New energy multi-station converter control method, system, equipment, medium and product based on network tracking-network construction adaptive fusion

Abstract

The invention discloses a new energy multi-station converter control method, system, device, medium and product based on network following-construction adaptive fusion, and relates to the field of new energy, the method comprises the following steps: calculating a new energy multi-station short circuit ratio; based on the new energy multi-station short-circuit comparison, carrying out adaptive fusion on network following control and network construction control to obtain fusion control; and controlling the new energy multi-station converter based on fusion control. According to the invention, self-adaptive fusion can be carried out on the grid following and grid construction control of the converter according to the new energy multi-station short-circuit ratio, so that the strong and weak grid oscillation stability of the converter is improved.

Description

Technical Field

[0001] This application relates to the field of new energy, and in particular to a control method, system, equipment, medium and product for new energy multi-site converters based on adaptive fusion of grid connection and grid construction. Background Technology

[0002] Wind power, photovoltaic, and other new energy units are connected to the AC grid via power electronic converters. The converter control modes mainly include two types: grid-following (GFL) control and grid-forming (GFM) control. GFL control relies on a phase-locked loop (PLL) to track the voltage phase at the grid connection point; GFM control utilizes a power synchronization control (PSC) or DC voltage synchronization link to construct a virtual internal potential frequency / phase, which requires reliance on the AC grid. In summary, grid-following converters are susceptible to oscillation risks in weak grids, but exhibit better oscillation stability in strong grids. In contrast, grid-forming converters have good oscillation stability in weak grids but are prone to oscillation instability in strong grids. The oscillation characteristics of the two types under different grid strengths are complementary.

[0003] The randomness and volatility of renewable energy output cause the operating conditions of generating units to exhibit time-varying characteristics, which may further lead to fluctuations in the grid intensity. However, single GFL control or GFM control is insufficient to ensure that the converter maintains oscillatory stability under time-varying grid intensity conditions. GFL-GFM switching control switches the converter control mode based on the short circuit ratio (SCR), and simulations have verified that the switching control has good stability against both strong and weak grid oscillations. However, with the increasing proportion of renewable energy in the power system and the diversification of access methods, some areas have seen renewable energy integrated into weak AC grids, which is one of the contributing factors to problems such as broadband oscillations and overvoltages. Hybrid synchronous control allows the converter to have both GFL and GFM control characteristics during faults, but the proportion of GFL or GFM control output presented by the hybrid synchronous control is fixed and cannot be adaptively adjusted online, which is insufficient to adapt to complex and variable grid operating conditions. Summary of the Invention

[0004] The purpose of this application is to provide a control method, system, equipment, medium and product for converters in new energy multi-sites based on adaptive fusion of grid connection and grid construction. It can improve the stability of the converter in strong and weak grid oscillations by adaptively fusing the grid connection and grid construction control of the converter according to the short-circuit ratio of the new energy multi-sites.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] Firstly, this application provides a control method for converters in multiple new energy power plants based on adaptive fusion of grid connection and network structure, including:

[0007] Calculate the short-circuit ratio of multiple new energy power plants;

[0008] Based on the short-circuit comparison of the new energy multi-station grid-following control and grid-building control, adaptive fusion is performed to obtain fused control;

[0009] This system controls the converters at multiple new energy power plants based on integrated control.

[0010] Secondly, this application provides a new energy multi-station converter control system based on grid-connection adaptive fusion, including:

[0011] The calculation unit is used to calculate the short-circuit ratio of multiple new energy power stations;

[0012] The fusion unit is used to adaptively fuse the grid-following control and grid-building control based on the short-circuit comparison of the new energy multi-sites to obtain fused control;

[0013] The control unit is used to control the converters of multiple new energy power plants based on fusion control.

[0014] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described new energy multi-station converter control method based on grid-network adaptive fusion.

[0015] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described control method for multi-site converters of new energy based on adaptive fusion of grid and network architecture.

