Photovoltaic off-grid inverter control method and system

Abstract

The invention relates to the technical field of power electronics, in particular to a photovoltaic off-grid inverter control method and system, and the method comprises the following steps: applying a test signal to identify an output interaction characteristic parameter, predicting the power generation power through combining with weather and attenuation, calculating the power fluctuation, and adjusting a current control parameter set. And calculating voltage and reactive power compensation parameters to generate an inverter control instruction, and combining a temperature load prediction trend to adjust a power allowable value to obtain a predictive power calibration coefficient. According to the invention, by analyzing the output interaction characteristics, enhancing the perception capability of the inverter to the actual operation environment, combining with the prediction of the photovoltaic power generation amount, realizing the prediction and influence evaluation of the power fluctuation, improving the adaptive adjustment capability of the current control parameters, improving the output voltage and reactive power control precision by utilizing the interaction characteristics, and optimizing the electric energy quality; and through thermal management of multi-point temperature and load prediction, the operation safety is improved, the service life of equipment is prolonged, and the operation performance of the photovoltaic off-grid system in a complex environment is improved.

Description

Technical Field

[0001] The present invention relates to the field of power electronics technology, and particularly to a control method and system for a photovoltaic off-grid inverter. Background Art

[0002] The field of power electronics technology includes the design and manufacture of power conversion devices and their applications in energy conversion. The core content of this field involves the working characteristics of power electronic devices, the optimization of circuit topologies, and the development of control strategies. The key research directions include power conversion problems in scenarios such as photovoltaic power generation systems, wind power generation systems, and electric vehicle drive systems. The technical system covers pulse width modulation technology, maximum power point tracking technology, and grid-connected inverter technology, aiming to provide theoretical support for improving power conversion efficiency, system operation stability, and anti-interference ability.

[0003] Among them, a control method for a photovoltaic off-grid inverter refers to a technical solution for the operation mode of the inverter in an independent photovoltaic power generation system. This topic covers the stability control of the output voltage and frequency of the inverter under the condition of no support from the public power grid, the power coordination mechanism between the energy storage unit and the photovoltaic array, and the dynamic response strategy during load mutation. The inverter modulation signal is generated through voltage-current double-loop control, the charge state monitoring mechanism is used to manage the charging and discharging process of the energy storage battery, the perturbation observation method is combined to adjust the working point of the photovoltaic array, and the power distribution during parallel operation of multiple inverters is achieved based on frequency droop control.

[0004] Traditional control methods for photovoltaic off-grid inverters adopt a feedback control logic based on instantaneous measurement values, showing deficiencies in dealing with the inherent intermittency of photovoltaic power generation and load mutation. They lack the ability to perceive the specific impedance of the connection line and the change of load type in real time. The voltage regulation accuracy is limited. When transmitting power over a long distance or connecting to a non-linear load, the terminal voltage deviation exceeds the allowable range, and power factor correction cannot be effectively carried out, increasing line losses. It cannot carry out forward-looking power planning by combining information such as weather forecasts and component attenuation, resulting in non-optimal energy capture efficiency under rapidly changing meteorological conditions. The maintenance of system stability relies on fast response and margin design, lacking a control parameter adaptive adjustment mechanism based on predictive evaluation. In the face of foreseeable large power fluctuations, due to parameter mismatch, there will be slow response or overshoot, affecting the stability of the DC bus voltage or even causing system collapse. The thermal protection mechanism is mostly a simple threshold-triggered type, unable to perform power management in advance according to load trends and environmental temperature changes, resulting in frequent activation of protection under critical conditions or shortening of equipment life due to cumulative thermal stress, affecting power supply continuity. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, embodiments of the present invention provide a control method and system for a photovoltaic off-grid inverter. The technical solution is as follows:

[0006] To achieve the above object, the present invention adopts the following technical solution. A control method for a photovoltaic off-grid inverter includes the following steps:

[0007] S1: Apply a test signal to the output end of the inverter, collect voltage and current response data, analyze the amplitude ratio and phase difference in the disturbance frequency band, extract the line impedance characteristics, monitor the dynamic change of the output current and perform transient analysis, extract the waveform timing characteristics and analyze the load power factor characteristics, and obtain the output interaction characteristic parameters;

[0008] S2: Call the output interaction characteristic parameters, obtain regional meteorological data, predict the irradiance in multiple time periods, combine with a dirt sensor to evaluate the optical attenuation degree of the components in real time, combine with the ambient temperature value to predict the power generation of the photovoltaic grid in multiple time periods, and generate a power generation prediction profile;

[0009] S3: Call the power generation prediction profile, calculate the volatility of the predicted photovoltaic power value, evaluate the impact of the volatility on the stability of the DC bus, and adjust the current control operation parameters to establish a current control parameter set;

[0010] S4: Call the current control parameter set and the output interaction characteristic parameters, evaluate the line voltage drop according to the line impedance characteristics, calculate the voltage adjustment parameter at the output end of the inverter, calculate the reactive power compensation amount according to the load power factor characteristics and in combination with the active power, obtain the reactive current adjustment parameter, and generate an inverter control instruction.

[0011] As a further solution of the present invention, the output interaction characteristic parameters are specifically line impedance parameters, load power factor parameters, current transient characteristic parameters and disturbance response parameters. The power generation prediction profile includes irradiance distribution values, component attenuation coefficients, and temperature-related power generation prediction values. The current control parameter set is specifically a power fluctuation threshold, a bus voltage tolerance parameter, and a current loop gain coefficient. The inverter control instruction specifically refers to a voltage compensation amount, a reactive current component, and an impedance compensation factor.

