Digital simulation platform and method for multi-working-condition test of constructed network type energy storage

Abstract

The invention provides a digital simulation platform and method for a multi-working-condition test of network-building type energy storage. The platform comprises an upper computer and a real-time simulation machine, the upper computer is connected with the real-time simulation machine; the real-time simulation machine comprises a CPU module and an FPGA module. The CPU module operates a power grid model and a virtual synchronous machine control algorithm; the FPGA module operates a switching device model; the CPU module sends a control signal to the FPGA module, and the FPGA module feeds back a switch state to the CPU module. High and low frequency decoupling calculation, low frequency modules such as a CPU processing power grid model and a control algorithm, and high frequency characteristics such as an FPGA special switch device model are realized through a CPU-FPGA heterogeneous architecture, and accurate coupling of multiple time scales is realized while the real-time performance of 10kHz switching frequency simulation is ensured.

Description

Technical Field

[0001] This application belongs to the field of power grid transient control, and particularly relates to a digital simulation platform and method for multi-condition testing of a network-forming energy storage system. Background Art

[0002] As a key means to improve the flexibility of the power grid, existing digital simulation technologies mostly use a single computing unit, making it difficult to balance the co-simulation of the high-frequency characteristics of power electronic devices and the low-frequency dynamics of the system level. This results in insufficient simulation accuracy and real-time performance, and cannot effectively support the rapid iterative verification of control strategies in multi-machine parallel scenarios. Summary of the Invention

[0003] The purpose of this application is to overcome the above-mentioned defects in the existing technologies and provide a digital simulation platform and method for multi-condition testing of a network-forming energy storage system.

[0004] This application provides a digital simulation platform for multi-condition testing of a network-forming energy storage system, including: a host computer and a real-time simulator;

[0005] The host computer is connected to the real-time simulator;

[0006] The real-time simulator includes a CPU module and an FPGA module; the CPU module runs the power grid model and the virtual synchronous machine control algorithm; the FPGA module runs the switch device model;

[0007] The CPU module sends control signals to the FPGA module, and the FPGA module feeds back the switch status to the CPU module.

[0008] Optionally, the power grid model includes a filter and a connection line mathematical model, and its mathematical expression is:

[0009]

[0010] Where, u d 、u q are the d / q components of the converter output voltage, u od 、u oq are the d / q components of the filter capacitor voltage, u gd 、u gq are the d / q components of the AC power grid voltage, i d 、i q are the d / q components of the converter output current, i od 、i oq are the d / q components of the line inductor current, L f is the filter inductor, C f is the filter capacitor, R c 、L care the equivalent inductance and resistance of the line.

[0011] Optionally, the virtual synchronous machine control algorithm includes a power calculation module, and its output power expression is:

[0012]

[0013] where P and Q are the output active power and reactive power respectively, u od and u oq are the d / q components of the filter capacitor voltage, i od and i oq are the d / q components of the line inductor current, and 1.5 is the three-phase system coefficient.

[0014] Optionally, the virtual synchronous machine control algorithm includes a virtual synchronous machine excitation control structure, and its expression is:

[0015]

[0016] where the moment of inertia J = 2 kg·m 2 ±20%, the damping coefficient D = 90 N·m·s / rad ± 15%, ω n is the rated angular frequency, ω is the actual angular frequency, P is the real-time active power, P ref is the active reference value, K d is the frequency droop coefficient, u ref is the voltage reference value, K q is the voltage droop coefficient, Q is the real-time reactive power, Q ref is the reactive reference value.

[0017] Optionally, it also includes a voltage-current double closed-loop control model, and its expression is:

[0018]

[0019] where i ud and i uq are the output current reference values of the voltage outer loop respectively, u d and u q are the voltage commands output by the current inner loop respectively, K pv and K iv are the voltage outer loop proportional / integral coefficients respectively, K pc and K ic are the current inner loop proportional / integral coefficients respectively, x ud and x uq are the integral state variables of the voltage loop respectively, x id and x iq are the integral state variables of the current loop respectively, ω n is the rated angular frequency.

