A generalized load modeling method considering distributed photovoltaic power generation system

Abstract

The application discloses a generalized load modeling method considering a distributed photovoltaic power generation system, and comprises the following steps: S1, a power distribution network simulation model containing a photovoltaic power generation system, static load and induction motor model is built in PSCAD; S2, a power grid voltage drop fault is set, and voltage data and active and reactive power dynamic data of a load bus are obtained according to the power distribution network simulation model; S3, a generalized load model is established, and the voltage data and the active and reactive power dynamic data of the load bus are combined to select an error calculation criterion function, and parameters in the generalized load model are identified; and S4, the generalized load modeling parameters are corrected according to the parameter identification result, and the step S3 is returned until the error calculation criterion function output meets preset requirements, and finally, the parameter identification result is obtained. The application makes up for the deficiency that the traditional power distribution network load model cannot accurately describe the reactive dynamic response characteristics under voltage fault, and has important practical significance.

Description

Technical Field

[0001] This invention relates to the field of power electronics technology, and more specifically to a generalized load modeling method for distributed photovoltaic power generation systems. Background Technology

[0002] Currently, a large number of distributed power sources are being connected to the distribution network of the new power system, and the penetration rate of distributed photovoltaics in the distribution network is constantly increasing. Source-load mismatch leads to bidirectional power flow, which in turn affects the load characteristics of the distribution network, making traditional load models difficult to apply.

[0003] In practical engineering, the load model used consists of a static load model and an induction motor model, without considering distributed photovoltaic (PV) systems. Equivalent modeling of PV power generation systems is divided into mechanistic and non-mechanistic models. Mechanistic models can better describe the transient characteristics of PV power generation systems, but they suffer from an excessive number of model parameters. Since PV power generation systems do not contain rotating equipment, non-mechanistic static load models are often used to characterize the grid-connected characteristics of PV power generation systems. In generalized load modeling that considers distributed PV power generation systems, a mechanistic model of the distributed PV power generation system is generally added to the static load model and induction motor model. However, this generalized load modeling method increases the complexity of the model and the number of parameters, making parameter identification more difficult and hindering its suitability for large-scale power system simulations, thus increasing the difficulty of practical application.

[0004] To address this, some scholars have proposed using polynomial static load models to characterize the power characteristics of distributed photovoltaic (PV) systems. However, traditional polynomial static load models cannot characterize the reactive power characteristics of PV systems under fault conditions. Based on the relationship between distributed PV output power and terminal voltage changes, some scholars have proposed an equivalent model of distributed PV based on an improved polynomial static load model, establishing a generalized load model that considers distributed PV systems, thus overcoming the shortcomings of traditional distribution network load models. However, considering the dynamic influence of different parameters on the load model, the problem of too many identified parameters still exists, which to some extent hinders the practical application of the generalized load model considering distributed PV systems. Summary of the Invention

[0005] The technical problem to be solved by the embodiments of the present invention is to provide a generalized load modeling method for distributed photovoltaic power generation systems, so as to reduce the parameters to be identified in the model and promote the practical application of generalized load models for distributed photovoltaic power generation systems.

[0006] To address the aforementioned technical problems, this invention provides a generalized load modeling method considering distributed photovoltaic power generation systems, comprising:

[0007] Step S1: Build a power distribution network simulation model in PSCAD that includes a photovoltaic power generation system, static load, and induction motor model;

[0008] Step S2: Set up a grid voltage drop fault and obtain the voltage data of the load bus and the dynamic data of active and reactive power according to the distribution network simulation model.

[0009] Step S3: Establish a generalized load model, and combine the obtained voltage data of the load bus and the dynamic data of active and reactive power to select the error calculation criterion function and identify the parameters in the generalized load model.

[0010] Step S4: Correct the generalized load modeling parameters based on the parameter identification results, and return to step S3 until the error calculation criterion function output meets the preset requirements to obtain the final parameter identification results.

[0011] Furthermore, the generalized load model established in step S3 includes: the distribution network simulation model established in step S1, and the equivalent model of the dynamic characteristics of the photovoltaic power generation system.

