at the machine terminals during the fault, α i ;

[0056] 102: Based on the active power output P before the photovoltaic unit failure 0_i Before the fault, the terminal voltage U gi_0 Terminal voltage U during the fault gi_fault The degree of voltage drop at the machine terminals during the fault, α i The photovoltaic units within the photovoltaic power station are divided into groups, and units with similar fault-crossing behaviors are grouped together.

[0057] Among them, if Then the unit is assigned to group I;

[0058] like Then the unit will be assigned to group II;

[0059] like Then this unit is classified into group III.

[0060] 103: Calculate the aggregation parameters of each group of photovoltaic units separately, establish the equivalent model of each group of photovoltaic units, and thus obtain the equivalent model of the entire photovoltaic power station;

[0061] 104: By integrating the equivalent model of the photovoltaic power plant into the grid model to be analyzed, the specific impact of large-scale photovoltaic access on the system's safety and stability under fault scenarios is studied.

[0062] In summary, through steps 101-104 above, the embodiments of the present invention reasonably construct a dynamic equivalent model of a photovoltaic power station suitable for low voltage ride-through simulation. This equivalent model can reflect the differences in fault ride-through behavior between photovoltaic units within the station during actual operation and has high equivalence accuracy.

[0063] Example 2

[0064] The scheme in Example 1 will be further described below with specific calculation formulas and examples:

[0065] 201: Obtain the operating irradiance of each photovoltaic power generation unit in the photovoltaic power station under the expected fault scenario and the voltage of the common collection point during the fault period, and calculate the output active power P of each photovoltaic unit before the fault in per-unit form. 0_i Before the fault, the terminal voltage U gi_0 Terminal voltage U during the faultgi_fault The degree of voltage drop at the machine terminals during the fault, α i ;

[0066] I. Calculation method for photovoltaic unit terminal voltage during faults

[0067] First, based on the actual topology of the photovoltaic power station, the node-branch correlation matrix and branch impedance matrix of each feeder in the station are constructed;

[0068] by Figure 2 Taking a domestic photovoltaic power station topology as an example, this paper introduces the methods for obtaining the node-branch correlation matrix and branch impedance matrix of the feeder.

[0069] Consider the connection point between each photovoltaic unit and the feeder in the station as a node, and the collector line connecting the two units as a branch. Let A be the node-branch correlation matrix of feeder 1. Then, the rows of matrix A represent nodes, and the columns represent branches. ij Let A be the element in the i-th row and j-th column of matrix A. If the current in branch j flows out of node i, then give a ij If the value is assigned to 1, and the flow into node i is a, then a is assigned a value of 1. ij Assign a value of -1, otherwise assign a ij The value is assigned to 0.

[0070] Let the branch impedance matrix of feeder 1 be Z. b In this embodiment of the invention, the mutual inductance between branches is ignored, then Z b It is a diagonal array, Z b The order is the number of branches of feeder 1.

[0071] In this embodiment of the invention, all variables and parameters are expressed in per-unit values. Assuming that the actual output current of the photovoltaic inverter can accurately track its corresponding reference value during a fault, the photovoltaic power generation unit can be equivalent to a controlled current source, whose output current... It can be represented as:

[0072]

[0073] Among them, P i For the i-th photovoltaic unit to output active power, Q i To output reactive power for the i-th photovoltaic unit, Let i be the terminal voltage vector of the i-th photovoltaic unit. dholdi To ensure that the active current does not drop during the failure of the i-th photovoltaic unit, i dmaxi This represents the active current margin of the i-th photovoltaic unit during the fault period.

[0074] Based on the node-branch correlation matrix of each feeder, the current equation for each node is established according to Kirchhoff's current law:

[0075]

[0076] In the formula, It is determined by the branch current. The column vector formed; Current injected from nodes The column vector formed, A i Let be the node-branch correlation matrix of the i-th feeder within the station.

[0077] Establish the branch voltage drop equation using Kirchhoff's voltage law:

[0078]

[0079] In the formula, It is caused by node voltage drop The column vector formed; It is caused by branch voltage drop The column vector formed, A i T It is the transpose of the node-branch correlation matrix of the i-th feeder within the station.

