General modeling method and device for active distribution network containing multiple types of distributed renewable energy

Abstract

The present invention discloses a general modeling method for an active distribution network containing multiple types of distributed renewable energy sources, including: establishing a low-order general model structure of distributed renewable energy sources; connecting the obtained general model of distributed renewable energy sources in parallel with a traditional comprehensive load model as a general model structure of an active distribution network; performing equivalent modeling on multiple nonlinear modules including low-voltage active power management, low-voltage reactive power management, and current limiting of converters in multiple types of distributed renewable energy sources in the active distribution network, and obtaining model parameters of each nonlinear module; using a particle swarm optimization algorithm to perform parameter identification on linear modules in the general model of the active distribution network; and calculating the final parameter values ​​of the general model of the active distribution network. The present invention can describe the general dynamics of multiple types of distributed renewable energy sources, and can also describe the equivalent characteristics of low voltage ride-through control and current limiting links of distributed renewable energy sources, and the model structure is simple and has high equivalent accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of power system modeling, and in particular to a general modeling method and device for an active distribution network containing multiple types of distributed renewable energy. Background Art

[0002] Power system analysis and control mainly rely on simulation calculations, and the accuracy of simulation calculations depends on the model used. Load is an important part of the power system. Inaccurate load models will lead to aggressive or conservative overall simulation calculation results. At present, with the continuous grid connection of distributed renewable energy, load characteristics have changed significantly. The existing load model is no longer suitable for the needs of modern power system simulation analysis, and new modeling means and methods are urgently needed.

[0003] Due to the diversity of distributed renewable energy such as wind power and photovoltaic power generation and the dispersion of access locations, as well as the small capacity of a single unit and the complexity of the model, detailed modeling is labor-intensive and computationally complex. At the same time, since distributed renewable energy such as doubly-fed wind turbines, direct-drive wind turbines, and photovoltaic power generation systems are all connected to the grid through power electronic equipment, their machine-grid dynamics are highly similar. Therefore, studying the interaction between distributed renewable energy and the power grid and proposing a general simplified model structure suitable for describing each distributed renewable energy are important for building an active distribution network model with a simple structure and satisfactory accuracy.

[0004] A Chinese patent (CN202011513919.2) discloses a modeling method for a comprehensive load model considering a distributed power generation system, comprising the following steps: S01, collecting the active power and reactive power at the sending end of the distribution line or transformer, the number of sending-end buses and the voltage of each bus, and the impedance of the distribution line and transformer; collecting the number of generators in the distributed power generation system, the current emitted by the generators, and the active output of the generators; and collecting the number of load branches and branch currents, load active power, reactive power, and voltage; S02, calculating the equivalent impedance of the distribution network in the distribution power supply area based on the network topology data, the distributed power generation system data, and the load equipment data of the substation, and based on the equivalent impedance of the distribution network in the distribution power supply area Impedance establishes an equivalent impedance model of the distribution network; S03, according to the distributed power generation system data, calculates and determines the aggregated equivalent parameters of the distributed power generation system, and establishes an equivalent distributed power generation system model based on the aggregated equivalent parameters of the distributed power generation system; S04, according to the load equipment data of the substation, calculates and determines the static load equivalent parameters and dynamic load equivalent parameters of the distribution power supply area, establishes an equivalent static load model based on the static load equivalent parameters, and establishes an equivalent dynamic load model based on the dynamic load equivalent parameters; S05, based on the distribution network equivalent impedance model, the equivalent static load model and the equivalent dynamic load model, and the equivalent distributed power generation system model, constructs a comprehensive load model considering the distributed power generation system. This invention overcomes the shortcomings of traditional load models that cannot describe the impact of distributed power generation systems on power grid characteristics, and improves the accuracy of power system simulation calculations. However, it does not involve a general dynamic description of multiple types of distributed new energy, nor does it take into account the low voltage ride-through control of distributed new energy, and does not have a high equivalent accuracy for the current limiting link of distributed new energy.