[0020] Optionally, the platform includes a multi-machine parallel system simulation module, which includes at least two grid-connected energy storage converters connected in parallel to the power grid.

[0021] This application also provides a digital simulation method for multi-operating condition testing of grid-type energy storage, including:

[0022] Establish the communication connection between the host computer and the real-time simulator, and configure the interactive interface between the CPU module of the real-time simulator and the FPG A module;

[0023] Running a power grid model and a virtual synchronous machine control algorithm in the CPU module, wherein the power grid model includes equation descriptions of filters and connecting lines;

[0024] running a switch device model in the FPGA module;

[0025] Sending a PWM control signal to the FPGA module via the CPU module;

[0026] The real-time status data of the switching device is fed back to the CPU module via the FPGA module.

[0027] Optionally, the power grid model includes: a filter inductor current equation, a filter capacitor voltage equation, and a line current dynamic equation.

[0028] Optionally, the virtual synchronous machine control includes: inertia-damping control and voltage droop control.

[0029] Optionally, it also includes a multi-machine parallel test: configuring at least two energy storage converters in parallel.

[0030] The beneficial effects of this application are:

[0031] The present application provides a digital simulation platform for multi-operating condition testing of grid-type energy storage, comprising: a host computer and a real-time simulator; the host computer is connected to the real-time simulator; the real-time simulator comprises a CPU module and an FPGA module; the CPU module runs a power grid model and a virtual synchronous machine control algorithm; the FPGA module runs a switching device model; the CPU module sends a control signal to the FPGA module, and the FPGA module feeds back the switching state to the CPU module. The present application implements high- and low-frequency decoupling calculations through a CPU-FPGA heterogeneous architecture. The CPU processes low-frequency modules such as the power grid model and control algorithm, while the FPGA specializes in high-frequency characteristics such as the switching device model. This ensures the real-time performance of the 10kHz switching frequency simulation while achieving precise coupling on multiple time scales. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a schematic diagram of the digital simulation platform for multi-operating condition testing of grid-type energy storage in this application;

[0033] Figure 2 It is a schematic diagram of the topology structure of the network-forming energy storage converter in this application;

[0034] Figure 3 It is a schematic diagram of the multi-machine parallel system of the network-forming energy storage converter in this application;

[0035] Figure 4 It is a schematic diagram of the active and reactive power fluctuations of the single-machine system under the condition of verifying voltage change in this application;

[0036] Figure 5 It is a schematic diagram of the frequency change of the single-machine system under the condition of verifying voltage change in this application;

[0037] Figure 6 It is a schematic diagram of the grid-connected voltage and current of the single-machine system under the condition of verifying voltage change in this application;

[0038] Figure 7 It is a schematic diagram of the active and reactive power fluctuations of the single-machine system under the condition of verifying frequency increase in this application;

[0039] Figure 8 It is a schematic diagram of the frequency change of the single-machine system under the condition of verifying frequency increase in this application;

[0040] Figure 9 It is a schematic diagram of the grid-connected voltage and grid-side voltage of the single-machine system under the condition of verifying frequency increase in this application;

[0041] Figure 10 It is a schematic diagram of the active and reactive power fluctuations of the single-machine system under the condition of verifying frequency decrease in this application;

[0042] Figure 11 It is a schematic diagram of the frequency change of the single-machine system under the condition of verifying frequency decrease in this application;

[0043] Figure 12 It is a schematic diagram of the grid-connected voltage and grid-side voltage of the single-machine system under the condition of verifying frequency decrease in this application;

[0044] Figure 13 It is a schematic diagram of the reactive power fluctuations of the multi-machine system under the condition of verifying voltage change in this application;

[0045] Figure 14 It is a schematic diagram of the grid connection point voltage fluctuations of the multi-machine system under the condition of verifying voltage change in this application;

[0046] Figure 15 It is a schematic diagram of the frequency change of the multi-machine system under the condition of verifying voltage change in this application;

[0047] Figure 16 It is a schematic diagram of the frequency change of the multi-machine system under the condition of verifying frequency change in this application;

[0048] Figure 17 It is a schematic diagram showing the active power change of a multi-machine system under the condition of verifying frequency change in this application. Detailed implementation manners

[0049] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it can be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, the embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0050] Please refer to Figure 1 as shown in Figure 1 which shows the structure of a digital simulation platform for multi-condition testing of a grid-forming energy storage.