[0012] Furthermore, the power balance expression for the generalized load model is as follows:

[0013]

[0014]

[0015] Among them, P g Q g These represent the active and reactive power output from the power grid, respectively; P PV Q PV These represent the active and reactive power generated by the photovoltaic power generation system, respectively; P load Q load These represent the total active power and total reactive power consumed by the load, respectively; P M Q M These represent the active and reactive power absorbed by the dynamic load, respectively; P ZIP Q ZIP These represent the active and reactive power absorbed by the static load, respectively.

[0016] Furthermore, the equivalent model of the dynamic characteristics of the photovoltaic power generation system is as follows:

[0017]

[0018] Where P and Q are the actual active power and actual reactive power, respectively; P0 and Q0 are the steady-state active power and steady-state reactive power, respectively; U is the actual load voltage; and U0 is the standard load voltage. pu n quThese are the voltage characteristic indices for active power and reactive power of the load, respectively.

[0019] Furthermore, the error calculation criterion function is:

[0020]

[0021] Where N is the data length, P meas (i), Q meas (i) represents the measured active and reactive power; P g (i), Q g (i) represents the active and reactive power of the generalized load model.

[0022] Furthermore, in step S3, the parameters for identifying the generalized load model include: the voltage characteristic index of the active power and the voltage characteristic index of the reactive power of the load; the proportional coefficient of the active load and the proportional coefficient of the reactive load; the stator reactance and initial slip of the induction motor; the proportion of the output power of the photovoltaic power generation system to the total load and the proportion of the power consumed by the induction motor to the total load power.

[0023] Furthermore, the modeling bus is the load bus, and also the grid connection point of the distributed photovoltaic power generation system.

[0024] Furthermore, the method also includes: comparing the generalized load model with simulation and measured data to verify the accuracy of the model.

[0025] Implementing this invention has the following beneficial effects: This invention proposes an improved power function static load model for distributed photovoltaic (PV) systems, introducing the correlation between distributed PV output power and terminal voltage changes as a variable. This simplifies the order of the PV mechanism model while maintaining accuracy within a certain range. Furthermore, it proposes a generalized load model considering distributed PV power generation systems, overcoming the shortcomings of traditional distribution network load models in accurately describing reactive power dynamic response characteristics under voltage faults. This has significant practical implications for advancing the practical application of generalized load models considering distributed PV power generation systems. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart illustrating a generalized load modeling method for distributed photovoltaic power generation systems according to an embodiment of the present invention.

[0028] Figure 2 This is a schematic diagram illustrating the low-voltage ride-through capability requirements of a photovoltaic power station in an embodiment of the present invention.

[0029] Figure 3 This is a schematic diagram of the main circuit topology and control structure of the distributed photovoltaic power generation system in an embodiment of the present invention.

[0030] Figure 4(a) is a schematic diagram of the change curve of PCC voltage (per unit value) when a short circuit fault occurs in PCC and causes a voltage drop; Figure 4(b) is a schematic diagram of the dynamic response of the active and reactive power output of the photovoltaic power generation system when a short circuit fault occurs in PCC and causes a voltage drop.

[0031] Figure 5(a) is a schematic diagram comparing the dynamic response of active power of the photovoltaic detailed model and the equivalent model in the embodiment of the present invention, and Figure 5(b) is a schematic diagram comparing the dynamic response of reactive power of the photovoltaic detailed model and the equivalent model in the embodiment of the present invention.

[0032] Figure 6(a) is a schematic diagram comparing the dynamic response of active power of the photovoltaic detailed model and the improved equivalent model in the embodiment of the present invention, and Figure 6(b) is a schematic diagram comparing the dynamic response of reactive power of the photovoltaic detailed model and the improved equivalent model in the embodiment of the present invention.

[0033] Figure 7 This is a schematic diagram of the generalized load modeling structure of the distributed photovoltaic power generation system in an embodiment of the present invention. Detailed Implementation

[0034] The following description of the embodiments is taken with reference to the accompanying drawings, which illustrate specific embodiments in which the invention can be implemented.

[0035] Please refer to Figure 1 As shown, this embodiment of the invention provides a generalized load modeling method considering distributed photovoltaic power generation systems, including:

[0036] Step S1: Build a power distribution network simulation model in PSCAD that includes a photovoltaic power generation system, static load, and induction motor model;

[0037] Step S2: Set up a grid voltage drop fault and obtain the voltage data of the load bus and the dynamic data of active and reactive power according to the distribution network simulation model.