[0016] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described new energy multi-station converter control method based on adaptive fusion of grid and network architecture.

[0017] According to the specific embodiments provided in this application, this application has the following technical effects:

[0018] This application provides a control method, system, device, medium, and product for a new energy multi-station converter based on adaptive fusion of grid connection and grid construction. It adjusts the grid connection coefficient and grid construction coefficient according to the multiple renewable energystations short circuit ratio (MRSCR), thereby adjusting the output ratio of grid connection control and grid construction control of the converter. This achieves adaptive fusion of grid connection and grid construction control. By controlling the converter through fusion control, the impedance characteristics of the converter can be adaptively adjusted, thereby improving the stability of the converter under strong and weak grid oscillations. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating a new energy multi-station converter control method based on adaptive fusion of grid connection and network structure, provided as an embodiment of this application;

[0021] Figure 2 This is a schematic diagram of GFL-GFM hybrid synchronous control;

[0022] Figure 3 A simplified equivalent model diagram of an AC system connected to multiple new energy power plants;

[0023] Figure 4 A schematic diagram illustrating the specific adjustment rules for the network connection coefficient and the network structure coefficient;

[0024] Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] The most fundamental difference between GFL control and GFM control lies in their synchronization methods. GFL control utilizes a PLL to track the phase θ of the grid-connected voltage. PLLSynchronization is achieved by relying on an external AC power grid; GFM control utilizes the PSC stage to generate a virtual internal potential phase θ. PSC Synchronization is achieved automatically through the control loop. If both synchronization methods are used simultaneously, the converter may possess characteristics of both GFL and GFM.

[0027] Figure 2 This is a schematic diagram of GFL-GFM hybrid synchronous control. Figure 2 In the middle, v abc To track the three-phase voltage at the grid connection point in the PLL circuit, the converter output current dq-axis component reference value v is obtained through Park transformation. q The control voltage reference value is obtained through a phase-locked loop (PLL), and its output phase angle Δω PLL After the inverse Park transform, Δθ PLL . Figure 2 middle and These refer to proportional gain and integral gain, respectively. The control voltage is generated proportionally based on the instantaneous value of the current error; the larger the voltage, the faster the current tracking response. The integral of the current error is compensated to eliminate the steady-state error; the larger the integral, the faster the steady-state error converges to zero. In the PSC circuit, P... ref For the PSC link to track the active power of the grid-connected point, D p is the damping coefficient.

[0028] Δθ PLL Dynamic characteristics are easily affected by the external AC power grid. Under weak grid conditions, even slight disturbances in the grid will cause Δθ to increase. PLL Significant fluctuations occur; however, under strong power grid conditions, Δθ PLL It is less affected by power grid disturbances. Therefore, Δθ PLL It exhibits good dynamic characteristics in strong power grids, but is prone to oscillation and instability in weak power grids.

[0029] The PSC process generates Δθ automatically based on control. PSC Therefore, the GFM converter exhibits voltage source characteristics. Under strong grid conditions, the interconnection impedance between the grid and the converter in the PSC stage is relatively small, Δθ PSC It is susceptible to disturbances on the power grid side. Under weak power grid conditions, there is a large interconnection impedance between the two voltage sources, Δθ PSC It is less affected by power grid disturbances. In general, Δθ PSC It exhibits good dynamic characteristics in weak power grids, but is prone to oscillation and instability in strong power grids.

[0030] If Δθ can be used selectively PLL and Δθ PSCGiven its dynamic characteristics, the converter may combine the advantages of GFL control and GFM control while avoiding their disadvantages. (Grid coefficient k) PLL Network coefficient k PSC The phase θ of the virtual internal potential is determined by Δθ. PLL , Δθ PSC The proportion of GFL and GFM characteristics in the converter's external characteristics determines the proportion of GFL and GFM characteristics. To combine the advantages of both GFL and GFM control, the control method described in this application can adaptively adjust the tracking and grid connection coefficients based on short-circuit conditions at multiple new energy power plants, thereby achieving Δθ PLL , Δθ PSC Selective fusion of dynamic characteristics.