[0051] This application provides a digital simulation platform for multi-condition testing of a grid-forming energy storage, including: a host computer 101 and a real-time simulator 102 based on RT-LAB. The host computer 101 is connected to the real-time simulator 102.

[0052] The host computer 101 is used for writing control strategies, setting parameters, and displaying results.

[0053] In the host computer 101, the human-machine real-time interaction interface is designed with a graphical user interface, which is simple and intuitive to operate. Users can perform operations such as model selection, parameter adjustment, condition setting, waveform observation, and result viewing through the SM and SC interfaces, realizing convenient interaction with the platform, and conducting in-depth analysis and visual display of the simulation results to verify the correctness and effectiveness of the corresponding grid-forming energy storage control algorithm.

[0054] The real-time simulator 102 includes a CPU module 1021 and an FPGA module 1022; the CPU module 1021 runs the power grid model and the virtual synchronous machine control algorithm; the FPGA module 1022 runs the switch device model; the CPU module 1021 sends control signals to the FPGA module 1022, and the FPGA module 1022 feeds back the switch state to the CPU module 1021.

[0055] Specifically, the real-time simulator 102 uses the CPU to simulate an external controller to generate PWM waves, and the real-time simulator 102 uses the FPGA to simulate actual power electronic switch devices to achieve joint simulation of the CPU and the FPGA. Among them, the CPU calculates the low-frequency part, and the FPGA calculates the high-frequency part.

[0056] Achieve high-low frequency decoupled computing through a CPU-FPGA heterogeneous architecture. The CPU processes low-frequency modules such as power grid models and control algorithms, while the FPGA specializes in high-frequency characteristics such as switch device models. While ensuring the real-time performance of switch frequency simulation, achieve precise coupling of multiple time scales.

[0057] Furthermore, the digital simulation platform for multi-condition testing of the network-forming energy storage also includes a data acquisition and communication module, which is responsible for realizing data interaction between the real-time simulator 102 and the host computer 101.

[0058] In the real-time simulator 102, a typical network-forming energy storage system topology is built using a virtual synchronous machine control strategy.

[0059] Please refer to Figure 2 as shown in Figure 2 which shows the topology of the network-forming energy storage converter in this application.

[0060] As Figure 2 shown, u dc is the ideal DC voltage on the DC side, the inductor L f and the capacitor C f connected in star form form a filtering link on the converter bridge arm side to suppress harmonic components in the output voltage and current of the converter. R c and L c are the equivalent resistance and inductance of the connecting line. i a , i b , i c are the output currents of the converter. i oa , i ob , i oc are the currents in the line inductor L c . u oa , u ob , u oc are the voltages of the filter capacitors. u ga , u gb , u gc are the AC grid voltages.

[0061] Based on the topology of the network-forming energy storage converter, select the dq coordinate system of the network-forming energy storage as the reference synchronous rotating coordinate system, and model the filter circuit, connecting line, power calculation, network-forming energy storage control algorithm, and voltage-current double closed-loop respectively.

[0062] Establish the mathematical models of the filter and the connecting line as follows:

[0063]

[0064] Among them, u d , u qare the d / q components of the converter output voltage, u od , u oq are the d / q components of the filter capacitor voltage, u gd , u gq are the d / q components of the AC grid voltage, i d , i q are the d / q components of the converter output current, i od , i oq are the d / q components of the line inductor current, L f is the filter inductor, C f is the filter capacitor, R c , L c are the line equivalent inductor and resistance.