[0080] The branch voltage drop can be calculated using Ohm's law. for:

[0081]

[0082] Among them, Z b This is the branch impedance matrix.

[0083] By combining equations (1), (2), (3), and (4), the voltage at each node on the feeder can be obtained as follows:

[0084]

[0085] in, This is the voltage vector at point PCC.

[0086] If the voltage at point PCC is known, the terminal voltage of each photovoltaic unit in the station can be calculated using the following steps:

[0087] 1) Based on the topology and actual data of the photovoltaic power station, establish the branch impedance matrix Z of each feeder within it. bi And node-branch association matrix A i ;

[0088] 2) Put all node voltages All values ​​are assigned to the PCC point voltage, and the new node voltage values ​​are obtained by solving equation (5).

[0089] 3) If (θ is the iteration precision), proceed to step 4); otherwise, The value assigned to Then proceed to step 2) for the next iteration.

[0090] 4) Output node voltage vector

[0091] II. Method for Calculating the Output Power of Photovoltaic Units under Maximum Power Control

[0092] The steady-state output active power of photovoltaic (PV) units is one of the aforementioned clustering indicators. However, in actual power system operation, the real-time operating information of each PV unit within the power station is usually unknown. Irradiance is the most critical factor affecting the output of a PV power generation system. Therefore, when performing simulation analysis for anticipated faults, historical irradiance data can be combined to obtain the operating irradiance of each PV unit, and the active power of each unit can be calculated based on this. This invention establishes the active power characteristic curve of a PV power generation system under maximum power point tracking (MPPT) control with respect to irradiance.

[0093] In practical engineering calculations, the output power P and output voltage U of a photovoltaic cell satisfy the following relationship:

[15] :

[0094]

[0095] In the formula, I sc ′、U oc ′、I m ′、U m ′ represents the short-circuit current, open-circuit voltage, maximum power point current, and maximum power point voltage of the photovoltaic cell under the current operating conditions, respectively.

[0096] Under maximum power point point control, the output voltage of the photovoltaic cell is U = U m Substituting it into equation (6), we get:

[0097]

[0098] Given the ambient temperature T, the maximum output power P of the photovoltaic cell can be calculated. max With light intensity I rr The relationship between them is:

[0099]

[0100] In the formula, ΔT = T - 25, I sc U oc I m U mThese represent the short-circuit current, open-circuit voltage, maximum power point current, and maximum power point voltage of the photovoltaic cell under standard operating conditions. The specific values ​​can be found in the photovoltaic cell product manual.

[0101] Photovoltaic cells are connected in series and parallel to form a photovoltaic array. Let N be the number of cells connected in series in the photovoltaic array. s The number of series connections is N p :

[0102] P array =N p N s P max (9)

[0103] The photovoltaic power generation system is connected to the grid via an inverter. When the power output from the photovoltaic array flows through the inverter, some power loss occurs. Therefore, the injected power P of the photovoltaic system... PV With the output power P of the photovoltaic array array Space satisfies:

[0104] P PV =ηP array (10)

[0105] In the formula, η represents the inverter's power generation efficiency, which is usually taken as 0.95-0.96.

[0106] The default voltage U at each photovoltaic unit terminal before the fault gi_0 All are 1, and the terminal voltage during the fault is U. gi_fault The degree of voltage drop at the photovoltaic unit terminals during the fault period is α. i =U fault_i / U gi_0 .

[0107] 202: Based on the active power output P before the photovoltaic unit failure 0_i Before the fault, the terminal voltage U gi_0 Terminal voltage U during the fault gi_fault The degree of voltage drop at the machine terminals during the fault, α i The photovoltaic units within the photovoltaic power station are divided into groups, and units with similar fault-crossing behaviors are grouped together.

[0108] Among them, if Then the unit is assigned to group I;

[0109] like Then the unit will be assigned to group II;

[0110] like Then this unit is classified into group III.

[0111] In this embodiment of the invention, the specific criteria for distinguishing the differences in fault ride-through behavior of photovoltaic units are described:

[0112] I. Control of Photovoltaic Power Generation Systems

[0113] This invention takes a single-stage photovoltaic power generation system as the research object, and all variables and parameters in the embodiments are expressed in per-unit values.