[0005] Chinese patent (CN201811472690.5) discloses a probabilistic equivalent modeling method for active distribution network considering the randomness of new energy, including the following steps: S01, obtaining the operating data of the active distribution network; S02, calculating the semi-invariant data of node load and node new energy generation in the active distribution network; S03, calculating the semi-invariant data of node injection power in the active distribution network; S04, calculating the approximate linear relationship between the node injection power of the active distribution network and the equivalent injection power of the boundary node; S05, based on the semi-invariant data of node injection power in the active distribution network and the approximate linear relationship, the semi-invariant data of the equivalent injection power of the boundary node is calculated; S06, the probabilistic equivalent model of the active distribution network is obtained according to the semi-invariant data of the equivalent injection power of the boundary node. The invention uses the semi-invariant as a link and establishes a probabilistic equivalent model of the active distribution network based on the node voltage equation of the power system to improve the analysis efficiency of the transmission network and adapt to the scenario of independent operation of transmission and distribution. However, the model of this invention is suitable for steady-state analysis of power systems. It does not involve the general dynamic description of multiple types of distributed renewable energy sources, nor does it involve low voltage ride-through control and current limiting links of distributed renewable energy sources. It is not suitable for dynamic analysis of power systems. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a general modeling method and device for an active distribution network containing multiple types of distributed renewable energy sources. The constructed model can describe the general dynamics of multiple types of distributed renewable energy sources, and can also describe the equivalent characteristics of the low voltage ride-through control and current limiting links of the distributed renewable energy sources. The model structure is simple and has high equivalent accuracy.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, an embodiment of the present invention provides a general modeling method for an active distribution network containing multiple types of distributed renewable energy sources, the modeling method comprising the following steps:

[0009] S1, comparing the common points of various distributed renewable energy detailed models, simulating and analyzing the dynamic characteristics of various distributed renewable energy under grid-side disturbance, and establishing a low-order general model of distributed renewable energy based on the analysis of the common points of the dynamic characteristics of various distributed renewable energy; the distributed renewable energy low-order general model includes an active power control module, a reactive power control module, a phase-locked loop module, a low-voltage active power management module, a low-voltage reactive power management module, a limiting link and a machine-grid interface module;

[0010] S2, connecting the obtained general model of distributed renewable energy and the comprehensive load model in parallel as a general model of active distribution network; the comprehensive load model is a parallel connection of an induction motor and a static ZIP load;

[0011] S3, equivalent modeling of multiple nonlinear modules including low voltage active power management, low voltage reactive power management and current limiting of converter in multiple types of distributed renewable energy in active distribution network;

[0012] S4, using particle swarm optimization algorithm, to identify the parameters of linear modules in the general model of active distribution network; linear modules include active control module, reactive control module, phase-locked loop module, machine-grid interface module in the general model of distributed new energy, and induction motor and static ZIP load in the comprehensive load model;

[0013] S5, integrating the identification results of the linear module with the equivalent results of the nonlinear module in step S2, and calculating the final parameter values ​​of the general model of the active distribution network.

[0014] Furthermore, in step S1, the input of the active power control module is the active power reference value, the control strategy adopts proportional integral control, and the output is the d-axis current i d ;

[0015] The control strategy of the reactive power control module is one of the three control methods: constant power factor control, constant reactive power control and constant voltage control. The control strategies under the three control modes are all proportional integral control, and the output is the q-axis current i q_normal ; Among them, the input under constant power factor control is the power factor angle, and the product of its tangent function and active power is the reactive power reference value; the input under constant reactive power control is the reactive power reference value; the input under constant voltage control is the voltage amplitude of the distributed new energy port;

[0016] The input of the phase-locked loop control module is the voltage phase angle of the distributed new energy outlet, the control strategy is the series connection of proportional integral control and integral control, and the output is the phase-locked angle;

[0017] In the low voltage reactive power management module, the q axis current i q It is represented by the current i under normal control of the converter q_normal and the q-axis additional reactive current i during low voltage ride-through qLVRT The sum of the q-axis current i q Affected by the converter current limit I max In the reactive power priority control mode, there are:

[0018] i q =min{i q_normal +i qLVRT , I max} (1);

[0019] For direct-drive wind turbines, the additional reactive current is expressed as:

[0020] i qLVRT=k q (U n -U)=k q ΔU, 0≤U≤0.9U n (2);

[0021] For photovoltaic power generation units, the additional reactive current is expressed as:

[0022]

[0023] For doubly-fed wind turbines, the additional reactive current is 0;

[0024] In the formula, k q is the reactive power support coefficient, U is the port voltage of distributed renewable energy, and U n is the rated voltage; ΔU is the rated voltage U n The difference between the terminal voltage U and

[0025] In the low voltage active power management module, the active power P of the distributed new energy during the low voltage ride-through period LVRT P is the active power reference value during normal operation ref The value of parameter λ is related to the type of distributed renewable energy and the amplitude of the voltage at the renewable energy port. d Affected by the converter current limit I max In the reactive power priority control mode, there are:

[0026]

[0027] For a doubly-fed wind turbine, λ is expressed as:

[0028]

[0029] For direct-drive wind turbines, λ is expressed as:

[0030]

[0031] For photovoltaic power generation units, λ = 1;

[0032] In the formula, k p is the active support coefficient;

[0033] The machine-grid interface module uses a current source model to represent distributed renewable energy, and the output currents are i d and i q .