[0038] Step S3: Establish a generalized load model, and combine the obtained voltage data of the load bus and the dynamic data of active and reactive power to select the error calculation criterion function and identify the parameters in the generalized load model.

[0039] Step S4: Correct the generalized load modeling parameters based on the parameter identification results, and return to step S3 until the error calculation criterion function output meets the preset requirements to obtain the final parameter identification results.

[0040] Specifically, firstly, we compare the polynomial static load model with the power function static load model.

[0041] Polynomial models and power function models are often used to describe the static load characteristics of power systems. A polynomial model establishes the relationship between power and voltage at the load bus using polynomial equations; its basic structure is shown below:

[0042]

[0043] Where P0 and Q0 are active power and reactive power, respectively; P Z P I P P These are the coefficients of the quadratic, linear, and constant terms of the load polynomial model, respectively.

[0044] The power function model establishes the relationship between power and voltage on the load bus through exponential equations. Its basic structure is shown below:

[0045]

[0046] Where, n pu n qu These are the voltage characteristic indices for active power and reactive power of the load, respectively.

[0047] A comparison of the advantages and disadvantages of polynomial static load models and power function static load models in terms of parameters and model accuracy: In terms of parameters, the power function model has the fewest parameters, while the polynomial model has more parameters; in terms of model accuracy, the power function model has higher accuracy and stronger model versatility.

[0048] The dynamic characteristics of distributed photovoltaic (PV) power generation systems are mainly determined by PV inverters and their control systems. GB / T19964-2012, "Technical Specifications for Grid Connection of Photovoltaic Power Stations to Power Systems," requires PV power stations to have low voltage ride-through (LVRT) capability. Figure 2 Low voltage ride-through requirements that photovoltaic power plants must meet:

[0049] a) When the voltage at the grid connection point of the photovoltaic power station drops to 0, the photovoltaic power station should be able to operate continuously without disconnecting from the grid for 0.15 seconds;

[0050] b) When the voltage at the grid connection point of the photovoltaic power station drops below curve 1, the photovoltaic power station can be disconnected from the grid.

[0051] Therefore, an LVRT control strategy has been incorporated into the control circuit of the distributed photovoltaic inverter. When a short-circuit fault in the power system causes a voltage drop, the dynamic reactive current injected into the grid by the photovoltaic power station enhances the reactive power support capability of the distributed photovoltaic power generation system, maintaining grid-connected operation of the device for a period of time. The dynamic reactive current injected into the grid under fault conditions should meet the following requirements:

[0052]

[0053] Among them, I dref I represents the dynamic reactive current injected into the power grid under fault conditions. N U is the rated current on the AC side of the distributed photovoltaic power station. T This is the per-unit value of the rated voltage on the AC side of a distributed photovoltaic power station.

[0054] This invention takes a single power generation unit in a photovoltaic power station as an example. A simulation model of a distributed photovoltaic power generation system with an LVRT control strategy is built in PSCAD (Power Systems Computer-Aided Design, a power electronics software for designing and simulating complex power systems). The main circuit topology and control structure are as follows: Figure 3 As shown. When a short-circuit fault occurs at the common coupling point PCC, causing a voltage drop, the PCC voltage (per unit value) change curve is as follows. Figure 4a As shown, the dynamic response of the photovoltaic power generation system to active and reactive power output is as follows: Figure 4b As shown.

[0055] Based on the above simulation results, transient simulation calculations were performed on an equivalent photovoltaic power generation system using a power-function static load model. A comparison of the active and reactive power transient response characteristics of the photovoltaic power generation system and the power-function static load model is shown in the figure below. Figure 5a , Figure 5b As shown in the figure, the active power dynamic response of the power function static load model can fit the active power dynamic characteristics of the photovoltaic power generation system well, while the reactive power dynamic response deviates significantly from the reactive power dynamic characteristics of the photovoltaic power generation system.

[0056] This invention transforms the power function static load model to provide an equivalent model that can describe the dynamic characteristics of the output power of a photovoltaic power generation system under fault conditions.

[0057] Comparing the reactive power dynamic response of the detailed photovoltaic model and the equivalent model reveals that the power function model can characterize the reactive power response characteristics during the fault process. However, the reactive power output in steady state is very small or even zero, and the power function model cannot characterize its reactive power characteristics. Therefore, this invention mainly improves the reactive power model in the power function model.