[0114] The output power equation of a photovoltaic power generation system can be expressed as:

[0115]

[0116] In the formula, U g i is the terminal voltage of the photovoltaic power generation system. d The system outputs active current; i q For the system to output reactive current, P ac For the photovoltaic system to output active power, Q ac It outputs reactive power to the photovoltaic system.

[0117] By establishing separate active and reactive current references for the photovoltaic system, independent decoupled control of the photovoltaic system's output power can be achieved.

[0118] During normal operation, the inverter's DC-side voltage achieves error-free tracking of the reference voltage (maximum power point voltage) through a PI regulator, thereby realizing the maximum power output of the photovoltaic power generation system under the current operating conditions. Simultaneously, the inverter's reactive current reference value i... qref0 Setting it to 0 allows the photovoltaic system to operate at unity power factor. In this case, the current reference value can be calculated using the following formula:

[0119]

[0120] Among them, i dref0 i is the reference value of the active current of the photovoltaic system during normal operation. qref0 K represents the reference value for reactive current of the photovoltaic system during normal operation. p K is the proportional coefficient of the voltage outer loop PI controller. i V is the integral coefficient of the voltage outer loop PI controller. dc V is the DC bus voltage of the inverter. dcref This is the reference value for the DC bus voltage of the inverter.

[0121] Suppose that due to an external fault, the terminal voltage of the photovoltaic system drops by U. g_fault U g_fault =αU g0 α is the voltage drop depth at the machine terminals, U g0 To ensure stable operation of the photovoltaic system's terminal voltage.

[0122] Grid requirements: The photovoltaic system should ensure continuous operation without disconnecting from the grid during a fault, and should prioritize injecting reactive current into the grid to support grid voltage recovery. In this embodiment of the invention, the reference value for the reactive current of the photovoltaic system during a fault is:

[0123]

[0124] Among them, i q_fault * This is a reference value for the reactive current of the photovoltaic system during a fault.

[0125] Due to the voltage drop at the generator terminals, the power balance between the AC and DC sides of the photovoltaic inverter will be disrupted after a fault occurs. The redundant active power accumulated on the DC-side capacitor will cause a sudden rise in the DC-side voltage. To maintain a constant DC-side voltage, the inverter output power should be controlled to be equal to that before the fault, i.e., the active current reference value should be:

[0126] i dhold =i d0 / α (14)

[0127] Among them, i dhold The active current reference value is used to ensure that the active power of the photovoltaic system does not drop during a fault. d0 This represents the active current of the photovoltaic system before the fault.

[0128] Due to inverter current constraints, under the premise of generating reactive current according to equation (13), the active current margin of the inverter during the fault period is:

[0129]

[0130] In the formula, i dmax I represents the active current margin of the inverter during a fault. max This is the maximum output current of the inverter, typically taken as 1.1 times the rated current.

[0131] To ensure that the inverter output current does not exceed the limit during a fault, the active current reference value i of the photovoltaic system during the fault period is set. d_fault * It should be:

[0132]

[0133] II. Classification and Judgment of Dynamic Behavior of Active Power

[0134] The dynamic response characteristics of the active power of the photovoltaic system after a fault consist of two stages: during the fault and after the fault. The two stages are analyzed separately based on a single photovoltaic power generation unit.

[0135] During the fault duration, according to equation (16): when i dhold <idmax At that time, i d_fault * =i dhold During a fault, the active power output of the photovoltaic system equals the power before the fault, and the DC-side voltage of the inverter remains stable; when i dhold >i dmax At that time, i d_fault * =i dmax During a fault, the active current is limited by the inverter current. At this time, the output active power is less than the power before the fault, and the DC side voltage cannot be stabilized, so the protection circuit needs to be activated.

[0136] The main difference in the active power response characteristics of the unit after fault clearance lies in the presence or absence of the ramp recovery phase, which depends on the active current i at the time of fault clearance. d_fault * Compared with the active current i before the fault d0 The size relationship, if i d_fault * >i d0 If i d_fault * <i d0 Due to the limited recovery rate of the active current, the active power will recover to its pre-fault steady-state value at a certain slope after the fault is cleared. From equation (14), we know that i hold Always greater than i d0 Therefore, we only need to compare i. dmax with i d0 The size relationship is sufficient, i dhold i d0 i dmax There are three types of relationships between them:

[0137] 1)i dhold <i dmax At this time i d_fault * =i dhold >i d0 The active power is restored instantaneously after the fault.