[0034] Further, in step S3, the process of equivalent modeling of multiple nonlinear modules including low voltage active power management, low voltage reactive power management and current limiting of converters in multiple types of distributed renewable energy in the active distribution network includes the following steps:

[0035] S31, perform the equivalent of low voltage active power management model:

[0036] S311, let the sum of the active powers of all distributed renewable energy sources be the active power P of the equivalent machine eq.ref :

[0037]

[0038] Where P eq.ref is the active power reference value of the equivalent machine, P gref (j) is the active power reference value of the jth distributed renewable energy source, λ eq is the coefficient of the equivalent machine, j is the jth distributed renewable energy, λ(j) is the value of the multiple parameter λ of the jth distributed renewable energy; n is the total number of distributed renewable energy in the distribution network;

[0039] S312,P eq.ref and It is known that according to formula (7), the λ of the equivalent machine is obtained eq ;

[0040] S32, perform the equivalent of low voltage reactive power management model:

[0041] Assume the reactive additional current i of the equivalent machine qLVRT.eq It is the sum of the reactive additional current of all distributed renewable energy sources during low voltage ride-through, that is:

[0042]

[0043] Among them, i qLVRT.eq is the reactive additional current of the equivalent machine; k q.eq is the reactive support coefficient of the equivalent machine; k q (j) is the reactive power support coefficient of the jth distributed renewable energy source, ΔU(j) is the rated voltage U of the jth distributed renewable energy source n The difference between the terminal voltage U and the eq is the rated voltage U of the equivalent machine n The difference between the terminal voltage U and

[0044] S33, perform equalization on the current limiting link of the converter:

[0045] S331, judging whether the current of each distributed renewable energy source in the original active distribution network has entered the limit range:

[0046] (a) When all distributed renewable energy sources have not entered the limit phase, there are:

[0047]

[0048] In the formula, I max (j) is the converter current limit of the jth distributed renewable energy source; i q (j) and i d (j) are the q-axis current and d-axis current of the j-th distributed renewable energy source; i q.eq and i d.eq are the reactive equivalent current and active equivalent current of the equivalent machine respectively; I max.eq is the limiting current of the equivalent machine;

[0049] (b) When the current of n1 distributed new energy converter exceeds its limit, and n-n1 does not exceed its limit, then:

[0050]

[0051] In the formula, n1 is the number of distributed renewable energy units whose converter current exceeds the limit, and n1 is a positive integer greater than or equal to 1 and less than n;

[0052] S332, according to equations (9) and (10), calculate the active equivalent current i of the equivalent machine d.eq and reactive equivalent current i q.eq , and then find the limiting current I of the equivalent machine max.eq ;

[0053] (c) When the current of all distributed renewable energy converters exceeds their limit, there are:

[0054]

[0055] Furthermore, in step S4, the particle swarm optimization algorithm is used to perform parameter identification on the linear module in the general model of the active distribution network, and the objective function is:

[0056]

[0057] Among them, P sim (i) and P real (i) represents the active power simulation results based on the general model and the detailed model, Q sim (i) and Q real (i) Represents the reactive power simulation results based on the general model and the detailed model respectively; K is the total number of points in the disturbed trajectory time window, and the sampling step is 10 -5 ; err is the error.