[0012] As a further solution of the present invention, the steps of applying a test signal to the output end of the inverter, collecting voltage and current response data, analyzing the amplitude ratio and phase difference in the disturbance frequency band, extracting the line impedance characteristics, monitoring the dynamic change of the output current and performing transient analysis, extracting the waveform timing characteristics and analyzing the load power factor characteristics, and obtaining the output interaction characteristic parameters are specifically as follows:

[0013] S101: Apply a test signal to the output end of the inverter, collect voltage and current response data, combine with a band-pass filter to isolate the test frequency components, calculate the voltage response amplitude, voltage response phase, current response amplitude, and current response phase at the test frequency, and establish a disturbance frequency response phasor;

[0014] S102: Based on the perturbed frequency response phasor, calculate the impedance modulus of the transmission line according to the voltage response amplitude and the current response amplitude, calculate the impedance phase angle according to the voltage response phase and the current response phase, and combine the impedance modulus and the impedance phase angle to obtain the line equivalent resistance value and the line equivalent reactance value, and obtain the line impedance characteristic parameters;

[0015] S103: Invoke the line impedance characteristic parameters, record the transient waveform by monitoring the change rate of the inverter output current, extract the timing characteristics of the waveform, calculate the load power factor angle, obtain the load power factor characteristics, and generate the output interaction characteristic parameters.

[0016] As a further solution of the present invention, the steps of invoking the output interaction characteristic parameters, obtaining regional meteorological data, predicting the irradiance of multiple time periods, combining with a dirt sensor to evaluate the optical attenuation degree of the component in real time, and predicting the power generation of the photovoltaic grid in multiple time periods in combination with the environmental temperature value and generating a power generation prediction profile are specifically as follows:

[0017] S201: Invoke the output interaction characteristic parameters, obtain regional meteorological data, extract the irradiance prediction data and the environmental temperature prediction data, and obtain the irradiance prediction value sequence by combining with time series interpolation;

[0018] S202: Based on the irradiance prediction value sequence, invoke the dirt sensor, calculate the optical attenuation ratio of the surface of the photovoltaic module by analyzing the difference between the current sensor reading and the calibrated sensor reading in real time, and obtain the optical attenuation evaluation value;

[0019] S203: Invoke the optical attenuation evaluation value, combine the environmental temperature prediction data and the irradiance prediction data, calculate the predicted power generation of each photovoltaic module in multiple time periods, obtain the predicted data of the power generation of the power grid in multiple time periods, and establish a power generation prediction profile.

[0020] As a further solution of the present invention, the formula for calculating the predicted power generation of each photovoltaic module in multiple time periods is:

[0021] P PV (k′) = η STC ·A·G(k′)·η·[1 + γ·(TCE(k′) - T STC )];

[0022] Calculate the predicted power generation value of a single photovoltaic module;

[0023] Among them, P PV (k′) represents the predicted power of time period k′, η STCRepresents the component efficiency under standard test conditions, A represents the component area, G(k′) represents the interpolated irradiance prediction value for time period k′, η represents the optical attenuation evaluation value, γ represents the power temperature coefficient, TCE(k′) represents the estimated operating temperature of the photovoltaic cell for time period k′, and T STC Represents the temperature under standard test conditions, and k′ represents the index number of the prediction time period.

[0024] As a further solution of the present invention, the steps of calling the generated power prediction profile, calculating the volatility of the photovoltaic power prediction value, evaluating the impact of the volatility on the DC bus stability, and adjusting the current control operation parameters to establish a current control parameter set are specifically as follows:

[0025] S301: Call the generated power prediction profile, calculate the volatility of the photovoltaic power prediction value, and generate a predicted power fluctuation index;

[0026] S302: Based on the predicted power fluctuation index, obtain the rated voltage value of the DC bus and the capacitance value parameter of the bus capacitor, analyze the impact of the photovoltaic power volatility on the DC bus stability, and obtain the bus voltage disturbance risk level;

[0027] S303: According to the bus voltage disturbance risk level, adjust the current control operation parameters, including the current loop proportional-integral gain value and the disturbance observer parameter group, to establish a current control parameter set.

[0028] As a further solution of the present invention, the steps of calling the current control parameter set and the output interaction characteristic parameters, evaluating the line voltage drop according to the line impedance characteristic, calculating the output terminal voltage adjustment parameter of the inverter, calculating the reactive power compensation amount according to the load power factor characteristic and combining with the active power, obtaining the reactive current adjustment parameter, and generating an inverter control instruction are specifically as follows:

[0029] S401: Call the current control parameter set and the output interaction characteristic parameters, calculate the line voltage drop according to the line impedance characteristic and combine with the real-time output current measurement value of the inverter, and obtain the output terminal voltage compensation value according to the target voltage reference value on the load side;

[0030] S402: Call the output terminal voltage compensation value, obtain the real-time output active power measurement value of the inverter according to the load power factor characteristic, calculate the target reactive power compensation amount according to the load power factor characteristic and the real-time active power measurement value, and obtain the target reactive power value;

[0031] S403: Call the target reactive power value, calculate the reactive current adjustment parameter, and obtain the inverter control instruction.

[0032] As a further solution of the present invention, the method further includes:

[0033] S5: Invoke the inverter control instruction, collect the temperatures at multiple positions of the inverter in real time, combine the real-time inverter load power and ambient temperature information, predict the temperature change trend of the inverter components, and adjust the allowable value of the inverter output power according to the rated safety temperature threshold to obtain a predictive power calibration coefficient;

[0034] The predictive power calibration coefficient includes a temperature safety margin, a load power limit, and a thermal inertia decay coefficient.