[0065] Furthermore, by collecting the filter output voltage and current, the output power of the grid-forming energy storage can be obtained through instantaneous power calculation as:

[0066]

[0067] where P and Q are the output active power and reactive power respectively, u od , u oq are the d / q components of the filter capacitor voltage, i od , i oq are the d / q components of the line inductor current, and 1.5 is the three-phase system coefficient.

[0068] Furthermore, according to the power and excitation control structure, the control algorithm of the grid-forming energy storage can be obtained as:

[0069]

[0070] where the moment of inertia is J, the damping coefficient is D, ω n is the rated angular frequency, ω is the actual angular frequency, P is the real-time active power, P ref is the active power reference value, K d is the frequency droop coefficient, u ref is the voltage reference value, K q is the voltage droop coefficient, Q is the real-time reactive power, Q ref is the reactive power reference value.

[0071] Define K pv and K iv as the voltage outer loop proportional and integral coefficients respectively, K pc and K ic as the current inner loop proportional and integral coefficients respectively, and establish the voltage outer loop and current inner loop control models as:

[0072]

[0073] Among them, i ud 、i uq They are the reference values of the voltage outer loop output current, u d 、u q They are the current inner loop output voltage command, K pv , K iv They are the voltage outer loop proportional / integral coefficient, K pc , K ic They are the current inner loop proportional / integral coefficients, x ud 、x uq are the voltage loop integral state variables, x id 、x iq are the current loop integral state variables, ω n is the rated angular frequency.

[0074] Define x ud 、x uq and x id 、x iq The intermediate state variables of the voltage and current double closed loops are defined respectively to describe the dynamic characteristics of the PI controller in the voltage outer loop and the current inner loop. The corresponding state equations are as follows:

[0075]

[0076] Please refer to Figure 3 As shown, Figure 3 The multi-machine parallel system of the grid-type energy storage converter in this application is demonstrated.

[0077] To enable parallel simulation testing of multiple energy storage converters, a typical operating scenario for a multi-machine parallel energy storage system was constructed. By integrating and solving these models, dynamic simulation of a grid-connected energy storage system under different operating conditions can be achieved.

[0078] Traditional centralized modeling approaches treat multi-machine systems as a single, integrated model, failing to accurately describe the dynamic coupling characteristics between energy storage units. For example, when multiple converters are connected in parallel, differences in line impedance can lead to uneven power distribution, a detail often overlooked by existing simulation platforms.

[0079] In this application, an independent electromagnetic transient model is built for each converter, and the coupling between the converters is accurately characterized using a line model. Parallel computation of nanosecond-level switching devices is implemented in an FPGA to capture transient current interactions when multiple converters are connected in parallel.

[0080] Furthermore, an adaptive virtual impedance algorithm is introduced to adjust K in real time in the CPU. pv , K iv , K pc , K icThe voltage-current dual closed-loop model of formula (4) realizes the dynamic decoupling of multi-machine power-frequency; through hardware-in-the-loop collaborative optimization, the multi-machine control parameter tuning can be completed within 30ms.

[0081] Furthermore, the CPU is responsible for the coordinated control of multiple machines in the low-frequency domain, while the FPGA specializes in high-frequency switching behavior, significantly improving computing efficiency. When the number of parallel machines is expanded from a single machine to multiple machines, the FPGA automatically allocates logic unit clusters to ensure that the simulation delay remains below 50μs when multiple machines are connected in parallel, meeting the 10kHz switching frequency requirement.

[0082] Based on the typical topological structure of the energy storage system and the construction and operation scenarios, the power grid model, energy storage system model and control strategy model are constructed based on power system analysis theory and numerical calculation methods.

[0083] Specific applications:

[0084] Build the following in Matlab / Simulink simulation software Figure 2 The topology of the energy storage controller is shown in Table 1.

[0085] At the same time, construct Figure 3 The energy storage multi-machine parallel system shown.

[0086] The energy storage system was simulated and verified under different grid voltage and frequency disturbances using a digital simulation platform based on RT-LAB. The test simulation platform interface is as follows: Figure 1 shown.