[0058] In a second aspect, the present invention relates to a general modeling device for an active distribution network including multiple types of distributed renewable energy sources, the modeling device comprising the following steps:

[0059] The distributed new energy low-order general model building module is used to compare the common points of various distributed new energy detailed models, simulate and analyze the dynamic characteristics of various distributed new energy under grid-side disturbances, and establish a distributed new energy low-order general model based on the analysis of the common points of the dynamic characteristics of various distributed new energy;

[0060] Distributed new energy low-order general model, which includes active power control module, reactive power control module, phase-locked loop module, low voltage active power management module, low voltage reactive power management module, amplitude limiting link and machine-network interface module;

[0061] An active distribution network general model building module is used to connect the obtained general model of distributed renewable energy and the comprehensive load model in parallel as the active distribution network general model; the comprehensive load model is the parallel connection of the induction motor and the static ZIP load;

[0062] The equivalent modeling module is used to perform equivalent modeling on multiple nonlinear modules including low-voltage active power management, low-voltage reactive power management and current limiting of converters in various types of distributed renewable energy in active distribution networks;

[0063] The parameter identification module is used to identify the parameters of the linear modules in the general model of the active distribution network using the particle swarm optimization algorithm; the linear modules include the active control module, reactive control module, phase-locked loop module, machine-grid interface module in the general model of distributed new energy, and the induction motor and static ZIP load in the comprehensive load model;

[0064] The final parameter value calculation module is used to integrate the identification results of the linear module and the equivalent results of the nonlinear module output by the equivalent modeling module to calculate the final parameter values ​​of the general model of the active distribution network.

[0065] In a third aspect, the present invention relates to a general modeling system for active distribution networks containing multiple types of distributed renewable energy, comprising:

[0066] one or more processors;

[0067] The memory stores operable instructions, which, when executed by the one or more processors, enable the one or more processors to perform operations, wherein the operations include the process of executing the above method.

[0068] The beneficial effects of the present invention are:

[0069] The general modeling method for generalized load of distribution network of multiple types of distributed power sources proposed in the present invention can accurately reflect the dynamic characteristics of generalized load under different distributed power generation proportions and different voltage drop degrees when taking into account the low voltage penetration characteristics and current limiting values ​​of multiple types of distributed power sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 The present invention is a flowchart of a general modeling method for an active distribution network containing multiple types of distributed renewable energy sources according to an embodiment of the present invention.

[0071] Figure 2 This is a schematic diagram of an actual active distribution network example.

[0072] Figure 3 Schematic diagram of a general simplified model of distributed power sources.

[0073] Figure 4 Schematic diagram of a generalized load model containing multiple types of distributed power sources.

[0074] Figure 5 The schematic diagram of power disturbance trajectory of the actual model and the simplified model under the scenario of voltage drop of 20% and distributed generation accounting for 100%; Figure 5 (a) corresponds to active power, Figure 5 (b) Corresponding reactive power.

[0075] Figure 6 The schematic diagram of power disturbance trajectory of the actual model and the simplified model under the scenario of voltage drop of 70% and distributed generation accounting for 100%; Figure 6 (a) corresponds to active power, Figure 6 (b) Corresponding reactive power. DETAILED DESCRIPTION

[0076] The present invention will now be described in further detail with reference to the accompanying drawings.

[0077] It should be noted that the terms such as "upper", "lower", "left", "right", "front", "back", etc. cited in the invention are only for the convenience of description and are not used to limit the scope of implementation of the present invention. Changes or adjustments to their relative relationships should be regarded as the scope of implementation of the present invention without substantially changing the technical content.

[0078] In combination with the embodiments of the present invention, a general modeling device for an active distribution network containing multiple types of distributed renewable energy sources is proposed. By analyzing the common points in the model structures, control methods and dynamic characteristics of different distributed renewable energy sources, a general modeling method suitable for multiple types of distributed power sources is proposed. The constructed model can reflect the general dynamics of multiple types of distributed renewable energy sources. The invented new energy general model is connected in parallel with the traditional load model as an equivalent model of the active distribution network. At the same time, the nonlinear links such as the low voltage ride-through module and the current limiting module of multiple types of renewable energy sources in the active distribution network are equivalent, and the linear modules in the active distribution network are parameter identified. The actual system verification shows that the model of the present invention can describe the dynamic characteristics of the active distribution network containing different distributed power generation proportions and different voltage drop degrees.

[0079] Figure 2 This is a schematic diagram of an actual active distribution network calculation example. It is an actual 35kV distribution network system in China. The system is built on the PSCAD / EMTDC platform. The resistance and reactance of each kilometer of cable line are 0.116Ω / km and 0.00034H / km respectively. The load of each node and the line parameters are also shown in the figure. Since the load of the industrial park is generally light industrial enterprises, small motors are generally used. In this embodiment, the motor parameters of the park are set to be the same, specifically: the stator resistance and reactance are R s =0.034pu and X s =0.00918pu, rotor resistance and reactance are R r =0.0607pu and X r =0.011pu, the rotor inertia time constant is H = 0.7s. The ZIP load uses a constant impedance load and the reactance / resistance ratio is 5.