[0035] As a further solution of the present invention, the steps of invoking the inverter control instruction, collecting the temperatures at multiple positions of the inverter in real time, combining the real-time inverter load power and ambient temperature information, predicting the temperature change trend of the inverter components, and adjusting the allowable value of the inverter output power according to the rated safety temperature threshold to obtain a predictive power calibration coefficient are specifically as follows:

[0036] S501: Invoke the inverter control instruction, use a temperature sensor to collect the temperature data at multiple positions of the inverter in real time, record the real-time measured value of the load power at the inverter output end, and establish a real-time operating state data set;

[0037] S502: Based on the real-time operating state data set, combine the real-time component temperature, inverter load power, and ambient temperature values to calculate the temperature change trend and obtain the predicted component temperature value;

[0038] The specific formula for calculating the temperature change trend is:

[0039]

[0040] Calculate the predicted component temperature value;

[0041] where TY t+Δt represents the predicted temperature after a future time interval of Δt, TD t represents the component temperature measured at the current time t, TG t-Δtl represents the component temperature measured at a past time t - Δtl, Δtl represents the historical time interval used to calculate the change rate, Δt represents the predicted time step, t represents the index of the current time, t + Δt represents the index of the target prediction time, and t - Δtl represents the index of the known historical time;

[0042] S503: Invoke the predicted component temperature value, compare it with the rated safe operating temperature threshold in real time, and adjust the allowable value of the inverter output power to obtain a predictive power calibration coefficient.

[0043] On the other hand, a photovoltaic off-grid inverter control system is provided. This system is applied to the photovoltaic off-grid inverter control method, and the system includes:

[0044] The interaction identification module applies a test signal to the output terminal of the inverter, collects voltage and current response data, analyzes the amplitude ratio and phase difference in the disturbance frequency band, calculates the line impedance, combines the dynamic monitoring of the output current, extracts the waveform timing characteristics of the transient current, calculates the load power factor, and obtains the output interaction characteristic parameters;

[0045] The power generation prediction module calls the output interaction characteristic parameters, obtains regional meteorological data, extracts the values of the dirt sensors and calculates the optical attenuation ratio of the photovoltaic modules, and combines the irradiance prediction data, temperature prediction data, and optical attenuation ratio to predict the power generation of the photovoltaic power grid at multiple time periods and generate a power generation prediction profile;

[0046] The stability regulation module loads the power generation prediction profile, calculates the volatility of the predicted photovoltaic power value, analyzes the influence degree of the power change rate on the bus voltage stability, and establishes a set of current control parameters;

[0047] The compensation control module retrieves the output interaction characteristic parameters and the set of current control parameters, calculates the line voltage drop compensation amount according to the line impedance and the real-time output current, calculates the reactive power compensation demand according to the load power factor and the real-time active power, and generates an inverter control instruction;

[0048] The thermal management module receives the inverter control instruction, collects the temperature data at multiple positions of the inverter, the real-time load power data, and the ambient temperature data, predicts the temperature evolution trend, and combines the rated safety temperature threshold to adjust the allowable value of the inverter output power to obtain a predictive power calibration coefficient.

[0049] The beneficial effects brought by the technical solution provided by the embodiments of the present invention at least include:

[0050] By analyzing the output interaction characteristics, the perception ability of the inverter to the actual operating environment is enhanced. Combining the predicted photovoltaic power generation, the prediction and impact assessment of power fluctuations are realized, the adaptive adjustment ability of the current control parameters is improved, the output voltage and reactive power control accuracy are improved by using the interaction characteristics, the power quality is optimized, and the thermal management of multi-point temperature and load prediction improves the operation safety and extends the equipment life, and improves the operation performance of the photovoltaic off-grid system in a complex environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0052] Figure 1 It is a schematic diagram of the working process of the present invention;

[0053] Figure 2 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0054] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0055] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0056] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0057] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0058] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0059] See also Figure 1 The present invention provides a technical solution, a photovoltaic off-grid inverter control method, comprising the following steps:

[0060] S1: Apply a test signal to the inverter output, collect voltage and current response data, analyze the amplitude ratio and phase difference of the disturbance frequency band, extract the line impedance characteristics, monitor the dynamic changes of the output current and perform transient analysis, extract the waveform timing characteristics and analyze the load power factor characteristics, and obtain the output interaction characteristic parameters;

[0061] S2: Call the output interactive characteristic parameters, obtain regional meteorological data, predict the irradiance in multiple time periods, combine with the dirt sensor, evaluate the optical attenuation of the components in real time, and predict the power generation of the photovoltaic power grid in multiple time periods in combination with the ambient temperature value to generate the power generation prediction profile;

[0062] S3: Call the power generation prediction profile, calculate the volatility of the predicted PV power value, evaluate the impact of the volatility on the stability of the DC bus, and adjust the current control operation parameters to establish a set of current control parameters;

[0063] S4: Call the set of current control parameters and the output interaction characteristic parameters. According to the line impedance characteristics, evaluate the line voltage drop, and calculate the voltage adjustment parameters at the inverter output. According to the load power factor characteristics and combined with the active power, calculate the reactive power compensation amount, obtain the reactive current adjustment parameters, and generate an inverter control command; S5: Call the inverter control command, collect the temperatures at multiple positions of the inverter in real time, combine the real-time inverter load power and ambient temperature information, predict the temperature change trend of the inverter components, and adjust the allowable value of the inverter output power according to the rated safety temperature threshold to obtain the predictive power calibration coefficient;

[0064] The output interaction characteristic parameters are specifically line impedance parameters, load power factor parameters, current transient characteristic parameters, and disturbance response parameters. The power generation prediction profile includes irradiance distribution values, component attenuation coefficients, and temperature-related power generation prediction values. The set of current control parameters is specifically the power fluctuation threshold, bus voltage tolerance parameters, and current loop gain coefficients. The inverter control command specifically refers to the voltage compensation amount, reactive current component, and impedance compensation factor. The predictive power calibration coefficient includes the temperature safety margin, load power limit, and thermal inertia attenuation coefficient.

