Common-bus photovoltaic energy storage AC micro-grid simulation model construction method

Abstract

The invention discloses a common-bus photovoltaic energy storage AC micro-grid simulation model construction method, and the method comprises the steps: constructing a micro-grid system architecture through cooperation of four core modules, and defining a simulation target; according to the micro-grid system architecture, performing digital modeling on each functional module of the micro-grid, and constructing a simulation model; setting an initial parameter of the simulation model and a simulation scene for multi-experiment comparison; the simulation model is optimized according to the multi-experiment contrast result, the step S300 is repeated for the optimized simulation model, and a final micro-grid simulation model with qualified accuracy is obtained. And realizing accurate grid-connected synchronization through a PLL phase-locked loop according to the micro-grid simulation model. The model solves the problems of photovoltaic output fluctuation, bus voltage instability, inverter harmonic pollution and the like, is high in simulation precision and fast in dynamic response, can accurately simulate system operation characteristics under complex working conditions, provides reliable support for engineering design, parameter optimization and stability verification of a common-bus photovoltaic energy storage micro-grid, and has a wide application prospect. The method is suitable for distributed photovoltaic power stations and other scenes.

Description

Technical Field

[0001] This invention relates to the field of microgrid simulation technology, specifically to a method for constructing a simulation model of a photovoltaic energy storage AC microgrid with a common bus. Background Technology

[0002] Against the backdrop of the "dual carbon" goals driving the global energy structure towards a cleaner and lower-carbon transformation, photovoltaic (PV) power generation has become one of the fastest-growing forms of renewable energy globally due to its renewable resources and zero-emission operation. According to data from the International Energy Agency (IEA), global new PV installations exceeded 400 GW in 2023, with a cumulative installed capacity exceeding 2 TW. It is projected that PV will account for more than 20% of global electricity supply by 2030. However, the output characteristics of PV power generation are highly dependent on natural conditions: drastic fluctuations in sunlight intensity from 200 W / m² to 1000 W / m² and changes in ambient temperature from 10°C to 30°C can cause PV array output power fluctuations of ±50%, directly leading to grid-connected voltage deviations, frequency fluctuations, and even triggering malfunctions in grid relay protection. This severely restricts the large-scale consumption of PV energy and poses a serious challenge to the safe and stable operation of the distribution network.

[0003] To address the issue of fluctuating photovoltaic (PV) output, this invention presents a common-bus PV energy storage AC microgrid. Leveraging the advantages of "centralized bus management + flexible energy storage adjustment," it has become a core technological approach for balancing PV output and improving system stability. This architecture simplifies the system topology (reducing wiring complexity by over 30%) and lowers equipment redundancy costs (by 15%-20% compared to distributed architectures) by connecting PV units, energy storage units, and inverters to the same DC bus. It has been widely applied in distributed PV power plants and microgrid energy storage systems. However, in actual operation and simulation modeling, this architecture still faces three major technological bottlenecks: low DC-DC conversion efficiency and poor bus voltage stability; weak bidirectional adjustment capability and slow dynamic response speed of the energy storage unit; and severe harmonic pollution and low grid synchronization accuracy of the grid-connected inverter, which are difficult to overcome effectively with existing technologies. Summary of the Invention

[0004] The present invention proposes a method, equipment and storage medium for constructing a simulation model of a photovoltaic energy storage AC microgrid with a common bus, which can at least solve one of the technical problems in the background art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A method for constructing a simulation model of a photovoltaic energy storage AC microgrid with a common bus, characterized by the following steps: S100. Define the microgrid system architecture and clarify the simulation objectives; S200. Based on the microgrid system architecture, digital modeling is performed on each functional module of the microgrid to construct a simulation model; S300: Set initial parameters for the simulation model and simulation scenarios to conduct multiple experimental comparisons; S400. Optimize the simulation model based on the results of multiple experiments. Repeat step S300 on the optimized simulation model to obtain the final microgrid simulation model with qualified accuracy.

[0006] Furthermore, the simulation model construction method in step S200 of the present invention includes: a method for establishing a digital model of a battery energy storage unit module, a method for establishing a digital model of a grid-connected inverter module, and a method for constructing a digital model of a photovoltaic module; The methods for establishing digital models of battery energy storage unit modules include: A DC-DC converter submodule with a BUCK-BOOST topology is constructed. The output of the topology is connected to an energy storage converter, and the input is connected to a battery to achieve dual-loop control of voltage and current. With the assistance of the BUCT-BOOST circuit, when the DC bus voltage of the energy storage is less than the threshold, the operating signal of the IGBT switching transistor is adjusted to switch to the BOOST boost circuit, and the power flows from the battery module to the DC bus.

[0007]

[0008] Where iL is the inductor current, Vin is the battery voltage, and i o For the output current, V dc R is the output voltage of the converter. L Let d be the parasitic resistance of the inductor, and d be the duty cycle of the switch Q1. Switch Q2 and switch Q1 are complementary in conduction, so the duty cycle of switch Q2 is 1-d.