[0080] In steady state, K DG =1, and the output of the doubly-fed wind turbine generator set, the output of the direct-drive permanent magnet wind turbine generator set and the output of photovoltaic power generation account for 30%, 40% and 30% respectively.

[0081] See also Figure 1 The general modeling method of active distribution network containing multiple types of distributed renewable energy sources according to the embodiment of the present invention specifically includes the following steps:

[0082] Step 1: Construct a low-order general model structure suitable for describing various types of distributed renewable energy.

[0083] First, the common features of the detailed models of various distributed renewable energy sources are compared, and the dynamic characteristics of various distributed renewable energy sources under grid-side disturbances are simulated and analyzed. Figure 3 The low-order general model of distributed renewable energy is shown in FIG. The model includes an active power control module, a reactive power control module, a phase-locked loop module, a low-voltage active power management module, a low-voltage reactive power management module, a limiting link, and a machine-grid interface module.

[0084] The input of the active power control module is the active power reference value, the control strategy adopts proportional integral control, and the output is the d-axis current i d .

[0085] The control strategy of the reactive power control module is one of constant power factor control, constant reactive power control and constant voltage control. The input under constant power factor control is the power factor angle, and the product of its tangent function and active power is the reactive power reference value. The input under constant reactive power control is the reactive power reference value. The input under constant voltage control is the voltage amplitude of the distributed new energy port. The control strategies under the three control modes are all proportional integral control, and the output is the q-axis current i q_normal ;

[0086] The input of the phase-locked loop module is the voltage phase angle of the distributed renewable energy outlet, the control strategy is proportional integral control and the series connection of integral control, and the output is the phase-locked angle;

[0087] In the low voltage reactive power management module, the q-axis current i q It is represented by the current i under normal control of the converter q_normal and the q-axis additional reactive current i during low voltage ride-through qLVRT The sum of the q-axis current and the current limit value I max In the reactive power priority control mode, there are:

[0088] i q =min{i q_normal +i qLVRT , I max} (1)

[0089] For direct-drive wind turbines, the additional reactive current is expressed as:

[0090] i qLVRT =k q (U n -U)=k q ΔU, 0≤U≤0.9U n (2)

[0091] For photovoltaic power generation units, the additional reactive current is expressed as:

[0092]

[0093] For doubly-fed wind turbines, the additional reactive current is 0.

[0094] In the formula, k q is the reactive support coefficient.

[0095] In the low voltage active power management module, the active power P of distributed renewable energy during low voltage ride-through LVRT P is the active power reference value during normal operation ref The value of parameter λ is related to the type of distributed renewable energy and the amplitude of the voltage at the renewable energy port. d The current is subject to the converter current limit Imax In the reactive power priority control mode, there are:

[0096]

[0097] For a doubly-fed wind turbine, λ is expressed as:

[0098]

[0099] For direct-drive wind turbines, λ is expressed as:

[0100]

[0101] For a photovoltaic power generation unit, λ=1.

[0102] Where U is the terminal voltage of distributed renewable energy, U n is the rated voltage, k p is the active support coefficient.

[0103] The machine-grid interface module uses a current source model to represent distributed renewable energy, and the output currents are i d and i q .

[0104] Step 2: The obtained general model of distributed renewable energy is connected in parallel with the traditional comprehensive load model as the general model of active distribution network. Figure 4 .

[0105] The comprehensive load model is a parallel connection of an induction motor and a static ZIP load.

[0106]

[0107] The output power ratio coefficient of distributed generation and the IM absorption power ratio coefficient are defined as K IM and K DG ,as follows:

[0108]

[0109] In the formula, K DG The value of represents the power transmission from DG to the grid and load. DG <1, it means the grid delivers power to the load; and when K DG When >1, DG can not only meet the power supply demand of the load but also transmit the excess power to the grid.

[0110] Step 3: Equivalent modeling of nonlinear modules such as low-voltage active power management, low-voltage reactive power management, and current limiting of converters for various types of distributed renewable energy in active distribution networks. The details are as follows:

[0111] The perturbation is set as:

[0112] Disturbance 1: The voltage of busbar B2 drops by 20% U n ,

[0113] Disturbance 2: The voltage of busbar B2 drops by 70% U n ,

[0114] The fault duration is 0.2s, and the system returns to its original state after the fault disappears.