[0087] Table 1 Main parameters of energy storage control system

[0088]

[0089] Simulation condition 1: Verification of voltage support characteristics of a single-machine energy storage converter.

[0090] The voltage support of a single machine is set to high and low wear conditions as follows: the system voltage drops by 0.3 pu at 6 seconds and recovers to 1 pu at 12 seconds; the voltage rises by 0.3 pu at 18 seconds and returns to normal value at 24 seconds.

[0091] Use the simulation platform to record the module and export the changes in 30 seconds, such as Figures 4 to 6 shown.

[0092] Simulation condition 2: Verification of frequency support characteristics of a single-machine energy storage converter.

[0093] The frequency support setting conditions for a single machine are as follows: in the frequency rising condition, the system frequency rises by 0.2 Hz in 6 seconds and recovers to 50 Hz in 12 seconds; in the frequency falling condition, the frequency drops by 0.2 Hz in 6 seconds and recovers to 50 Hz in 12 seconds.

[0094] Use the recording module of the simulation platform to export the change conditions of the frequency rising for 30 s and the frequency falling for 25 s respectively, as Figures 7 to 12 shown.

[0095] Simulation condition 3: Verification of the voltage support characteristics of the multi-machine parallel energy storage system.

[0096] The high and low voltage ride-through conditions for the multi-machine voltage support are set as follows: At 10 s, the voltage of the system drops by 0.3 pu and recovers to 1 pu at 16 s; at 22 s, the voltage rises by 0.3 pu and returns to the normal value at 28 s.

[0097] Use the recording module of the simulation platform to export the change conditions for 30 s, as Figures 13 to 15 shown.

[0098] Simulation condition 4: Verification of the frequency support characteristics of the multi-machine parallel energy storage system.

[0099] The conditions for the multi-machine frequency support are set as follows: For the frequency falling condition, the frequency of the system drops by 0.2 Hz at 6 s and recovers to 50 Hz at 12 s.

[0100] Use the recording module of the simulation platform to export the change conditions of the frequency dropping by 0.2 Hz for 30 s, as Figures 16 to 17 shown.

[0101] Referring to Figures 4 to 17 It can be found that the multi-condition test digital simulation platform proposed in this application for the network-forming energy storage can achieve the expected functions and effects, can complete the simulation verification of the single-machine and multi-machine energy storage systems under different conditions, and further uses the visualization interface of the data results to demonstrate the rationality and accuracy of the control algorithm. The platform has good scalability and computational efficiency, can meet the simulation requirements of the new power system, and provides an efficient and reliable tool for the research and application of the network-forming energy storage system.

[0102] This application also provides a digital simulation method for the multi-condition test of the network-forming energy storage, including:[[]]

[0103] Establish a communication connection between the host computer 101 and the real-time simulator 102, and configure the interaction interface between the CPU module 1021 and the FPGA module 1022 of the real-time simulator 102;

[0104] Run the power grid model and the virtual synchronous machine control algorithm in the CPU module 1021, and the power grid model includes the equation descriptions of the filter and the connecting line;

[0105] Run the switch device model in the FPGA module 1022;

[0106] Send the PWM control signal from the CPU module 1021 to the FPGA module 1022;

[0107] Feedback the real-time status data of the switching device to the CPU module 1021 through the FPGA module 1022.

[0108] Furthermore, the power grid model includes: filter inductor current equation, filter capacitor voltage equation, and line current dynamic equation.

[0109] Furthermore, the virtual synchronous machine control includes: inertia-damping control and voltage droop control.

[0110] Furthermore, it also includes multi-machine parallel test: configure at least two energy storage converters in parallel.

[0111] The above description of the embodiments is for the convenience of those of ordinary skill in the art to understand and apply the present invention. It is obvious that those skilled in the art can easily make various modifications to the above embodiments and apply the general principles described herein to other embodiments without creative efforts. Therefore, the present invention is not limited to the above embodiments, and all improvements and modifications made by those skilled in the art based on the disclosure of the present invention should be within the protection scope of the present invention.