[0009] Furthermore, the method for establishing a digital model of a grid-connected inverter module according to the present invention includes: A half-bridge structure is constructed by connecting a diode in parallel with an IGBT, and a three-phase full-bridge topology is constructed by connecting three sets of half-bridge structures. The DC input of the full-bridge topology is 750 / 700V, the AC output is 380V / 50Hz and the common AC bus is 380V / 50Hz, and the rated power is 1000W. The photovoltaic-side grid-connected converter adopts UI control, which is controlled through the dq rotating coordinate system. In the abc three-phase stationary coordinate system, the formulas for the active power Ps and reactive power Qs on the system side are unique. According to the instantaneous power equation, the expressions for the active power Ps and reactive power Qs are:

[0010]

[0011] in , , , , , It refers to the three-phase voltage and current; From the inverse park transformation, we get:

[0012]

[0013] Substituting the formula from the Parker inverse transform into the differential equations for inductance and capacitance, and assuming the inverter is in normal operating condition (i.e., only positive sequence and no zero sequence), we can obtain the power expression for dq rotation as follows:

[0014]

[0015] The power expression for dq rotation is calculated by converting the three-phase voltage and current on the grid side into d and q components in the dq rotating coordinate system. Let This ensures that the d-axis component of the grid-side voltage aligns with the direction of the grid-side voltage vector, leading to the transformed formula:

[0016]

[0017] A three-phase full-bridge topology is created using IGBTs. The DC side of this topology is connected to a 750 / 700V DC bus, which connects to the Boost converter unit of the photovoltaic module and the output of the bidirectional DC-DC converter for battery energy storage. The AC side is connected to a 380V / 50Hz common AC bus, which is then connected to the grid-side public power grid. Since the grid-side is connected to an infinite power grid, the grid's power frequency voltage remains constant. Because the output voltage of the grid-connected inverter introduces the voltage at the grid connection point, therefore… It remains unchanged, only for... Adjustment is used to regulate the active power output of the inverter; similarly, only the... Adjustment, to adjust the reactive power output of the inverter;

[0018] The inverter-side output dq voltage component is controlled by a feedforward decoupling method. , Its cross-decoupling control equations are as follows:

[0019]

[0020] in , The output voltage component dq is the inverter side voltage. , For power loop PI parameters, , For the current loop PI parameters, It is the dq voltage component on the grid side; Substituting equations (10) and (11) into equation (9), we obtain the decoupled dq axis equation, which is only related to the d-axis or q-axis alone:

[0021] Complete decoupling and combine it with outer loop synchronization processing:

[0022]

[0023] Complete the setting of voltage outer loop and current inner loop parameters, which will serve as the initial parameters for subsequent optimization of voltage outer loop and current inner loop parameters.

[0024] Furthermore, the method for optimizing the parameters of the voltage outer loop and current inner loop of the present invention includes: The grid voltage is acquired by a PLL, and the voltage phase and frequency are calculated. Simultaneously, the phase signal is converted into the three-phase current signal acquired by the abc-dq converter and then into a dq coordinate system. and Quantity; For parallel processing of the d and q axes, the d-axis: the outer voltage loop acquires the DC-side voltage signal. With the rated DC voltage The differential feedback is generated by the difference, and after passing through the voltage loop PI controller, the output is... Signal, and with The signals are subtracted to obtain the differential signal of the inner current loop. This differential signal is then passed through the PI controller of the current loop and coupled with a coupling term to obtain the output. Signal; q-axis: setting ,and The signals are subtracted to form a differential signal, which is then passed through a PI controller in a current loop. A coupling term is also added to the differential signal, resulting in the output. The signal is then converted by the dq-abc inverse converter and the PWM output is used to give the inverter the PWM signal to form a closed loop control. The filter module on the photovoltaic side adopts L filter, DC bus capacitor C1=3 mF, DC bus voltage Udc-=750 V, grid-connected three-phase inductor, resistor Lg=3 mH, Rg=3 / 8 ohm, grid-connected line voltage amplitude egd=311 V; Further tuning of parameters The model of the controlled object in the control equations of the inner current loop is:

[0025] Therefore, the open-loop function of the current loop is:

[0026] Therefore, the closed-loop transfer function is:

[0027] The zero point of the PI controller in the voltage loop is designed at wbw,v / 3, and the open-loop gain of kgp,v at that point is set to 1. Further obtaining the equivalent modulation wave equation of SVPWM in the ABC coordinate system will make the implicit modulation wave of SVPWM explicit.

[0028] Furthermore, the implicit modulation waveform explicitation method of the SVPWM of the present invention includes: Using a dual-loop control of voltage and current, combined with the principle of space voltage vector approximation, the following equation is derived:

[0029] In the formula, m is the SVPWM modulation coefficient. The average phase voltage of the first sector is further obtained as follows:

[0030] Similarly, the modulation waveforms of other sectors are derived, and the phase voltage modulation function for each phase is:

[0031] Obtain the modulated wave of the implicit modulated wave of SVPWM.