[0115] When the low voltage active power management model is equal, the sum of the active power of all distributed renewable energy sources is the active power P of the equivalent machine. eq.ref , so we have:

[0116]

[0117] Where P eq.ref is the active power reference value of the equivalent machine, P g.ref is the active power reference value of distributed generation, λ eq is the coefficient of the equivalent machine, j is the jth distributed renewable energy source; n is the total number of distributed renewable energy sources in the distribution network. eq.ref and It is known that according to the above formula, the λ of the equivalent machine can be obtained eq .

[0118] When the low voltage reactive power management model is equal, the reactive additional current i of the equal value machine is qLVRT.eq It is the sum of the reactive additional current of all distributed renewable energy sources during low voltage ride-through, that is:

[0119]

[0120] Among them, i qLVRT.eq is the reactive additional current of the equivalent machine; k q.eq is the reactive support coefficient of the equivalent machine.

[0121] When the current limit link is equal, it needs to be determined based on whether the current of each distributed renewable energy source in the original active distribution network enters the limit, as follows:

[0122] (a) When all distributed renewable energy sources have not entered the limit phase, there are:

[0123]

[0124] (b) When the current of n1 distributed new energy converter exceeds its limit, and n-n1 does not exceed its limit, then:

[0125]

[0126] According to equations (11) and (12), first calculate the active equivalent current i of the equivalent machine d.eq and reactive equivalent current i q.eq , and then according to the above formula, the limiting current I of the equivalent machine is obtained max.eq .

[0127] (c) When the current of all distributed renewable energy converters exceeds their limit,

[0128]

[0129] In the formula, i d.eq is the active equivalent current of the equivalent machine, i q.eq is the reactive equivalent current of the equivalent machine, I max.eq is the current limit of the equivalent machine, and n1 is the number of distributed renewable energy units whose converter current exceeds the limit.

[0130] According to formula (9) and formula (10), 20% U n Voltage drop λ eq =0.8998, k q.eq =0.2923; 70% U n Voltage drop disturbance eq =0.4301, k q.eq =0.9946. Under the two disturbances, the current of distributed renewable energy did not reach the limit value. According to formula (11), I max.eq =1.2741.

[0131] Step 4: Use the particle swarm optimization algorithm to identify the parameters of the general model of the active distribution network and obtain the parameters of the general model of the active distribution network.

[0132] Take 20%U n Based on the disturbed trajectory of active power and reactive power of bus B2 under voltage drop, the parameters to be identified are {R DG ,X DG ,R CLM ,X CLM ,K pp1 ,K pi1 ,K qp1 ,K qi1 ,K PLLp ,K PLLi ,X s ,H,s0,K DG ,K IM}, where s0 is the initial slip of the equivalent motor. The parameter identification objective is The subscripts sim and real represent the simulation results based on the general model and the detailed model, respectively. K is the total number of points in the disturbed trajectory time window, and the sampling step is 10. -5, err is the error.

[0133] The particle swarm optimization algorithm is used for parameter identification. The parameter identification results are shown in Table 1.

[0134] Table 1 Parameter identification results

[0135] parameter Identification value parameter Identification value <![CDATA[R DG (Oh)]]> 2.8714 <![CDATA[L DG (H)]]> 0.02122 <![CDATA[K pp ]]> 2.8821 <![CDATA[K pi ]]> 0.1290 <![CDATA[K qp ]]> 1.1114 <![CDATA[K qi ]]> 0.3437 <![CDATA[K θp ]]> 114.1579 <![CDATA[K θi ]]> 2800.2345 <![CDATA[R CLM (Oh)]]> 2.1743 <![CDATA[L CLM (H)]]> 0.01925 <![CDATA[X s ]]> 0.01014 H(s) 0.7711 <![CDATA[S0]]> 0.0269 / <![CDATA[K DG ]]> 107.9117 <![CDATA[K IM ]]> 56.0269

[0136] Based on the parameter identification results in Table 1, the disturbance trajectories of the original active distribution network detailed model and the proposed active distribution network simplified model are compared. Figure 5 .