[0065] Apply a test signal to the inverter output, collect the voltage and current response data, analyze the amplitude ratio and phase difference in the disturbance frequency band, extract the line impedance characteristics, extract the waveform timing characteristics and analyze the load power factor characteristics by monitoring the dynamic change of the output current and performing transient analysis. The steps to obtain the output interaction characteristic parameters are specifically:

[0066] S101: Apply a test signal to the inverter output, collect the voltage and current response data, combine with band-pass filtering to isolate the test frequency components, calculate the voltage response amplitude, voltage response phase, current response amplitude, and current response phase at the test frequency, and establish a disturbance frequency response phasor;

[0067] Apply a test signal to the output terminal of the inverter. For example, for a 5-kW off-grid inverter operating in a 220-Volt, 50-Hertz grid environment, superimpose a sinusoidal voltage signal with a frequency of 500 Hertz (the fundamental frequency is 50 Hertz) and an amplitude of 11 Volts into its pulse-width modulation drive signal. The selection of this frequency can avoid the grid fundamental frequency and its main harmonic components, and at the same time be far from the interference of the inverter's own switching frequency (such as 20 kHz). Start the high-speed data acquisition system to synchronously record the instantaneous waveforms of the voltage and current at the output terminal of the inverter. Set the sampling frequency to 40 kHz and continuously collect for 0.2 seconds to obtain sufficient data points including multiple fundamental wave periods and test signal periods. For example, collect a time series of 8000 voltage sample points and 8000 current sample points. Apply digital band-pass filter processing to the collected original voltage and current time series data. The center frequency of this filter is set to the test signal frequency of 500 Hertz, and the bandwidth is set to 50 Hertz. For example, select a fourth-order Butterworth band-pass filter to filter out the fundamental wave, harmonics, and high-frequency noise, and obtain the filtered voltage sequence and current sequence containing information near 500 Hertz. Apply signal processing techniques to the filtered voltage sequence to extract the amplitude and phase information at the test frequency. Using the principle of digital lock-in amplification, multiply the filtered voltage sequence by the reference cosine signal with the same frequency and the same phase and the reference sine signal with the same frequency and orthogonal phase, and then extract the DC component through low-pass filtering to obtain the in-phase component and quadrature component of the voltage. Use the formula:

[0068]

[0069] Calculate the voltage response amplitude, where V amp is the voltage response amplitude at the test frequency, V I is the in-phase component of the voltage obtained by multiplying by the reference cosine signal and then low-pass filtering, V Q is the quadrature component of the voltage obtained by multiplying by the reference sine signal and then low-pass filtering. Assume that the obtained in-phase component of the voltage is 10.5 Volts and the quadrature component of the voltage is -2.6 Volts. Substitute the set values for calculation:

[0070]

[0071] Volts;

[0072] The calculation results show that at the 500-Hertz test frequency, the effective amplitude of the voltage response at the output terminal of the inverter is 10.817 Volts. Similarly, by calculating the arctangent values of the in-phase component and quadrature component of the voltage, the voltage response phase V phase = atan2(V Q , V I ). Perform the same processing flow on the filtered current sequence, and calculate the current response amplitude I ampAnd the current response phase I phase , combine the four calculated values of the voltage response amplitude, voltage response phase, current response amplitude, and current response phase to establish a disturbance frequency response phasor that characterizes the system response characteristics at this test frequency.

[0073] S102: Based on the disturbance frequency response phasor, calculate the impedance modulus value of the transmission line according to the voltage response amplitude and the current response amplitude, calculate the impedance phase angle according to the voltage response phase and the current response phase, and combine the impedance modulus value and the impedance phase angle to obtain the line equivalent resistance value and the line equivalent reactance value, and obtain the line impedance characteristic parameters;

[0074] Based on the disturbance frequency response phasor established in the previous step, this phasor includes the amplitude V of the voltage response at the test frequency (such as 500 Hz) amp and the phase V phase , as well as the amplitude I of the current response amp and the phase I phase . Calculate the impedance modulus value of the transmission line according to the voltage response amplitude and the current response amplitude at this test frequency. This modulus value reflects the proportional relationship between the voltage and the current amplitude and represents the total resistance of the line to the current at this frequency. The formula is:

[0075]

[0076] Calculate the impedance modulus value of the transmission line, where Z mag is the impedance modulus value of the transmission line at the test frequency, in ohms, V amp is the voltage response amplitude at the test frequency, in volts, I amp is the current response amplitude at the test frequency, in amperes. Assume that the voltage response amplitude calculated in paragraph 1 is 10.817 volts and the current response amplitude is 5.1 amperes, and substitute the set values for calculation:

[0077]

[0078] The calculation results show that at 500 Hz, the total impedance presented by the line from the inverter output to the load is approximately 2.121 ohms. Calculate the impedance phase angle according to the voltage response phase and the current response phase. This phase angle represents the angle by which the voltage phasor leads or lags the current phasor. The calculation method is the voltage response phase minus the current response phase, that is, Z angle =V phase -I phase, assuming the voltage response phase is 0.52 radians and the current response phase is 0.21 radians, then the impedance phase angle is 0.52 - 0.21 = 0.31 radians. Combining the calculated impedance modulus value (about 2.121 ohms) and the impedance phase angle (0.31 radians), using the complex number operation rules to decompose and obtain the equivalent resistance value and equivalent reactance value of the line. The equivalent resistance value is obtained by multiplying the impedance modulus value by the cosine value of the impedance phase angle, and the equivalent reactance value is obtained by multiplying the impedance modulus value by the sine value of the impedance phase angle, and obtain the line impedance characteristic parameters composed of the line equivalent resistance value and the line equivalent reactance value.