[0032] Furthermore, the method for conducting multiple experimental controls in this invention includes: Set up an experimental control group: Control Group 1: Traditional single-stage photovoltaic system: Control Group 1 does not include a battery energy storage unit. The photovoltaic array is directly connected to the grid through an inverter after DC-DC boost. The conventional perturbation-observation method is used for MPPT control. Control group 2 conventional SPWM control system: Control group 2 includes an energy storage unit, but adopts the traditional sinusoidal pulse width modulation (SPWM) in the inverter modulation stage and does not adopt the dq axis feedforward decoupling control strategy; Under steady-state operating conditions, the output current waveforms and spectrum analysis results of control group 1 and control group 2 were obtained to verify the effectiveness of the inverter control strategy.

[0033] Furthermore, the method for obtaining the final microgrid simulation model in step S400 of the present invention includes: The control strategy of the grid inverter is optimized using a feedforward cross-coupling method, and the PI parameters are retuned based on the modulus maximum method. The specific tuning calculation process is as follows: Inner current loop: The bandwidth is set to 500Hz, and the parameters of the current loop are:

[0034] Simultaneously decouple the d-axis and q-axis components; Based on the inner current loop, the outer voltage loop is tuned, with its bandwidth set to one-tenth of the current loop's bandwidth, i.e., 50Hz. The parameters of the outer voltage loop are:

[0035] Substitute the optimized control parameters back into the simulation model, and repeat step S300 to obtain the final parameters, thus obtaining the final microgrid simulation model.

[0036] In summary, the fully trained cyclic deep policy network of the microgrid simulation model in this invention can learn the different characteristics and temporal coupling relationships of the OLTC and photovoltaic inverter clusters during voltage management. This allows the fully trained agents to achieve coordinated control of the upstream OLTC and downstream photovoltaic inverter clusters in the distribution network simply by adjusting the reactive power output of the photovoltaic inverters during voltage regulation. Compared to existing methods for coordinated voltage regulation of heterogeneous devices within the same grid, this invention does not require disrupting the original voltage regulation logic of the devices, thus facilitating grid connection of photovoltaic inverters. Attached Figure Description

[0037] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a framework diagram of the microgrid simulation model of the present invention; Figure 3 This is a structural diagram of the photovoltaic MPPT algorithm of the present invention; Figure 4 This is a structural diagram of the photovoltaic bidirectional DC-DC converter of the present invention; Figure 5 This is a structural diagram of the energy storage SVPWM implementation of the present invention; Figure 6 This is the voltage and current dual-loop control diagram of the grid-connected inverter of the present invention; Figure 7 This is a waveform diagram of the DC bus of the present invention; Figure 8 This is a waveform diagram of the grid-side voltage and current of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0039] like Figure 1 As shown in the figure, the method for constructing a common bus photovoltaic energy storage AC microgrid simulation model in this embodiment involves the following steps performed by a computer device: S100. Define the microgrid system architecture and clarify the simulation objectives; S200. Based on the microgrid system architecture, digital modeling is performed on each functional module of the microgrid to construct a simulation model; S300: Set initial parameters for the simulation model and simulation scenarios to conduct multiple experimental comparisons; S400. Optimize the simulation model based on the results of multiple experiments. Repeat step S300 on the optimized simulation model to obtain the final microgrid simulation model with qualified accuracy.

[0040] The following provides a detailed explanation of each step: S100. Define the microgrid system architecture and clarify the simulation objectives; The architecture of a microgrid is an organic combination of its physical structure and control logic. It is far more than a simple collection of equipment; rather, it is an intelligent local energy system with self-consistency, dispatchability, and scalability.

[0041] like Figure 2 As shown, the microgrid architecture in this scheme includes: photovoltaic modules, battery energy storage modules, and grid-connected inverter modules; The photovoltaic power generation system adopts a two-stage topology. The front-stage DC-DC module can use the MPPT algorithm to make the photovoltaic module work at the real-time maximum power point, while the rear-stage DC-AC converter can realize DC inversion to AC to achieve grid connection. The photovoltaic module in this design adopts a five-series and ten-parallel photovoltaic panel array to construct a control mode for maximum power point tracking of photovoltaic panels. like Figure 3As shown, the incremental conductance method is used to control the MPPT module. This control method is designed based on the fact that the derivative of the output power of the solar cell with respect to the voltage is 0 at the maximum power point. It can determine the relationship between the operating point voltage and the maximum power point voltage. When the derivative of power with respect to voltage is greater than zero, the voltage of the photovoltaic is less than the voltage at the maximum power point, and the current is adjusted accordingly to achieve maximum power point tracking. At the same time, a BOOST boost module is used, with the switching frequency set to 20000Hz, the output voltage to 750V, the output voltage ripple to 1%, and the input current ripple to 5%.