[0137] Based on the parameter identification results in Table 1 and 70% U n λ calculated under voltage drop disturbance eq =0.4301, k q.eq =0.9946, compared with 70% U n The disturbed trajectories of the original detailed model and the proposed simplified model of active distribution network under voltage sag disturbance. Figure 5 The feasibility of the invented simplified model of active distribution network was verified. Figure 6 The adaptability of the proposed simplified model of active distribution network is verified.

[0138] The above are only preferred embodiments of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A general modeling method for active distribution networks containing multiple types of distributed renewable energy sources, characterized in that: The modeling method comprises the following steps: S1, comparing the common points of various distributed renewable energy detailed models, simulating and analyzing the dynamic characteristics of various distributed renewable energy under grid-side disturbance, and establishing a low-order general model of distributed renewable energy based on the analysis of the common points of the dynamic characteristics of various distributed renewable energy; the distributed renewable energy low-order general model includes an active power control module, a reactive power control module, a phase-locked loop module, a low-voltage active power management module, a low-voltage reactive power management module, a limiting link and a machine-grid interface module; S2, connecting the obtained distributed new energy general model and the comprehensive load model in parallel as a general model of the active distribution network; the comprehensive load model is a parallel connection of an induction motor and a static ZIP load; S3, equivalent modeling of multiple nonlinear modules including low voltage active power management, low voltage reactive power management and current limiting of converter in multiple types of distributed renewable energy in active distribution network; S4, using particle swarm optimization algorithm, to identify the parameters of linear modules in the general model of active distribution network; linear modules include active control module, reactive control module, phase-locked loop module, machine-grid interface module in the general model of distributed new energy, and induction motor and static ZIP load in the comprehensive load model; S5, integrating the identification results of the linear module with the equivalent results of the nonlinear module in step S2, and calculating the final parameter values ​​of the general model of the active distribution network; In step S1, the input of the active power control module is the active power reference value, the control strategy adopts proportional integral control, and the output is the d-axis current i d ; The control strategy of the reactive power control module is one of the three control methods: constant power factor control, constant reactive power control and constant voltage control. The control strategies under the three control modes are all proportional integral control, and the output is the q-axis current i q_normal ; Among them, the input under constant power factor control is the power factor angle, and the product of its tangent function and active power is the reactive power reference value; the input under constant reactive power control is the reactive power reference value; the input under constant voltage control is the voltage amplitude of the distributed new energy port; The input of the phase-locked loop module is the voltage phase angle of the distributed new energy outlet, the control strategy is proportional integral control and the series connection of integral control, and the output is the phase-locked angle; In the low voltage reactive power management module, the q axis current i q It is represented by the current i under normal control of the converter q_normal and the q-axis additional reactive current i during low voltage ride-through qLVRT The sum of the q-axis current i q Affected by the converter current limit I max In the reactive power priority control mode, there are: in q =min{i q_normal +i qLVRT ,IN max }(1); For direct-drive wind turbines, the additional reactive current is expressed as: i qLVRT =k q (U n -U),0≤U≤0.9U n (2); For photovoltaic power generation units, the additional reactive current is expressed as: For doubly-fed wind turbines, the additional reactive current is 0; In the formula, k q is the reactive power support coefficient, U is the port voltage of distributed renewable energy, and U n is the rated voltage; In the low voltage active power management module, the active power P of the distributed new energy during the low voltage ride-through period LVRT P is the active power reference value during normal operation ref The value of parameter λ is related to the type of distributed renewable energy and the amplitude of the voltage at the renewable energy port. d Affected by the converter current limit I max In the reactive power priority control mode, there are: For a doubly-fed wind turbine, λ is expressed as: For direct-drive wind turbines, λ is expressed as: For photovoltaic power generation units, λ = 1; In the formula, k p is the active support coefficient; The machine-grid interface module uses a current source model to represent distributed renewable energy, and the output currents are i d and i q .