[0079] S103: Invoke the line impedance characteristic parameters, by monitoring the change rate of the inverter output current, record the transient waveform, extract the timing characteristics of the waveform, calculate the load power factor angle, obtain the load power factor characteristics, and generate output interaction characteristic parameters;

[0080] Invoke the line impedance characteristic parameters obtained in the previous step, utilize the information of the line equivalent resistance value and the line equivalent reactance value, continuously monitor the instantaneous value of the output current through the monitoring unit built in the inverter control system, and calculate its change rate. Set a current change rate threshold to determine whether a significant load transient change occurs. For example, the threshold is set to 10000 amperes per second. When the absolute change rate of the monitored current exceeds this threshold, trigger the transient waveform recording program. This program will automatically store the output voltage and output current waveform data of several power frequency cycles before and after the trigger moment (for example, 5 cycles before and after, that is, a total of 200 milliseconds). The sampling frequency is maintained at, for example, 40 kHz. Analyze the recorded transient voltage and current waveform data, with the focus on extracting the timing characteristics that can reflect the load power factor characteristics. For example, analyze the zero-crossing moments of the voltage fundamental component and the current fundamental component respectively, calculate the time difference between the two, and use the formula:

[0081] φ = ω·Δt zero ;

[0082] Calculate the load power factor angle, where φ is the load power factor angle, in radians, ω is the power grid fundamental angular frequency. For a 50 Hz system, ω = 2πf = 2π×50 = 100π radians per second, and Δt zero is the time difference between the zero-crossing of the voltage fundamental wave and the zero-crossing of the current fundamental wave, in seconds, which can be obtained by analyzing the recorded waveform data. Assume that through waveform analysis, in a certain load connection transient process, the zero-crossing of the voltage fundamental wave leads the zero-crossing of the current fundamental wave by 1.5 milliseconds, that is, the time difference is 0.0015 seconds. Substitute the set value into the calculation:

[0083] φ = (100π rad / s)×(0.0015 s) ≈ 0.471 rad;

[0084] The calculation results show that the power factor angle of this load is approximately 0.471 radians (about 27 degrees). Since the time difference is positive (voltage leading current), it indicates that the load exhibits an inductive lag characteristic. The main parameter for obtaining the power factor characteristic of the load is the power factor angle (0.471 radians), or its corresponding power factor (cos(0.471) ≈ 0.891). Integrate the calculated load power factor characteristic with the line impedance characteristic parameters (line equivalent resistance value and line equivalent reactance value) obtained in the previous step to jointly generate output interaction characteristic parameters for subsequent control steps to call.

[0085] The steps of calling the output interaction characteristic parameters, obtaining regional meteorological data, predicting the irradiance for multiple time periods, combining with a dirt sensor to evaluate the optical attenuation degree of the components in real time, and combining with the ambient temperature value to predict the power generation of the photovoltaic grid for multiple time periods and generating a power generation prediction profile are specifically as follows:

[0086] S201: Call the output interaction characteristic parameters, obtain regional meteorological data, extract irradiance prediction data and ambient temperature prediction data, and combine with time series interpolation to obtain a sequence of irradiance prediction values;

[0087] Obtain regional meteorological data by accessing the application programming interface (API) of a third-party meteorological service provider. For example, send an HTTP request to a specified URL using an authorization key. The request parameters include geographical coordinates (such as longitude 116.3 and latitude 39.9) and the required data types (hourly irradiance and ambient temperature predictions for the next 24 hours). The API returns data in JSON format. Parse the returned JSON data to extract the list of irradiance prediction data (for example, in watts per square meter, W / m 2 ) and the list of ambient temperature prediction data (for example, in degrees Celsius, °C). Assume that the obtained irradiance prediction data for the next 3 hours are [550, 620, 680] W / m 2 , and the corresponding ambient temperature prediction data is [25, 26, 27] °C. Combine with time series interpolation to process the obtained hourly data. For example, use the linear interpolation method to generate predicted values at intermediate times between adjacent hourly data points. Use the formula:

[0088]

[0089] Calculate the irradiance interpolation between two known prediction data points. Among them, G interp (t) is the interpolated irradiance prediction value at time t, G i is the known irradiance prediction value at time T i , G i+1 is the irradiance prediction value at the next known time T i+1 , and t is the time for which interpolation is required, satisfying Ti t ≤ t ≤ T i+1 。Suppose it is necessary to calculate the predicted irradiance value at 1 hour and 15 minutes (i.e., t = 1.25 hours). Given the predicted irradiance value G i at the 1st hour (T i = 1) is 550 W / m 2 , and the predicted irradiance value G i+1 at the 2nd hour (T i+1 = 2) is 620 W / m 2 , substitute the set values for calculation:

[0090]

[0091] The calculation results show that at the moment of 1 hour and 15 minutes, the predicted irradiance value is approximately 567.5 watts per square meter. The same method is applied to all time points that require interpolation and the environmental temperature prediction data. For example, interpolating every 15 minutes between the 1st hour and the 2nd hour will obtain a sequence of predicted irradiance values at 1:00, 1:15, 1:30, 1:45, and 2:00, such as [550, 567.5, 585, 602.5, 620] W / m 2 . Perform the same time series interpolation processing on all the obtained predicted irradiance data for future time periods (such as the next 24 hours) to obtain a sequence of predicted irradiance values with the required time resolution (such as 15 minutes).

[0092] S202: Based on the sequence of predicted irradiance values, call the soiling sensor. By analyzing the difference between the current sensor reading and the calibrated sensor reading in real time, calculate the optical attenuation ratio of the photovoltaic module surface to obtain the optical attenuation evaluation value;

[0093] Based on the sequence of predicted irradiance values, this sequence is the predicted irradiance values for multiple future time periods (such as the next 24 hours, with one point every 15 minutes) obtained after interpolation in the previous step, in units of watts per square meter. Call the soiling sensor to read the real-time output signal of the soiling sensor installed beside the photovoltaic array or on a representative module. By analyzing the difference between the current sensor reading and the calibrated sensor reading in real time, the calibrated sensor reading refers to the expected output current value corresponding to a certain standard irradiance (such as 1000 W / m 2 ) when the sensor surface is clean. This value is measured and stored during sensor installation and commissioning or regular maintenance. For example, the calibrated reading in the clean state is I sc,clean = 1.2 amperes. Read the output current I sc,dirty of the sensor in the current soiled state in real time. For example, the current reading is 0.9 amperes. Combine with the current actual irradiance for normalization comparison to obtain the current actual irradiance value G actual, two sensors installed side by side are used, one is kept clean (its reading is I sc,ref ), and one is exposed to natural dirt (its reading is I sc,dirty ). The attenuation is calculated by comparing the ratio of the real-time readings of the two, using the formula:

[0094]

[0095] Calculate the transmittance factor represented by the optical attenuation ratio on the surface of the photovoltaic module. Among them, η soiling is the transmittance factor after optical attenuation evaluation (unitless, value range 0 to 1), I sc,dirty is the real-time reading of the dirty sensor, and I sc,ref is the real-time reading of the reference sensor kept clean. Assume that the real-time reading of the dirty sensor is 0.9 amperes, and the real-time reading of the reference sensor kept clean beside it is 1.05 amperes. Substitute the set values into the calculation:

[0096]

[0097] The calculation results show that due to surface dirt, the effective irradiance received by the photovoltaic module is about 85.7% of that in the non-dirty state, that is, the optical attenuation causes about 14.3% of irradiance loss. This calculated value is the optical attenuation evaluation value (here is the transmittance factor 0.857). This value reflects the degree of decline in the ability of the photovoltaic module to receive solar irradiance due to factors such as dust and stains at the current moment, and the optical attenuation evaluation value is obtained.

[0098] S203: Call the optical attenuation evaluation value, combine the environmental temperature prediction data and the irradiance prediction data, calculate the predicted power generation of each photovoltaic module in multiple time periods, obtain the predicted data of the power generation of the power grid in multiple time periods, and establish a power generation prediction profile;

[0099] The formula for calculating the predicted power generation of each photovoltaic module in multiple time periods is:

[0100] P PV (k′) = η STC ·A·G(k′)·η·[1 + γ·(TCE(k′) - T STC )];

[0101] Calculate the predicted power generation value of a single photovoltaic module;

[0102] Among them, P PV (k′) represents the predicted power at time period k′, and η STCrepresents the component efficiency under standard test conditions, A represents the component area, G(k′) represents the interpolated irradiance prediction value for time period k′, η represents the optical attenuation evaluation value, γ represents the power temperature coefficient, TCE(k′) represents the estimated operating temperature of the photovoltaic cell for time period k′, and T STC represents the temperature under standard test conditions, and k′ represents the index number of the prediction time period;

[0103] Formula:

[0104] P PV (k′) = η STC ·A·G(k′)·η·[1 + γ·(TCE(k′) - T STC )];

[0105] Detailed explanation of the formula and the derivation process of the formula calculation:

[0106] The formula is used to calculate the power generation of a single photovoltaic component in a specific prediction time period k′, and the result is used to predict the power generation of the entire photovoltaic power station;

[0107] Parameter meanings and set values:

[0108] P PV (k′) represents the predicted power generation of a single photovoltaic component in the prediction time period k′, with the unit of watt W; η STC represents the conversion efficiency of the photovoltaic component under standard test conditions, with a set value of 0.20, that is, 20%; A represents the light-receiving area of a single photovoltaic component, with a set value of 1.7 square meters m 2 ;

[0109] G(k′) represents the predicted value of the plane irradiance in the prediction time period k′, with a set value of 800 watts per square meter W / m 2 ;

[0110] η represents the optical attenuation evaluation value, which reflects the influence of factors such as dust occlusion and component surface aging on light absorption, with a set value of 0.95;

[0111] γ represents the power temperature coefficient of the photovoltaic component, with a set value of -0.004 per °C;

[0112] TCE(k′) represents the estimated operating temperature of the photovoltaic cell in the prediction time period k′, set to 55 °C;

[0113] T STC represents the reference temperature of the battery under standard test conditions, set to 25 °C;

[0114] k′ represents the index number of the prediction time period;

[0115] Substitute the parameters into the formula for calculation:

[0116] TCE(k′) - T STC = 55 °C - 25 °C = 30 °C;

[0117] 1 + γ·(TCE(k′) - T STC ) = 1 + (-0.004 / °C)·(30 °C) = 1 - 0.12 = 0.88;

[0118] η STC ·A·G(k′)

[0119] ·η = 0.20·1.7 m 2 ·800 W / m 2 ·0.95 = 0.20·1.7·800·0.95 W = 258.4 W;

[0120] P PV (k′) = 258.4 W·0.88 = 227.392 W;

[0121] The result of 227.392 W indicates that at the prediction period k′, after considering the effects of irradiance, optical attenuation, and cell operating temperature, the predicted output power of a single photovoltaic module is approximately 227.39 watts.

[0122] The steps of calling the power generation prediction profile, calculating the volatility of the predicted photovoltaic power value, evaluating the impact of the volatility on the DC bus stability, and adjusting the current control operation parameters to establish the current control parameter set are as follows:

[0123] S301: Call the power generation prediction profile, calculate the volatility of the predicted photovoltaic power value, and generate a predicted power fluctuation index;

[0124] Call the power generation prediction profile, which is a time - series data containing the predicted output power values of the photovoltaic grid for multiple future periods (e.g., the next 24 hours, with a point every 15 minutes), such as the sequence P_pred = [141.98, 155.3, 168.1, 179.5,...] watts. Calculate the volatility of the predicted photovoltaic power value by analyzing the rate of change between the data points of this power prediction sequence to quantify the smoothness or severity of the future power changes. A commonly used method is to calculate the power change amount or change rate (also known as the ramp rate) between adjacent prediction periods, using the formula:

[0125]

[0126] Calculate the power change rate at the end of the k - th prediction period, where R(t k ) is the average power change rate between time t k and t k+1 , with the unit of watts per second or kilowatts per minute, and P pred (tk+1 ) is the predicted power value for the (k + 1)-th prediction period, P pred (t k ) is the predicted power value for the k-th prediction period, and ΔT is the time interval of the prediction period, such as 15 minutes or 900 seconds. Assume that in the power generation prediction profile, the predicted power at 1 hour and 15 minutes is 141.98 watts, and the predicted power at 1 hour and 30 minutes is 155.3 watts. The prediction period interval is 15 minutes (900 seconds). Substitute the set values into the calculation:

[0127]

[0128] The calculation results show that within the prediction interval from 1 hour and 15 minutes to 1 hour and 30 minutes, the photovoltaic power is expected to increase by approximately 0.0148 watts per second on average. Repeat this calculation for all adjacent periods of the entire power generation prediction profile to obtain a series of power change rate values. Further process these change rate values, such as calculating their maximum value, average value, or standard deviation, to form one or more comprehensive predicted power fluctuation indicators. For example, calculate the maximum positive change rate (power increase rate) and the maximum negative change rate (power decrease rate) predicted within the next 1 hour. These two values are used as predicted power fluctuation indicators to generate predicted power fluctuation indicators.