[0042] Assuming the photovoltaic panels operate at a light intensity of 1000 and a temperature of 25 degrees Celsius, the maximum output power of each photovoltaic unit is 230.1W, and the voltage of each power supply is 30.36V. Therefore, the maximum total power is:

[0043] At the maximum power point, the input voltage of the BOOST circuit is:

[0044] The input current is:

[0045] The output voltage ripple is:

[0046] The output current ripple is:

[0047] Therefore, the formulas for calculating the inductance and capacitance of the BOOST circuit are:

[0048]

[0049] S200. Based on the microgrid system architecture, construct a simulation model; The simulation model includes a digital model of the battery energy storage unit module and a digital model of the grid-connected inverter module; The methods for establishing digital models of battery energy storage unit modules include: like Figure 4As shown, a lithium-ion battery is used, along with a bidirectional DC-DC converter submodule. This submodule adopts a BUCK-BOOST topology, with its input connected to the battery and its output connected to the energy storage converter. The module employs dual-loop voltage and current control. With the support of the BUCK-BOOST circuit, when the energy storage DC bus voltage is lower than a given value, the operating signal of the IGBT switch is adjusted to switch to the BOOST boost circuit, allowing power to flow from the battery module to the DC bus, thereby stabilizing the DC bus voltage on the energy storage side.

[0050] like Figure 5 As shown in the model, the voltage regulation response time of the bidirectional DC-DC module is less than 0.1s. This bidirectional DC-DC converter can operate in three modes: the first is Buck charging mode, where switch Q1 is off and Q2 is on, and the capacitor flows from the DC bus side to the energy storage side; the second is Boost discharging mode, where switch Q1 is on and Q2 is off, and the energy flows from the energy storage side to the DC bus side; the third is Buck-Boost charging and discharging mode, where switches Q1 and Q2 alternately and complementaryly conduct during the switching cycle, and the inductor current alternates between positive and negative within one switching cycle, enabling bidirectional energy flow.

[0051] One of the main functions of this battery-powered bidirectional DC-DC converter is to support the bus voltage. This model uses dual closed-loop control of voltage and current. The working principle of the converter is derived below: First, write the differential equations for the inductor and capacitor:

[0052]

[0053] Where iL is the inductor current, Vin is the battery voltage, io is the output current, vdc is the converter output voltage, RL is the inductor parasitic resistance, and d is the duty cycle of switch Q1. Switch Q2 and switch Q1 are complementary in conduction, so the duty cycle of switch Q2 is 1-d.

[0054] Methods for establishing digital models of grid-connected inverter modules: like Figure 6 As shown, a three-phase full-bridge topology is adopted, with each half-bridge consisting of an IGBT connected in parallel with a diode. The DC input is 750 / 700V, and the AC output is connected to the common AC bus (380V / 50Hz). The rated power is 1000W. The photovoltaic grid-connected converter uses UI control. This control is performed using the dq rotating coordinate system. Compared with the abc three-phase stationary coordinate system, the derivation of the dq rotating coordinate system is more convenient.

[0055] First, in the three-phase stationary coordinate system abc, the formulas for the active power Ps and reactive power Qs on the system side are unique. Simultaneously, based on the instantaneous power equation, the expressions for active power Ps and reactive power Qs are obtained as follows:

[0056]

[0057] in , , , , , These are the three-phase voltage and current.

[0058] From the inverse Park transform, we know that:

[0059]

[0060] Substituting the formulas from the Parker inverse transform into (1) and (2), and assuming the inverter is in normal operating condition (i.e., only positive sequence and no zero sequence), we can obtain the power expression for dq rotation as follows:

[0061]

[0062] This formula converts the three-phase voltage and current on the grid side into d and q components in a dq rotating coordinate system for calculation. To ensure that the d-axis component of the grid-side voltage aligns with the direction of the grid-side voltage vector, it is necessary to... This leads to the transformed formula:

[0063]

[0064] Because the grid side is connected to an infinitely large power grid, its voltage is constant. It remains unchanged, so we only need to... Adjustment can regulate both the active power output of the inverter and, similarly, only the active power output of the inverter needs to be adjusted. Adjustment can regulate the reactive power output of the inverter.

[0065]

[0066] As can be seen from this control model, if we want to control the dq voltage component of the inverter side output... , If the control of the d-axis and q-axis is coupled, it will be difficult to design the controller. Therefore, a feedforward decoupling method is adopted to reduce the difficulty of controller design. The cross-decoupling control equation is as follows:

[0067]

[0068] in , The output voltage component dq is the inverter side voltage. , For power loop PI parameters, , For the current loop PI parameters, It is the dq voltage component on the grid side.

[0069] Substituting equations (10) and (11) into equation (9), we can obtain the decoupled dq-axis equation, which is only related to the d-axis or q-axis alone:

[0070] At this point, decoupling is complete. The next step is to process the outer loop:

[0071]

[0072] Thus, the parameter settings for the outer voltage loop and the inner current loop are complete.

[0073] Further optimization of the set parameters can be performed as follows: First, the PLL acquires the grid voltage, then calculates the voltage phase and frequency. Simultaneously, the phase signal is converted to the three-phase current signal acquired by the abc-dq converter and then into a dq coordinate system. and Quantity.