Claims

1. A digital simulation platform for multi-condition testing of network-forming energy storage, characterized in that Including: A host computer and a real-time simulator; The host computer is connected to the real-time simulator; The real-time simulator includes a CPU module and an FPGA module; The CPU module runs a power grid model and a virtual synchronous machine control algorithm; the FPGA module runs a switch device model; The CPU module sends a control signal to the FPGA module, and the FPGA module feeds back the switch state to the CPU module.

2. The digital simulation platform for multi-condition testing of network-forming energy storage according to claim 1, characterized in that The power grid model includes a filter and a connection line mathematical model, and its mathematical expression is: where, u d and u q are the d / q components of the converter output voltage, u od and u oq are the d / q components of the filter capacitor voltage, u gd and u gq are the d / q components of the AC grid voltage, i d and i q are the d / q components of the converter output current, i od and i oq are the d / q components of the line inductor current, L f is the filter inductor, C f is the filter capacitor, R c and L c are the line equivalent inductor and resistance.

3. The digital simulation platform for multi-condition testing of a network-forming energy storage according to claim 2, wherein, The virtual synchronous machine control algorithm includes a power calculation module, and its output power expression is: where P and Q are the active power and reactive power output respectively, and u od and u oq are the d / q components of the filter capacitor voltage, i od and i oq are the d / q components of the line inductor current, and 1.5 is the three-phase system coefficient.

4. The digital simulation platform for multi-condition testing of a network-forming energy storage according to claim 3, characterized in that, The virtual synchronous machine control algorithm includes a virtual synchronous machine excitation control structure, and its expression is: Among them, the moment of inertia J = 2 kg·m 2 ±20%, the damping coefficient D = 90 N·m·s / rad ± 15%, ω n is the rated angular frequency, ω is the actual angular frequency, P is the real-time active power, P ref is the active power reference value, K d is the frequency droop coefficient, u ref is the voltage reference value, K q is the voltage droop coefficient, Q is the real-time reactive power, Q ref is the reactive power reference value.

5. The digital simulation platform for multi-condition testing of network-forming energy storage according to claim 4, characterized in that It also includes a voltage-current double closed-loop control model, and its expression is: Among them, i ud and i uq are respectively the reference values of the output current of the outer voltage loop, u d and u q are respectively the voltage commands of the output of the inner current loop, K pv and K iv are respectively the proportional / integral coefficients of the outer voltage loop, K pc and K ic are respectively the proportional / integral coefficients of the inner current loop, x ud and x uq are respectively the integral state variables of the voltage loop, x id and x iq are respectively the integral state variables of the current loop, ω n is the rated angular frequency.

6. The digital simulation platform for multi-condition testing of a network-constructing energy storage according to claim 1, characterized in that, The platform includes a multi-machine parallel system simulation module, including at least two grid-forming energy storage converters connected in parallel to the power grid.

7. A digital simulation method for multi-condition testing of network-forming energy storage, characterized in that, Including: Establish a communication connection between the host computer and the real-time simulator, and configure the interaction interface between the CPU module and the FPGA module of the real-time simulator; Run a power grid model and a virtual synchronous machine control algorithm in the CPU module, and the power grid model includes equation descriptions of a filter and a connection line; Run a switch device model in the FPGA module; Send a PWM control signal from the CPU module to the FPGA module; Feed back the real-time state data of the switch device from the FPGA module to the CPU module.

8. The digital simulation method for multi-condition testing of a network-forming energy storage according to claim 7, characterized in that The power grid model includes: a filter inductor current equation, a filter capacitor voltage equation, and a line current dynamic equation.

9. The digital simulation method for multi-condition testing of a network-forming energy storage according to claim 7, characterized in that, The virtual synchronous machine control includes: inertia-damping control and voltage droop control.

10. A digital simulation method for multi-condition testing of a network-constructing energy storage according to claim 7, characterized in that, It also includes a multi-machine parallel test: configure at least two energy storage converters in parallel.

Images