[0129] S302: Based on the predicted power fluctuation indicators, obtain the rated voltage value of the DC bus and the capacitance value of the bus capacitor, analyze the impact of photovoltaic power volatility on the stability of the DC bus, and obtain the risk level of bus voltage disturbance;

[0130] Based on the predicted power fluctuation indicators, for example, the maximum predicted power increase rate within the next 1 hour calculated in the previous step is 0.5 watts per second, and the maximum predicted power decrease rate is -0.8 watts per second. Obtain the rated voltage value of the DC bus and the capacitance value of the bus capacitor. These are design parameters of the inverter system and are usually stored in the system configuration. For example, the rated voltage V dc,nom of the DC bus is set to 400 volts, and the total capacitance C bus of the DC bus support capacitor is 2200 microfarads (μF). Analyze the impact of photovoltaic power volatility on the stability of the DC bus, that is, evaluate the degree to which the predicted rapid change in photovoltaic power (quantified by the fluctuation indicator) causes the DC bus voltage to deviate from its rated value. When the photovoltaic power suddenly increases, the excess energy is injected into the bus capacitor, causing the voltage to rise, and vice versa, causing the voltage to drop. The degree of influence is related to the power change rate and the size of the bus capacitor. Use the approximate relationship:

[0131]

[0132] Estimate an approximate measure of the maximum percentage deviation of the DC bus voltage caused by the maximum power fluctuation, where ΔVdc Represents the estimated value of the maximum relative deviation of the DC bus voltage caused by power fluctuation (unitless), ΔP max To predict the maximum absolute power change in the power fluctuation index, Δt resp is the time window for control system response or evaluation, C bus is the DC bus capacitance, V dc,nom is the rated voltage of the DC bus. Assuming the predicted maximum power change rate is 0.8 watts per second and the evaluation time window is 1 second, ΔP max ≈0.8W / s×1s=0.8W, the DC bus capacitance is 2200μF, i.e. 2.2×10 -3 Farad, rated voltage is 400 volts, substitute the set value to calculate:

[0133]

[0134] The calculation results show that the estimated relative deviation of the DC bus voltage caused by the expected maximum power fluctuation is approximately 0.000909, or approximately 0.09%. Based on this estimated voltage deviation degree or more complex stability analysis results, the risk level division rules are set. For example, a deviation estimate less than 0.5% is low risk, 0.5% to 2% is medium risk, and greater than 2% is high risk. In this example, 0.09% is much less than 0.5%, so it is judged as low risk, and the bus voltage disturbance risk level is obtained.

[0135] S303: adjusting the current control operation parameters, including the current loop proportional integral gain value and the disturbance observer parameter group, according to the bus voltage disturbance risk level, and establishing a current control parameter set;

[0136] According to the bus voltage disturbance risk level, that is, the risk level obtained by the previous link assessment, the current control operating parameters are adjusted. The process is carried out according to the preset rule base or lookup table. The rule base defines the current control parameter configuration that should be adopted under different risk levels. For example, a low risk level corresponds to a set of parameters that tend to be fast response and high efficiency, a medium risk corresponds to a set of parameters that balance response speed and stability, and a high risk corresponds to a set of conservative parameters that tend to be stability and robustness. The parameters that need to be adjusted usually include the gain value of the current loop proportional integral (PI) controller, such as the proportional gain K p And the integral gain K i , and the disturbance observer (DOB) or other related parameter groups of the feedforward control link, such as the bandwidth or filter coefficient of the DOB. For the case judged as low risk, a relatively aggressive PI gain value is selected to obtain a faster current tracking speed. Assume that the system has three sets of parameters preset: low risk group (K p =0.8,K i= 50, DOB bandwidth = 1000 rad / s), medium-risk group (K p = 0.6, K i = 30, DOB bandwidth = 800 rad / s), high-risk group (K p = 0.4, K i = 15, DOB bandwidth = 500 rad / s). Since the current risk level is low, the parameters of the low-risk group are selected. The proportional gain of the current loop is set to 0.8, the integral gain is set to 50, and the relevant parameters of the disturbance observer are adjusted to the set value corresponding to a bandwidth of 1000 rad / s. If the risk level is medium, the proportional gain will be adjusted to 0.6, the integral gain will be adjusted to 30, and the DOB parameters will be adjusted so that its bandwidth is 800 rad / s. All relevant control parameters corresponding to the selected risk level (including the proportional-integral gain value of the current loop, the disturbance observer parameter set, etc.) are integrated together to establish the current effective current control parameter set.