[0074] Simultaneously, dual-axis parallel processing of d and q axes begins. The d-axis: outer voltage loop acquires the DC-side voltage signal. With the rated DC voltage The differential feedback is generated by the difference, and after passing through the voltage loop PI controller, the output is... Signal, and with The signals are subtracted to obtain the differential signal of the inner current loop. This differential signal is then passed through the PI controller of the current loop and coupled with a coupling term to obtain the output. Signal. q-axis: Setting ,and The signals are subtracted to form a differential signal, which is then passed through a PI controller in a current loop. A coupling term is also added to the differential signal, resulting in the output. The signal is then converted by a dq-abc inverter, and the PWM output is used to give the inverter a PWM signal to form a closed loop control. The filter module on the photovoltaic side uses L filter, DC bus capacitor C1=3 mF, DC bus voltage Udc-=750 V, grid-connected three-phase inductor, resistor Lg=3 mH, Rg=3 / 8 ohm, grid-connected line voltage amplitude egd=311 V.

[0075] The parameters are then tuned. The model of the controlled object in the control equations of the inner current loop is:

[0076] Therefore, the open-loop function of the current loop is:

[0077] Therefore, the closed-loop transfer function is:

[0078] The bandwidth of the current loop is set to f = 500Hz, therefore the PI controller parameters for the current loop are tuned as follows:

[0079]

[0080] 0.375 = 1178.1 The model of the controlled object in the control equations of the voltage outer loop is:

[0081] Therefore, the open-loop function of the current loop is (simplifying the inner current loop to a first-order standard transfer function):

[0082] Therefore, the voltage closed-loop transfer function is:

[0083] in This is the voltage gain coefficient. Time constant

[0084]

[0085] Based on general tuning criteria, the bandwidth f of the voltage loop v =f / 10=50 Hz, and the symmetrical optimal method is used for tuning. The symmetrical optimal method positions the PI controller's zero between the integral and inertial elements to maximize the phase margin. We design the zero of the voltage loop PI controller at... / 3 places, order The open-loop gain at this point is 1, or 0 dB;

[0086]

[0087] 841.67 The energy storage-side inverter employs SVPWM control. SVPWM is essentially a modified SPWM that regularly samples a modulation wave injected with a zero-sequence component into a three-phase sine wave. However, the modulation process of SVPWM is implemented in space, while SPWM is implemented phase-by-phase in the ABC coordinate system; the phase voltage modulation wave of SPWM is a sine wave, while SVPWM does not have a clearly defined phase voltage modulation wave, which is implicit. To reveal the intrinsic relationship between SVPWM and SPWM, it is necessary to derive the equivalent modulation wave equation of SVPWM in the ABC coordinate system, that is, to make the implicit modulation wave of SVPWM explicit.

[0088] Using a dual-loop control of voltage and current, combined with the principle of space voltage vector approximation, the following equation can be derived:

[0089] In this formula, m is the SVPWM modulation coefficient. Therefore, using the above formula, the average value of each phase voltage in the first sector can be obtained:

[0090] Similarly, the modulation waveforms of other sectors can be derived, and the phase voltage modulation function for each phase is:

[0091] Obtain the modulated wave of the implicit modulated wave of SVPWM.

[0092] S300: Set initial parameters for the simulation model and simulation scenarios to conduct multiple experimental comparisons; According to the microgrid simulation model mentioned above, the model includes a photovoltaic power generation unit with a rated power of 10kW, a 20Ah lithium-ion battery energy storage unit, and a three-phase grid-connected inverter unit.

[0093] Initial simulation model parameters are set as follows: Simulating a standard test environment (1000W / m², 25℃), with a maximum output power of approximately 11.5kW. The DC bus voltage is set to 750V, with an allowable fluctuation range of 2%. The switching frequency of the photovoltaic-side Boost circuit is set to 20kHz, with an output voltage ripple limit of 1%. The response time of the bidirectional DC-DC converter on the energy storage side is required to be less than 0.1s. The inverter-side carrier frequency is 10kHz, employing SVPWM complementary switching logic. The current inner loop bandwidth is set to 500Hz, the voltage outer loop bandwidth is set to 50Hz, and the PI parameters are tuned using the symmetrical optimal method.

[0094] To verify the effectiveness of the BUCK-BOOST converter and grid-connected inverter model in this scheme, this example sets up two test environments: drastic fluctuations in light intensity and sudden load changes. In the tests, this example uses two control groups for comparison: Control group 1 (traditional single-stage photovoltaic system): This group does not include a battery energy storage unit. The photovoltaic array is directly connected to the grid through an inverter after being boosted by DC-DC. The conventional perturbation and observation (P&O) method is used for MPPT control.

[0095] Control group 2 (conventional SPWM control system): This group includes an energy storage unit, but uses traditional sinusoidal pulse width modulation (SPWM) in the inverter modulation stage and does not adopt the dq axis feedforward decoupling control strategy.

[0096] S400. Optimize the simulation model based on the results of multiple experiments. Repeat step S300 for the optimized reverse model to obtain the final microgrid simulation model with qualified accuracy.