[0138] 2)i d0 <i dmax <i dhold At this time i d_fault * =i dmax During the fault, the active power is restored instantaneously.

[0139] 3)i dmax <i d0 At this time i d_fault * =i dmaxAfter a fault, the active power recovers to the steady-state value before the fault at a certain slope.

[0140] In summary, the control process of the photovoltaic system throughout the entire fault process can be summarized as follows: Figure 3 As shown:

[0141] Under different control strategies, the active power dynamic response characteristic curves of the unit are different, specifically as follows: Figure 4 As shown:

[0142] After clarifying the differences in the dynamic behavior of photovoltaic power generation units during fault ride-through, it is necessary to find a suitable clustering index to separate photovoltaic units with different dynamic response characteristics.

[0143] Active current i before the fault d0 It can be obtained by combining equation (11):

[0144] i d0 =P0 / U g0 (17)

[0145] In the formula, P0 is the active power before the fault; U g0 This represents the voltage at the photovoltaic terminal before the fault.

[0146] If i d0 =i dmax Combining equations (13), (15), and (17), we can obtain:

[0147]

[0148] Among them, P ambit1 This represents the classification boundary between Class I and Class II response curves.

[0149] If i dmax =i dhold Combining equations (13), (14), (15), and (18), we can obtain:

[0150] P ambit2 =αP ambit1 (19)

[0151] Among them, P ambit2 This represents the classification boundary between Class II and Class III response curves.

[0152] If P0 is less than P ambit2 Then the active power during the fault period is equal to the power before the fault, corresponding to Figure III Curve-like; if P ambit2 <P0<P ambit1 If the active power during the fault is less than the power before the fault, and the active power recovers instantaneously during the fault, then... Figure II Curve-like; if P0 > P ambit1If the active power during the fault is less than the power before the fault, the active power after the fault recovers to the steady-state value before the fault with a certain slope. Figure I Curve-like structures.

[0153] Combining equations (18) and (19), the critical active power P of the photovoltaic unit under different voltage drop depths can be obtained. ambit1 P ambit2 The relationship between the two is as follows: Figure 5 As shown.

[0154] Figure 5 Each region corresponds to a specific LVRT (Low Voltage Ride-Through) dynamic response characteristic. Based on the clustering boundary shown in the figure above, photovoltaic units with the same dynamic characteristics can be grouped into one category, and the entire power station can ultimately be represented by a maximum of three units.

[0155] 203: Calculate the aggregation parameters of each group of photovoltaic units separately, establish the equivalent model of each group of photovoltaic units, and thus obtain the equivalent model of the entire photovoltaic power station;

[0156] 204: By integrating the equivalent model of the photovoltaic power plant into the grid model to be analyzed, the specific impact of large-scale photovoltaic access on the system's safety and stability under fault scenarios is studied.

[0157] In summary, through steps 201-204 above, the embodiments of the present invention reasonably construct a dynamic equivalent model of a photovoltaic power station suitable for low voltage ride-through simulation. This equivalent model can reflect the differences in fault ride-through behavior between photovoltaic units within the station during actual operation and has high equivalence accuracy.

[0158] Example 3

[0159] The following examples demonstrate the equivalence accuracy and effectiveness of the large-scale photovoltaic power plant equivalent modeling methods based on fault ride-through behavior differences proposed in Examples 1 and 2. Details are provided below:

[0160] Simulation verification based on Figure 2 The image shows a 100MW photovoltaic power station in my country. This power station consists of 32 photovoltaic units, each with a capacity of 3.15MW. The photovoltaic units are connected by cable lines, the length of which is already shown. Figure 2 Note in the text, Figure 6Ten sets of illumination scenarios for the power station were measured in July 2021. Each column in the figure corresponds to one illumination scenario, with 32 points in each column. The vertical axis of each point represents the operating illumination intensity of one unit in that scenario. Detailed models, single-unit equivalent models, and the three-unit equivalent model proposed in this embodiment of the invention were constructed on the Matlab / Simulink platform. Assuming that the operating temperature of each photovoltaic unit is the same (25℃), simulation verification was carried out under different PCC point voltage drop depths, taking the fifth illumination scenario as an example.