[0058] Depend on Figure 4a ,Figure 4b It can be seen that during power system faults, the dynamic changes in active power of the photovoltaic power generation system are positively correlated with voltage changes, while the dynamic changes in reactive power are negatively correlated with voltage changes. Therefore, the reactive power part of equation (2) is transformed, with the voltage change as the independent variable of the reactive power model. At the same time, in order to enable the improved power function model to describe the reactive power characteristics of the photovoltaic power generation system under steady state, a constant term is added to the reactive power model, resulting in the equivalent photovoltaic power generation system of the polynomial model shown in equation (4).

[0059]

[0060] Compared to the power function static load model, the reactive power output of the power function model shown in equation (4) is 0 in steady state. Under fault conditions, the reactive power output changes with voltage disturbances, reflecting the reactive power compensation effect of the photovoltaic power generation system. Therefore, as long as the voltage characteristic index n of the reactive power is... qu With proper selection, the power function model shown in equation (4) can characterize the load characteristics.

[0061] A simulation model of a distributed photovoltaic power generation system with LVRT control strategy was built in PSCAD. A voltage drop fault in the power system was set, and the equivalent model shown in Equation (4) was used for transient simulation calculation. The transient response characteristics of active and reactive power of the photovoltaic power generation system and the power function static load model were compared. The comparison results are as follows: Figure 6a , Figure 6b As shown.

[0062] Depend on Figure 5a , Figure 5b and Figure 6a , Figure 6b It can be seen that, under the same voltage disturbance, the equivalent model of the photovoltaic power generation system based on the improved power function can better describe its active and reactive power transient response characteristics. In this case, the power function model has only two parameters to be identified, which is half the number compared to the polynomial model. Therefore, the power function model is more suitable for large-scale power system simulations.

[0063] Load modeling of distribution networks containing distributed photovoltaic (PV) systems generally involves paralleling the mechanistic model of the distributed PV system with a static load model and an induction motor model to form a generalized load model. As the capacity of distributed PV systems increases annually, the dynamic characteristics of PV systems should be reflected in the integrated load model. Its equivalent model is then incorporated into the distribution network load model, thus forming a generalized integrated load model. Its basic structure is as follows: Figure 7 As shown.

[0064] Among them, P g Q g These represent the active and reactive power output from the power grid, respectively; P PVQ PV These represent the active and reactive power generated by the photovoltaic power generation system, respectively; P load Q load These represent the total active power and total reactive power consumed by the load, respectively; P M Q M These represent the active and reactive power absorbed by the dynamic load, respectively; P ZIP Q ZIP These represent the active and reactive power absorbed by the static load, respectively. The dynamic load is described using a third-order induction motor model, while the static load is described using a ZIP model. The photovoltaic power generation system is described using the equivalent model of the photovoltaic power generation system with the improved power function proposed in this invention. It should be noted that the modeling bus is also the load bus and the grid connection point of the distributed photovoltaic power generation system.

[0065] Based on the generalized load modeling structure that takes into account distributed photovoltaic power generation systems, the power balance expression of the generalized load model can be established as follows:

[0066]

[0067]

[0068] It is understandable that the independent parameters that have a significant impact on dynamic characteristics in the generalized load model of the distribution network include: power function model n pu n qu The proportionality factor 'a' of active load in the ZIP model p b p The proportionality coefficient a of reactive load q b q Stator reactance X of induction motor S Initial slip s0. In addition, the proportion of different load powers to the total power should be considered, requiring the addition of an independent parameter k, which represents the proportion of photovoltaic power generation system output power to the total load. PV and the proportion of power consumed by the induction motor to the total load power, k m .