[0097] Set up an experimental control group: Control Group 1: Traditional single-stage photovoltaic system: Control Group 1 does not include a battery energy storage unit. The photovoltaic array is directly connected to the grid through an inverter after DC-DC boost. The conventional perturbation-observation method is used for MPPT control. Control group 2 conventional SPWM control system: Control group 2 includes an energy storage unit, but adopts the traditional sinusoidal pulse width modulation (SPWM) in the inverter modulation stage and does not adopt the dq axis feedforward decoupling control strategy; Under steady-state operating conditions, the output current waveforms and spectrum analysis results of control group 1 and control group 2 were obtained to verify the effectiveness of the inverter control strategy. The results are as follows: like Figure 7 , Figure 8As shown in the simulation results, the control group 1, lacking the power buffer of the energy storage unit, experiences a significant drop in DC bus voltage when the light intensity suddenly decreases, resulting in a long voltage recovery time and large steady-state ripple. In contrast, the model of this invention benefits from the dual-loop voltage and current control of the bidirectional Buck-Boost converter of the battery. When the DC bus voltage is detected to be lower than a given value, it quickly switches to Boost discharge mode, allowing energy to flow from the energy storage side to the DC bus.

[0098] Table 1 Comparison of DC bus voltage stability indicators

[0099] Table 1 shows the DC bus voltage performance indicators under different control strategies. The model of this invention stabilizes the DC bus voltage at 750V, with ripple controlled within 1% (approximately 7.5V), and the voltage regulation response time is less than 0.1s, meeting the design requirements.

[0100] Next, under steady-state operating conditions, the effectiveness of the inverter control strategy proposed in this invention is verified. Figure 8 The waveform and spectrum analysis of the output current on the AC side of the inverter are shown for control group 2 and the model of the present invention.

[0101] Control group 2 uses SPWM modulation and lacks feedforward decoupling control, resulting in coupling between the d-axis and q-axis control and poor dynamic performance. Spectral analysis shows that the output current of control group 2 contains a significant third harmonic component. In contrast, the model of this invention employs complementary SVPWM control and a dq-axis feedforward decoupling strategy, effectively suppressing the third and fifth harmonics and reducing switching losses. Furthermore, the model of this invention uses complementary logic with a 1mus turn-on time difference between adjacent switches, achieving a converter efficiency of up to 95%. Table 2 shows the power quality comparison data at the grid connection point (PCC).

[0102] Table 2 Comparison of Grid-Connected Power Quality and Efficiency

[0103] First, based on the microgrid architecture design, the photovoltaic, energy storage, and inverter modules were built and their physical parameters were set in the Simulink environment of MATLAB. The specific parameter settings are as follows: Firstly, regarding the photovoltaic array, a five-series and ten-parallel design is adopted, with a maximum power of 230.1W per panel, and the set environmental parameters are a room temperature of 25℃ and a light intensity of 1000W / m². 2Under the premise that the maximum total power of the system is 11505W, according to the MPPT algorithm, the voltage and current of the maximum power are 151.8V and 75.8A respectively. The inductance of the photovoltaic side is 1.6mH and the capacitance is 403uF. The energy storage system uses lithium-ion batteries with a given rated capacity of 20Ah. The SOC is set to operate between 20% and 80% to extend the battery life. The DC bus voltage of the energy storage side is set to 700V and the capacitance of the DC bus is 3mF. The filter inductance of the grid-connected inverter is 3mH and its parasitic resistance is set to 0.375 ohms. The carrier frequency of the PWM is 10kHz and the grid connection voltage and frequency are 380V / 50Hz.

[0104] To better verify the effectiveness of the control strategy, the following dynamic simulation experimental scenario was set up: Scenario 1: Steady-state operation between 0.0-0.8s, with the light intensity set to 1000W / m². 2 At this time, the photovoltaic system should output full power, and any remaining power will be used to charge the battery's SOC; Scenario 2: Set a photovoltaic power drop between 0.8-1.6s, with the light intensity decreasing to 400W / m². 2 At this time, the power output of the photovoltaic system is insufficient to support the load, and the Xu Ya battery supplies power to the grid and is in a discharging state.

[0105] S400. Optimize the simulation model based on the results of multiple experiments. Repeat step S300 on the optimized simulation model to obtain the final microgrid simulation model with qualified accuracy. Since the parameters in the S300 may exhibit dynamic response delays or steady-state oscillations during simulation, the control strategy for the grid-connected inverter is optimized using a feedforward cross-coupling method. The PI parameters are then retuned based on the modulus maximum method. The specific tuning calculation process is as follows: Regarding the inner current loop, the bandwidth is set to 500Hz, therefore the parameters of the current loop are:

[0106] The tuning of this parameter ensures that the current can follow quickly, while decoupling the d-axis and q-axis components.

[0107] Based on the current inner loop, the voltage outer loop is tuned, with its bandwidth set to one-tenth of the current loop's bandwidth, i.e., 50Hz. Therefore, the parameters of the voltage outer loop are:

[0108] Positive definite parameters can stabilize the DC bus voltage and provide a certain degree of immunity to load fluctuations.