2. The general modeling method for active distribution network containing multiple types of distributed renewable energy sources according to claim 1 is characterized in that: In step S3, the process of equivalent modeling of multiple nonlinear modules including low voltage active power management, low voltage reactive power management and current limiting of converters in multiple types of distributed renewable energy in the active distribution network includes the following steps: S31, perform the equivalent of low voltage active power management model: S311, let the sum of the active powers of all distributed renewable energy sources be the active power P of the equivalent machine eq.ref : Where P eq.ref is the active power reference value of the equivalent machine, P gref (j) is the active power reference value of the jth distributed renewable energy source, λ eq is the coefficient of the equivalent machine, j is the jth distributed renewable energy, λ(j) is the value of the parameter λ of the jth distributed renewable energy; n is the total number of distributed renewable energy in the distribution network; S312,P eq.ref and It is known that according to formula (7), the λ of the equivalent machine is obtained eq ; S32, perform the equivalent of low voltage reactive power management model: Assume the reactive additional current i of the equivalent machine qLVRT.eq It is the sum of the reactive additional current of all distributed renewable energy sources during low voltage ride-through, that is: Among them, i qLVRT.eq is the reactive additional current of the equivalent machine; k q.eq is the reactive support coefficient of the equivalent machine; k q (j) is the reactive power support coefficient of the jth distributed renewable energy source, ΔU(j) is the rated voltage U of the jth distributed renewable energy source n The difference between the terminal voltage U and the eq is the rated voltage U of the equivalent machine n And the terminal voltage U eq The difference between S33, perform equalization on the current limiting link of the converter: S331, judging whether the current of each distributed renewable energy source in the original active distribution network has entered the limit range: (a) When all distributed renewable energy sources have not entered the limit phase, there are: In the formula, I max (j) is the converter current limit of the jth distributed renewable energy source; i q (j) and i d (j) are the q-axis current and d-axis current of the j-th distributed renewable energy source; i q.eq and i d.eq are the reactive equivalent current and active equivalent current of the equivalent machine respectively; I max.eq is the limiting current of the equivalent machine; (b) When the current of n1 distributed new energy converter exceeds its limit, and n-n1 does not exceed its limit, then: In the formula, n1 is the number of distributed renewable energy units whose converter current exceeds the limit, and n1 is a positive integer greater than or equal to 1 and less than n; S332, according to equations (9) and (10), calculate the active equivalent current i of the equivalent machine d.eq and reactive equivalent current i q.eq , and then find the limiting current I of the equivalent machine max.eq ; (c) When the current of all distributed renewable energy converters exceeds their limit, there are:

3. The general modeling method of active distribution network containing multiple types of distributed renewable energy sources according to claim 1 is characterized in that: In step S4, the particle swarm optimization algorithm is used to perform parameter identification on the linear module in the general model of the active distribution network. The objective function is: Among them, P sim (i) and P real (i) represents the active power simulation results based on the general model and the detailed model, Q sim (i) and Q real (i) Represents the reactive power simulation results based on the general model and the detailed model respectively; K is the total number of points in the disturbed trajectory time window, and the sampling step is 10 -5 s; err is the error.

4. A general modeling device for active distribution network containing multiple types of distributed renewable energy sources based on the method of claim 1, characterized in that: The modeling device comprises the following steps: The distributed new energy low-order general model building module is used to compare the common points of various distributed new energy detailed models, simulate and analyze the dynamic characteristics of various distributed new energy under grid-side disturbances, and establish a distributed new energy low-order general model based on the analysis of the common points of the dynamic characteristics of various distributed new energy; Distributed new energy low-order general model, which includes active power control module, reactive power control module, phase-locked loop module, low voltage active power management module, low voltage reactive power management module, amplitude limiting link and machine-network interface module; The active distribution network general model building module is used to connect the obtained distributed new energy equivalent model and the comprehensive load model in parallel as the active distribution network general model; the comprehensive load model is the parallel connection of the induction motor and the static ZIP load; The equivalent modeling module is used to perform equivalent modeling on multiple nonlinear modules including low-voltage active power management, low-voltage reactive power management and current limiting of converters in various types of distributed renewable energy in active distribution networks; The parameter identification module is used to identify the parameters of the linear modules in the general model of the active distribution network using the particle swarm optimization algorithm; the linear modules include the active control module, reactive control module, phase-locked loop module, machine-grid interface module in the general model of distributed new energy, and the induction motor and static ZIP load in the comprehensive load model; The final parameter value calculation module is used to integrate the identification results of the linear module and the equivalent results of the nonlinear module output by the equivalent modeling module to calculate the final parameter values ​​of the general model of the active distribution network.

5. A general modeling system for active distribution networks containing multiple types of distributed renewable energy, characterized in that: include: one or more processors; A memory storing operable instructions, wherein when the instructions are executed by the one or more processors, the one or more processors are caused to perform operations, wherein the operations include the process of executing the method described in any one of claims 1 to 3.

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