[0161] In Example 3, a symmetrical short-circuit fault occurred at point PCC at the 30th second of the simulation. The fault was cleared after 0.2 seconds. During the fault, the voltage at point PCC dropped to 0.2675pu, 0.364pu, and 0.605pu, respectively.

[0162] The terminal voltage of each photovoltaic unit during the fault period is obtained by combining equation (5) and the PCC point voltage iteration. The active power before the fault is calculated by combining equations (8), (9), (10) and the operating light intensity of each photovoltaic unit. Based on the calculation results, combined with Figure 5 The active power dynamic response classification boundary is shown to divide the photovoltaic cells, and the clustering results are shown in Table 1:

[0163] Table 1. Schematic diagram of clustering results under different PCC point voltage drop levels.

[0164] a. The voltage at point PCC drops to 0.2675 pu.

[0165]

[0166] b. The voltage at point PCC drops to 0.364 pu.

[0167]

[0168]

[0169] c. The voltage at point PCC drops to 0.605 pu.

[0170]

[0171] Figure 7 The simulation curves are compared for three different PCC voltage drop depths. The black solid line represents the detailed model simulation curve, the light gray short dashed line represents the single-machine equivalent model simulation curve, and the dark gray long dashed line represents the three-machine equivalent model simulation curve proposed in this embodiment of the invention. As can be seen from the simulation results, under different voltage drop depths, the three-machine equivalent model can fit the dynamic behavior of the detailed model in the three stages before, during and after the fault well, and the accuracy is significantly improved compared with the single-machine equivalent model.

[0172] The above results show that the three-machine equivalent model designed in the embodiments of the present invention can take into account the differences in the dynamic behavior of active power fault ride-through of different photovoltaic units during the actual operation of photovoltaic power plants. Furthermore, the three-stage recovery equivalent model designed in the embodiments of the present invention for the active power slope recovery characteristics of actual photovoltaic power plants still has a good fitting effect on the detailed model recovery stage while simplifying the calculation complexity. This indicates that the present invention has good equivalent accuracy and engineering applicability.

[0173] References

[0174] [1] Ye Lin, Pei Ming, Lu Peng, et al. Short-term photovoltaic power combination prediction method based on weather classification [J]. Automation of Electric Power Systems, 2021, 45(01):44-54.

[0175] [2] National Energy Administration. 2022 Photovoltaic Power Generation Construction and Operation Status [EB / OL]. [2023-02-17]

[0176] [3] M.Ding, Z.Xu, W.Wang,

[0177] [4] K.Jia, C.Gu, Z.Xuan, L.Li and Y.Lin, "Fault Characteristics Analysis and Line Protection Design Within a Large-Scale Photovoltaic Power Plant," in IEEE Transactions on Smart Grid, vol.9, no.5, pp.4099-4108, Sept.2018.

[0178] [5]A.Samadi,L. E.Shayesteh and R.Eriksson, "Static Equivalent ofDistribution Grids With High Penetration of PV Systems," in IEEE Transactionson Smart Grid, vol.6, no.4, pp.1763-1774, July 2015.

[0179] [6] Zhou Lin, Zhang Mi. Analysis of resonance phenomenon in large photovoltaic power plants [J]. Electric Power Automation Equipment, 2014, 34(6):8-14.

[0180] [7] Yan Kai, Zhang Baohui, Qu Jiping et al. Transient modeling and equivalent value of photovoltaic power generation system [J]. Power System Protection and Control, 2015, 43(01):1-8.

[0181] [8] P.Chao, W.Li, S.Peng,

[0182] [9]P.Li et al., "High-Precision Dynamic Modeling of Two-StagedPhotovoltaic Power Station Clusters," in IEEE Transactions on Power Systems, vol.34, no.6, pp.4393-4407, Nov.2019

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[10] Guo Yifei, Gao Houlei, Tian Jia. Photovoltaic output modeling with the introduction of cluster analysis and its application in reliability assessment [J]. Automation of Electric Power Systems, 2016, 40(23):93-100.