[0109] Substituting the optimized control parameters back into the model and repeating scenarios 1 and 2 in S3, the performance improvements obtained are compared as shown below.

[0110] Under the conditions of coarse control parameter adjustment and no cross decoupling, the DC bus fluctuation is: The DC bus voltage fluctuation is approximately 4.5%, while after parameter readjustment, the DC bus voltage fluctuation can be obtained as follows: The harmonic distortion rate is approximately 0.8%, which indicates that the DC bus voltage is better stabilized after parameter adjustment. The grid-connected current harmonic distortion rate before and after parameter adjustment is 4.2% and 1.45%, respectively, and the average efficiency of the converter is 84.5% and 91%, respectively.

[0111] The final model verification results show that the optimized simulation model exhibits a maximum DC bus voltage drop of only 5V under sudden light drop conditions, and recovers to a steady state of 750V within 60ms. At the grid connection point, the A-phase current waveform is smooth, and SVPWM modulation effectively eliminates low-order harmonics, verifying the accuracy and robustness of the "simulation model of a common bus photovoltaic energy storage AC microgrid with BUCK-BOOST converter and grid-connected inverter".

[0112] In summary, the simulation model established in this invention achieves efficient energy management through the synergistic effect of incremental conductance test (MPPT) on the photovoltaic side, bidirectional Buck-Boost fast response on the energy storage side, and SVPWM and feedforward decoupling control on the inverter side.

[0113] When photovoltaic power output fluctuates, the model of this invention can maintain the common DC bus voltage within an extremely narrow range of $750V\pm 2\%$ through the "peak shaving and valley filling" effect of the battery. Compared with the control group, this model not only has lower ripple and output voltage ripple in steady state, but also exhibits stronger anti-interference ability and faster response speed (<0.1s) in dynamic processes, verifying the accuracy and superiority of the simulation model in the claims.

[0114] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0115] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0116] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing a simulation model of a photovoltaic energy storage AC microgrid with a common bus, characterized in that, Includes the following steps: S100. Define the microgrid system architecture and clarify the simulation objectives; S200. Based on the microgrid system architecture, digital modeling is performed on each functional module of the microgrid to construct a simulation model; S300: Set initial parameters for the simulation model and simulation scenarios to conduct multiple experimental comparisons; S400. Optimize the simulation model based on the results of multiple experiments. Repeat step S300 on the optimized simulation model to obtain the final microgrid simulation model with qualified accuracy.

2. The method for constructing a simulation model of a photovoltaic energy storage AC microgrid according to claim 1, characterized in that, The simulation model construction methods in step S200 include: a method for establishing a digital model of a battery energy storage unit module, a method for establishing a digital model of a grid-connected inverter module, and a method for constructing a digital model of a photovoltaic module; The methods for establishing digital models of battery energy storage unit modules include: A DC-DC converter submodule with a BUCK-BOOST topology is constructed. The output of the topology is connected to an energy storage converter, and the input is connected to a battery to achieve dual-loop control of voltage and current. With the assistance of the BUCT-BOOST circuit, when the DC bus voltage of the energy storage is less than the threshold, the operating signal of the IGBT switching transistor is adjusted to switch to the BOOST boost circuit, and the power flows from the battery module to the DC bus. Where iL is the inductor current, Vin is the battery voltage, and i o For the output current, V dc R is the output voltage of the converter. L Let d be the parasitic resistance of the inductor, and d be the duty cycle of the switch Q1. Switch Q2 and switch Q1 are complementary in conduction, so the duty cycle of switch Q2 is 1-d.

3. The method for constructing a simulation model of a photovoltaic energy storage AC microgrid according to claim 2, characterized in that, The method for establishing a digital model of a grid-connected inverter module includes: A half-bridge structure is constructed by connecting a diode in parallel with an IGBT, and a three-phase full-bridge topology is constructed by connecting three sets of half-bridge structures. The DC input of the full-bridge topology is 750 / 700V, the AC output is 380V / 50Hz and the common AC bus is 380V / 50Hz, and the rated power is 1000W. The photovoltaic-side grid-connected converter adopts UI control, which is controlled through the dq rotating coordinate system. In the three-phase stationary coordinate system abc, the formulas for the active power Ps and reactive power Qs on the system side are unique. According to the instantaneous power equation, the expressions for the active power Ps and reactive power Qs are: in , , , , , It refers to the three-phase voltage and current; From the inverse park transformation, we get: Substituting the formula from the Parker inverse transform into the differential equations for inductance and capacitance, and assuming the inverter is in normal operating condition (i.e., only positive sequence and no zero sequence), we can obtain the power expression for dq rotation as follows: The power expression for dq rotation is calculated by converting the three-phase voltage and current on the grid side into d and q components in the dq rotating coordinate system. Let This ensures that the d-axis component of the grid-side voltage aligns with the direction of the grid-side voltage vector, leading to the transformed formula: A three-phase full-bridge topology is created using IGBTs. The DC side of this topology is connected to a 750 / 700V DC bus, which connects to the Boost converter unit of the photovoltaic module and the output of the bidirectional DC-DC converter for battery energy storage. The AC side is connected to a 380V / 50Hz common AC bus, which is then connected to the grid-side public power grid. Since the grid-side is connected to an infinite power grid, the grid's power frequency voltage remains constant. Because the output voltage of the grid-connected inverter introduces the voltage at the grid connection point, therefore… It remains unchanged, only for... Adjustment is used to regulate the active power output of the inverter; similarly, only the... Adjustment, set to regulate the reactive power output of the inverter; The inverter-side output dq voltage component is controlled by a feedforward decoupling method. , Its cross-decoupling control equations are as follows: in , The output voltage component dq is the inverter side voltage. , For power loop PI parameters, , For the current loop PI parameters, It is the dq voltage component on the grid side; Substituting equations (10) and (11) into equation (9), we obtain the decoupled dq axis equation, which is only related to the d-axis or q-axis alone: Complete decoupling and combine it with outer loop synchronization processing: Complete the setting of voltage outer loop and current inner loop parameters, which will serve as the initial parameters for subsequent optimization of voltage outer loop and current inner loop parameters.