[0031] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0032] In one exemplary embodiment, such as Figure 1 As shown, a new energy multi-site converter control method based on grid-network adaptive fusion is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is described using a server as an example, including the following steps S1 to S3. Wherein:

[0033] S1: Calculate the short-circuit ratio of multiple renewable energy power plants. Specifically, this includes: simplifying the AC system connected to multiple renewable energy power plants to obtain an equivalent model; and calculating the short-circuit ratio of multiple renewable energy power plants based on the parameters in the equivalent model.

[0034] Thevenin equivalent method can simplify an AC system connected to multiple new energy power plants into a single ideal voltage source in series with equivalent impedance. Using the multi-port Thevenin equivalent method, we can obtain... Figure 3 The diagram shows a simplified equivalent model of n new energy power stations simultaneously connected to an AC system.

[0035] Figure 3 middle, P REi Q REi and These are the apparent power, active power, reactive power, and grid-connected bus voltage of the new energy power station i. The equivalent impedance between the grid connection points of new energy power station i and new energy power station j is calculated. The equivalent impedance on the system side between the main grid equivalent power source n and the corresponding grid connection point is calculated.

[0036] The short-circuit ratio (MSR) of multiple renewable energy power plants is used to measure the relative magnitude between the nominal voltage of the AC system and the voltage generated by the renewable energy power plants after multiple renewable energy power plants are connected to the AC system. Based on the above physical meaning, the MRSCR of the grid-connected bus node of the i-th renewable energy power plant in the AC system is:

[0037]

[0038] Where: MRSCR i Let be the short-circuit ratio of the i-th renewable energy power station's grid-connected bus node. Let be the nominal voltage of the grid-connected bus node of the i-th renewable energy power station. Let be the voltage generated at the grid-connected bus node by the power generation of the i-th renewable energy power station. Let n be the equivalent impedance between the grid-connected bus node of the i-th renewable energy power station and the grid-connected bus node of the j-th renewable energy power station, where n is the number of renewable energy power stations in the multi-power station network. The short-circuit current provided for the renewable energy power plant. Let the actual operating voltage of the i-th grid-connected bus node be... Multiply both the numerator and denominator in the above equation by... We can obtain:

[0039]

[0040] In the formula: The actual apparent power of new energy injected into the grid-connected bus node of the i-th new energy power station; It is the complex power conversion factor between the grid-connected bus node of the i-th renewable energy power station and the grid-connected bus node of the j-th renewable energy power station, reflecting the phase and amplitude differences between the electrical quantities at the grid-side access point / grid-connection point of each renewable energy power station.

[0041] S2: Adaptively fuse the grid-following control and grid-building control based on the short-circuit ratio of the new energy multi-station system to obtain fused control. Specifically, this includes: adjusting the grid-following coefficient of the grid-following control and the grid-building coefficient of the grid-building control based on the short-circuit ratio of the new energy multi-station system; the grid-following coefficient and the grid-building coefficient are added together to equal 1. Adaptively fuse the grid-following control and the grid-building control based on the adjusted grid-following coefficient and the grid-building coefficient.

[0042] The key to adaptive fusion control is how to establish the relationship between the external grid strength and the characteristics of GFL and GFM control, that is, how to adjust the Δθ in the virtual internal potential phase θ according to MRSCR. PLL or Δθ PSC The proportion. From Δθ PLL With Δθ PSC Dynamic characteristics show that under strong power grid conditions, Δθ PLL The dynamic characteristics are good, and in this case, θ should mainly come from Δθ. PLL; Under weak grid conditions, Δθ PSC has good dynamic characteristics, and at this time, θ should mainly depend on Δθ PSC . The specific adjustment rules of the grid-following coefficient k PLL and the grid-forming coefficient k PSC are as follows Figure 4 shown:

[0043] (1) When the short-circuit ratio of the new energy multi-station is less than or equal to the first threshold, reduce the grid-following coefficient and increase the grid-forming coefficient. As Figure 4 shown, in this embodiment, the first threshold is 3. When MRSCR ≤ 3, k PSC > k PLL , and the GFM control characteristic dominates; as MRSCR decreases, k PSC gradually increases, and the GFM characteristic gradually strengthens. Therefore, when MRSCR ≤ 3, reduce the grid-following coefficient k PLL and increase the grid-forming coefficient k PSC .

[0044] (2) When the short-circuit ratio of the new energy multi-station is greater than the first threshold and less than the second threshold, do not adjust the grid-following coefficient k PLL and the grid-forming coefficient k PSC . As Figure 4 shown, in this embodiment, the second threshold is 10. When 3 < MRSCR < 10, GFL control and GFM control within a relatively wide range (40% - 60%) are sufficient to ensure that the converter does not oscillate and become unstable. To avoid frequent and unnecessary adjustment of the grid-following / forming coefficients, the adaptive adjustment rule introduces a hysteresis link in this interval.

[0045] (3) When the short-circuit ratio of the new energy multi-station is greater than or equal to the second threshold, increase the grid-following coefficient k PLL and reduce the grid-forming coefficient k PSC . As Figure 4 [[ID=​​​​​​​​​​​

[0048] The above-mentioned new energy multi-station converter control method based on grid-network adaptive fusion provided in this application has the following advantages:

[0049] (1) The adaptive fusion control in this application enables a single converter to have both grid connection and grid construction characteristics, and can also adaptively adjust the output ratio of grid connection and grid construction control of the converter according to the grid strength of multiple stations.

[0050] (2) The MRSCR used in this application takes into account the amplitude and phase difference of each electrical quantity between different nodes, and can also take into account the impact of reactive power of new energy power plants. It is applicable to the voltage intensity assessment calculation of multiple new energy power plants connected to AC systems in various scenarios.

[0051] (3) In the adaptive fusion control in this application, the enhancement of the grid control helps to reduce the negative resistance effect, and the enhancement of the grid control can increase the impedance amplitude. Therefore, the adaptive fusion control can adaptively adjust the converter impedance characteristics according to the grid strength of multiple stations, thereby improving the stability of the converter in strong and weak grid oscillations.

[0052] (4) The adaptive fusion control converter of this application does not have the risk of oscillation instability in the range of 1≤MRSCR≤50, and its stable operation capability under strong and weak grid oscillations is better than that of simple grid-following control and grid-building control.

[0053] Based on the same inventive concept, this application also provides a new energy multi-station converter control system based on grid-connection and grid-structure adaptive fusion. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the new energy multi-station converter control system based on grid-connection and grid-structure adaptive fusion provided below can be found in the limitations of the new energy multi-station converter control method based on grid-connection and grid-structure adaptive fusion described above, and will not be repeated here.

[0054] In one exemplary embodiment, a new energy multi-station converter control system based on grid-connection adaptive fusion is provided, comprising:

[0055] The calculation unit is used to calculate the short-circuit ratio of multiple new energy power stations.

[0056] The fusion unit is used to adaptively fuse the grid control and grid construction control based on the short-circuit comparison of the new energy multi-sites to obtain fused control.

[0057] The control unit is used to control the converters of multiple new energy power plants based on fusion control.

[0058] In one exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments. The computer device may be a server or a terminal, and its internal structure diagram may be as follows: Figure 5 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores data to be processed. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a new energy multi-site converter control method based on adaptive fusion of grid-connection and network architecture.