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[11] Sheng Wanxing, Ji Yu, Wu Ming, et al. Dynamic clustering modeling of regional centralized photovoltaic power generation system based on improved fuzzy C-means clustering algorithm [J]. Power System Technology, 2017, 41(10):3284-3291.

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[12] Cui Xiaodan, Li Wei, Li Zhaowei, et al. Online dynamic equivalent method for large-scale photovoltaic power plants applicable to electromechanical transient simulation [J]. Automation of Electric Power Systems, 2015, 39(12):21-26.

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[13] Tang Binwei, Yuan Tiejiang, Chao Qin et al. Analysis of photovoltaic LVRT based on DC-Chopper protection [J]. Power Technology, 2013, 37(11):2016-2018+2034.

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[14] J.Zheng, Z.Ma, Z.Wang,

[0188]

[15] Su Jianhui, Yu Shijie, Zhao Wei, et al. Mathematical model for silicon solar cell engineering [J]. Acta Energiae Solaris Sinica, 2001(04):409-412.

[0189] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0190] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic equivalent control method for large-scale photovoltaic power plants based on differences in fault ride-through behavior, characterized in that, The method includes: Obtain the operating irradiance of each photovoltaic power generation unit in the photovoltaic power plant under the expected fault scenario and the voltage of the common collection point during the fault period, and calculate the output active power P of each photovoltaic unit before the fault in per-unit form. 0_i Before the fault, the terminal voltage U gi_0 Terminal voltage U during the fault gi_fault The degree of voltage drop at the machine terminals during the fault, α i ; P 0_i = ηN s N p P max In the formula, η represents the inverter's power generation efficiency, and N s N represents the number of photovoltaic arrays connected in series. p This represents the number of photovoltaic arrays connected in parallel. U gi_0 ＝1 In the formula, The voltage vector at point PCC. The voltage at the terminals of each photovoltaic unit during the fault period The column vector formed The output current of each photovoltaic unit The column vector consists of A, which is the node-branch correlation matrix of each feeder in the photovoltaic power plant, and Z. b This is the branch impedance matrix for each feeder in the photovoltaic power plant; α i =U gi_fault / IN gi_0 Based on the active power P output before the photovoltaic unit fault 0_i Before the fault, the terminal voltage U gi_0 Terminal voltage U during the fault gi_fault The degree of voltage drop at the machine terminals during the fault, α i The photovoltaic units within the photovoltaic power station are divided into groups, and units with similar fault-crossing behaviors are grouped together. like The photovoltaic unit is then classified into Group I. like The photovoltaic unit will then be classified into group II. like The photovoltaic unit will then be classified into group III. The aggregation parameters of each group of photovoltaic units are calculated separately, and an equivalent model of each group of photovoltaic units is established, thereby obtaining the equivalent model of the entire photovoltaic power station. By integrating the equivalent model of the photovoltaic power plant into the grid model to be analyzed, the specific impact of large-scale photovoltaic access on the system's safety and stability under fault scenarios can be obtained.

2. The dynamic equivalent control method for large-scale photovoltaic power plants based on differences in fault ride-through behavior according to claim 1, characterized in that, The maximum output power P of the photovoltaic cell before the fault max With light intensity I rr The relationship between them is: In the formula, I sc U oc I m U m These represent standard operating conditions (1000W / m). 2 The short-circuit current, open-circuit voltage, maximum power point current, and maximum power point voltage of a photovoltaic cell at 25℃, ΔT=T-25, where T represents the operating temperature of the photovoltaic unit.

3. The dynamic equivalent control method for large-scale photovoltaic power plants based on differences in fault ride-through behavior according to claim 1, characterized in that, The output current of the i-th photovoltaic unit as follows: In the formula, P i For the i-th photovoltaic unit to output active power, Q i To output reactive power for the i-th photovoltaic unit, Let i be the terminal voltage vector of the i-th photovoltaic unit. dholdi To ensure that the active current does not drop during the failure of the i-th photovoltaic unit, i dmaxi This represents the active current margin of the i-th photovoltaic unit during the fault period.

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