4. The method for constructing a simulation model of a photovoltaic energy storage AC microgrid according to claim 3, characterized in that, The optimization methods for voltage outer loop and current inner loop parameters include: The grid voltage is acquired by a PLL, and the voltage phase and frequency are calculated. Simultaneously, the phase signal is converted into the three-phase current signal acquired by the abc-dq converter and then into a dq coordinate system. and Quantity; For parallel processing of the d and q axes, the d-axis: the outer voltage loop acquires the DC-side voltage signal. With the rated DC voltage The differential feedback is generated by the difference, and after passing through the voltage loop PI controller, the output is... Signal, and with The signals are subtracted to obtain the differential signal of the inner current loop. This differential signal is then passed through the PI controller of the current loop and coupled with a coupling term to obtain the output. Signal; q-axis: setting ,and The signals are subtracted to form a differential signal, which is then passed through a PI controller in a current loop. A coupling term is also added to the differential signal, resulting in the output. The signal is then converted by the dq-abc inverse converter and the PWM output is used to give the inverter the PWM signal to form a closed loop control. The filter module on the photovoltaic side adopts L filter, DC bus capacitor C1=3 mF, DC bus voltage Udc-=750V, grid-connected three-phase inductor, resistor Lg=3 mH, Rg=3 / 8 ohm, grid-connected line voltage amplitude egd=311 V; Further tuning of parameters The model of the controlled object in the control equations of the inner current loop is: Therefore, the open-loop function of the current loop is: Therefore, the closed-loop transfer function is: The zero point of the PI controller in the voltage loop is designed at wbw,v / 3, and the open-loop gain of kgp,v at that point is set to 1. Further obtaining the equivalent modulation wave equation of SVPWM in the ABC coordinate system will make the implicit modulation wave of SVPWM explicit.

5. The method for constructing a simulation model of a photovoltaic energy storage AC microgrid according to claim 4, characterized in that, Methods for expliciting the implicit modulation waveform in SVPWM include: Using a dual-loop control of voltage and current, combined with the principle of space voltage vector approximation, the following equation is derived: In the formula, m is the SVPWM modulation coefficient. The average phase voltage of the first sector is further obtained as follows: Similarly, the modulation waveforms of other sectors are derived, and the phase voltage modulation function for each phase is: Obtain the modulated wave of the implicit modulated wave of SVPWM.

6. The method for constructing a simulation model of a photovoltaic energy storage AC microgrid according to claim 2, characterized in that, Methods for conducting multiple experimental controls include: Set up an experimental control group: Control Group 1: Traditional single-stage photovoltaic system: Control Group 1 does not include a battery energy storage unit. The photovoltaic array is directly connected to the grid through an inverter after DC-DC boost. The conventional perturbation-observation method is used for MPPT control. Control group 2 conventional SPWM control system: Control group 2 includes an energy storage unit, but adopts the traditional sinusoidal pulse width modulation (SPWM) in the inverter modulation stage and does not adopt the dq axis feedforward decoupling control strategy; Under steady-state operating conditions, the output current waveforms and spectrum analysis results of control group 1 and control group 2 were obtained to verify the effectiveness of the inverter control strategy.

7. The method for constructing a simulation model of a photovoltaic energy storage AC microgrid according to claim 6, characterized in that, The method for obtaining the final microgrid simulation model in step S400 includes: The control strategy of the grid inverter is optimized using a feedforward cross-coupling method, and the PI parameters are retuned based on the modulus maximum method. The specific tuning calculation process is as follows: Inner current loop: The bandwidth is set to 500Hz, and the parameters of the current loop are: Simultaneously decouple the d-axis and q-axis components; Based on the inner current loop, the outer voltage loop is tuned, with its bandwidth set to one-tenth of the current loop's bandwidth, i.e., 50Hz. The parameters of the outer voltage loop are: Substitute the optimized control parameters back into the simulation model, and repeat step S300 to obtain the final parameters, thus obtaining the final microgrid simulation model.

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