[0059] Those skilled in the art will understand that Figure 5 The structures shown are merely block diagrams of some structures related to the present application and do not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0060] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0061] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0062] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0063] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0064] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0065] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0066] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A control method for converters in multiple new energy power plants based on adaptive fusion of grid connection and network construction, characterized in that, include: Calculate the short-circuit ratio of multiple new energy power stations; Based on the short-circuit comparison of the new energy multi-station grid-following control and grid-building control, adaptive fusion is performed to obtain fused control; This system controls the converters at multiple new energy power plants based on integrated control.

2. The control method for converters of multiple new energy power plants based on adaptive fusion of grid connection and network structure as described in claim 1, specifically includes calculating the short-circuit ratio of multiple new energy power plants: The AC system connected to multiple new energy power stations is simplified to obtain an equivalent model; The short-circuit ratio of multiple new energy power stations is calculated based on the parameters in the equivalent model.

3. The new energy multi-station converter control method based on grid-network adaptive fusion according to claim 2, characterized in that, The AC system connected to multiple new energy power plants is simplified to obtain an equivalent model, which specifically includes: The Thevenin equivalent method is used to simplify the AC system connected to multiple new energy power stations, resulting in an equivalent model.

4. The new energy multi-station converter control method based on grid-network adaptive fusion according to claim 1, characterized in that, The formula for calculating the short-circuit ratio of multiple new energy power stations is as follows: Among them, MRSCR i Let be the short-circuit ratio of the i-th renewable energy power station's grid-connected bus node. Let be the actual operating voltage of the i-th renewable energy power station's grid-connected bus node. Let be the nominal voltage of the grid-connected bus node of the i-th renewable energy power station. Let n be the equivalent impedance between the grid-connected bus node of the i-th renewable energy power station and the grid-connected bus node of the j-th renewable energy power station, where n is the number of renewable energy power stations in the multi-power station network. These represent the actual apparent power of new energy injected into the grid-connected bus nodes of the i-th and j-th new energy power plants, respectively. It is the complex power conversion factor between the grid-connected bus node of the i-th renewable energy power station and the grid-connected bus node of the j-th renewable energy power station.

5. The new energy multi-station converter control method based on grid-network adaptive fusion according to claim 1, characterized in that, Based on the short-circuit comparison of the new energy multi-station grid-connected control and grid-building control, adaptive fusion is performed to obtain fused control, which specifically includes: The grid-following coefficient and the grid-building coefficient of the grid-building control are based on the short-circuit ratio adjustment of the new energy multi-station grid; the grid-following coefficient and the grid-building coefficient are added together to get 1. Adaptive fusion of network following control and network construction control is performed based on the adjusted network following coefficient and network construction coefficient.

6. The new energy multi-station converter control method based on grid-network adaptive fusion according to claim 5, characterized in that, The grid-following coefficient and grid-building coefficient of the grid-connecting control based on the short-circuit ratio adjustment of the new energy multi-stations specifically include: When the short-circuit ratio of the new energy multi-station is less than or equal to the first threshold, the grid connection coefficient is reduced and the grid construction coefficient is increased. When the short-circuit ratio of the new energy multi-station is greater than the first threshold and less than the second threshold, the grid connection coefficient and grid construction coefficient are not adjusted. When the short-circuit ratio of the new energy multi-station is greater than or equal to the second threshold, the grid connection coefficient is increased and the grid construction coefficient is decreased.

7. A new energy multi-station converter control system based on grid-network adaptive fusion, characterized in that, include: The calculation unit is used to calculate the short-circuit ratio of multiple new energy power stations; The fusion unit is used to adaptively fuse the grid-following control and grid-building control based on the short-circuit comparison of the new energy multi-sites to obtain fused control; The control unit is used to control the converters of multiple new energy power plants based on fusion control.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the new energy multi-station converter control method based on grid-network adaptive fusion as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the new energy multi-station converter control method based on adaptive fusion of grid-network integration as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the new energy multi-station converter control method based on adaptive fusion of grid-network integration as described in any one of claims 1-6.

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