[0069] Therefore, in the generalized load modeling method for distributed photovoltaic power generation systems in this embodiment of the invention, step S1 constructs a distribution network model in PSCAD that includes the photovoltaic power generation system, static load, and induction motor models to generate voltage and power data under actual conditions. To simulate potential fault conditions in the actual power grid, step S2 sets up a grid voltage dip fault, which allows the acquisition of voltage data for the load bus (a key connection point in the power grid) and dynamic data on active and reactive power (actual efficiency and ineffective power consumption in the power grid). Step S3 utilizes the established generalized load model and the acquired dynamic data on grid-connected bus voltage, active power, and reactive power to select a suitable error calculation criterion function and use an intelligent algorithm (such as machine learning or optimization algorithms) to identify these independent parameters. Step S4 corrects the generalized load modeling parameters based on the identification results. This process may require iterative steps until the error function output meets preset requirements, and then the parameter identification results are output. Finally, the accuracy of the model is verified by comparing the generalized load model with simulation / measured data. In short, this embodiment first builds and uses a simulation model to generate data in a specific environment, then uses this data and intelligent algorithms to train and optimize a load model that can accurately reflect the behavior of the grid after the injection of distributed photovoltaic power generation, and finally verifies the accuracy of this model.

[0070] It should be noted that the error calculation criterion function selected in this embodiment of the invention is as shown in equation (7):

[0071]

[0072] Where N is the data length, P meas (i), Q meas (i) represents the measured active and reactive power; P g (i), Q g (i) represents the active and reactive power of the generalized load model.

[0073] As explained above, compared with existing technologies, the beneficial effects of this invention are as follows: This invention proposes an improved power function static load model for distributed photovoltaic (PV) systems, introducing the correlation between distributed PV output power and terminal voltage changes as a variable. This simplifies the order of the PV mechanism model while maintaining accuracy within a certain range. Furthermore, it proposes a generalized load model considering distributed PV power generation systems, overcoming the shortcomings of traditional distribution network load models in accurately describing reactive power dynamic response characteristics under voltage faults. This has significant practical implications for advancing the practical application of generalized load models considering distributed PV power generation systems.

[0074] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A generalized load modeling method considering distributed photovoltaic power generation systems, characterized in that, include: Step S1: Build a power distribution network simulation model in PSCAD that includes a photovoltaic power generation system, static load, and induction motor model; Step S2: Set up a grid voltage drop fault and obtain the voltage data of the load bus and the dynamic data of active and reactive power according to the distribution network simulation model. Step S3: Establish a generalized load model, and combine the obtained voltage data of the load bus and the dynamic data of active and reactive power to select the error calculation criterion function and identify the parameters in the generalized load model. Step S4: Correct the generalized load modeling parameters based on the parameter identification results, and return to step S3 until the error calculation criterion function output meets the preset requirements to obtain the final parameter identification results. The generalized load model established in step S3 includes: the distribution network simulation model established in step S1, and the equivalent model of the dynamic characteristics of the photovoltaic power generation system. The power balance expression for the generalized load model is as follows: in, P g , Q g These are the active and reactive power output from the power grid, respectively. P PV Q PV These represent the active and reactive power generated by the photovoltaic power generation system, respectively. P load , Q load These represent the total active power and total reactive power consumed by the load, respectively. P M , Q M These represent the active and reactive power absorbed by the dynamic load, respectively. P ZIP , Q ZIP These represent the active and reactive power absorbed by the static load, respectively. The equivalent model of the dynamic characteristics of the photovoltaic power generation system is as follows: in, P , Q These are the actual active power and the actual reactive power, respectively. P 0、 Q 0 represents steady-state active power and steady-state reactive power, respectively. U This is the actual voltage of the load. U 0 represents the standard load voltage; n pu , n qu These are the voltage characteristic indices for active power and reactive power of the load, respectively.

2. The method according to claim 1, characterized in that, The error calculation criterion function is: in, N For data length, P meas ( i ), Q meas ( i () represents the measured active and reactive power; P g ( i ), Q g ( i ) represents the active and reactive power of the generalized load model.

3. The method according to claim 1, characterized in that, In step S3, the parameters for identifying the generalized load model include: the voltage characteristic index of the active power and the voltage characteristic index of the reactive power of the load; the proportional coefficient of the active load and the proportional coefficient of the reactive load; the stator reactance and initial slip of the induction motor; the proportion of the output power of the photovoltaic power generation system to the total load and the proportion of the power consumed by the induction motor to the total load power.

4. The method according to claim 1, characterized in that, The modeling bus is the load bus and also the grid connection point of the distributed photovoltaic power generation system.

5. The method according to claim 1, characterized in that, Also includes: The accuracy of the generalized load model is verified by comparing it with simulation and measured data.

Images