[0137] The steps of calling the current control parameter set and the output interaction characteristic parameters, evaluating the line voltage drop according to the line impedance characteristic, and calculating the inverter output terminal voltage adjustment parameter, calculating the reactive power compensation amount according to the load power factor characteristic and combining the active power, and obtaining the reactive current adjustment parameter to generate the inverter control command are specifically as follows:

[0138] S401: Call the current control parameter set and the output interaction characteristic parameters. According to the line impedance characteristic, combine the real-time measured value of the inverter output current to calculate the line voltage drop, and obtain the output terminal voltage compensation value according to the load-side target voltage reference value;

[0139] Call the currently effective current control parameter set and the previously obtained output interaction characteristic parameters, including the line equivalent resistance value and the line equivalent reactance value included in the line impedance characteristic. For example, the equivalent resistance is 0.1 ohm and the equivalent reactance is 0.2 ohm. According to the line impedance characteristic, combine the real-time measured value of the output current collected by the inverter controller (including its amplitude and phase) to calculate the voltage drop caused by the current transmitted on the line, and obtain the root mean square value I of the current at the inverter output terminal in real time rms and the phase angle φ relative to the reference voltage reference i , for example, the measured root mean square value of the current is 15 amperes and the phase angle is -0.3 radians (indicating that the current lags). Represent the current and impedance in complex form, calculate the line voltage drop vector, and further calculate the real part of the voltage drop vector, that is, the component of the voltage drop on the axis in phase with the reference voltage. Use the formula:

[0140] ΔV R = I rms ·R eq ·cos(φ i ) - Irms ·X eq ·sin(φ i );

[0141] Calculate the real component of the line voltage drop, where ΔV R is the real component of the line voltage drop, in volts, I rms is the root mean square value of the inverter output current, in amperes, R eq is the line equivalent resistance value, in ohms, φ i is the phase angle of the output current relative to the reference voltage, in radians, X eq is the line equivalent reactance value, in ohms. Assume that I rms is measured in real time as 15 A, φ i is -0.3 radians, and the line parameters are R eq is 0.1 ohm, X eq is 0.2 ohm. Substitute the set values for calculation:

[0142] ΔV R =(15 A)·(0.1 Ω)·cos(-0.3)-(15 A)·(0.2 Ω)·sin(-0.3)

[0143] ≈1.5·0.9553 - 3.0·(-0.2955)≈1.433 + 0.887≈2.32 volts;

[0144] The calculation result shows that the real part of the line voltage drop vector is approximately 2.32 volts. Similarly, the calculated imaginary component is 2.42 volts. Therefore, the line voltage drop vector is approximately 2.32 + j2.42 volts. According to the target voltage reference value expected to be maintained at the remote load side, for example, the target is a load terminal voltage of 220 volts and a phase of 0 degrees, add the calculated line voltage drop vector to the load target voltage vector. This calculated reference voltage vector at the inverter output terminal is the output terminal voltage compensation value.

[0145] S402: Call the output terminal voltage compensation value. According to the load power factor characteristic, obtain the measured value of the real-time active power output by the inverter. According to the load power factor characteristic and the measured value of the real-time active power, calculate the target reactive power compensation amount to obtain the target reactive power value;

[0146] Call the output terminal voltage compensation value calculated in the previous step, that is, the reference voltage vector that the inverter needs to generate volts, whose amplitude is approximately 222.33 volts. According to the load power factor characteristic obtained previously in the output interaction characteristic parameters, especially the load power factor angle φ load, for example, given that the load power factor angle is 0.471 radians (corresponding to a power factor of approximately 0.891 lagging), obtain the active power value P output by the inverter controller through real-time measurement out , for example, obtained by calculating the average value of the product of the instantaneous voltage and the instantaneous current over a power frequency cycle. The current measured value is 3000 watts. According to the known load power factor characteristics and the real-time measured active power value, calculate the reactive power consumed by the load, which is the target reactive power compensation amount that the inverter needs to provide. The formula is used:

[0147] Q load =P out ·tan(φ load );

[0148] Calculate the reactive power required by the load, where Q load is the reactive power consumed by the load, in units of volt-amperes reactive (VAr), P out is the measured value of the active power output by the inverter in real time, in units of watts (W), and φ load is the load power factor angle, in units of radians. Assuming that the real-time output active power is 3000 watts and the load power factor angle is 0.471 radians, substitute the set values for calculation:

[0149] Q load = 3000W·tan(0.471) ≈ 3000W·0.510 ≈ 1530VAr;

[0150] The calculation result shows that the current load needs to consume approximately 1530 volt-amperes reactive of reactive power. To maintain the normal operation of the load and meet its reactive power demand (usually provided by the inverter in an off-grid system), the inverter needs to generate this part of reactive power. Therefore, this calculated load reactive power value is set as the target reactive power value for inverter control, and the target reactive power value (approximately 1530VAr) is obtained.

[0151] S403: Call the target reactive power value, calculate the reactive current adjustment parameter, and obtain the inverter control command;

[0152] Call the target reactive power value obtained in the previous step, that is, Q target ≈ 1530VAr, and at the same time use the d-axis component of the reference voltage vector at the output end of the inverter calculated in S401, that is, V d,ref ≈ 222.33 volts, calculate the reactive current command component required to achieve this target reactive power, which is the core part of the reactive current adjustment parameter. The formula is used:

[0153]

[0154] Calculate the reactive current command component, where Iq,cmd is the q-axis (reactive) current command value, with the unit of ampere, Q target is the target reactive power value, with the unit of var, V d,ref is the d-axis reference voltage value (approximately the reference voltage amplitude), with the unit of volt. Assume the target reactive power value is 1530 VAr and the d-axis reference voltage value is 222.33 volts. Substitute the set values into the calculation:

[0155]

[0156] The calculation results show that in order to output a target reactive power of 1530 VAr, at the current reference voltage, it is necessary to generate a q-axis current component of approximately 6.88 amperes. At the same time, according to the active power required by the system, calculate the active current command component, I d,cmd ≈P target / V d,ref =3000 W / 222.33 V ≈ 13.49 amperes. Combine the calculated active current command I d,cmd and the reactive current command I q,cmd to form a reference current vector in the dq coordinate system amperes. Call the control law in the current control parameter set, compare the reference current vector with the actually measured current vector obtained through coordinate transformation, calculate the error, generate a modulation voltage command in the dq coordinate system through PI controller operation, and then through inverse coordinate transformation and space vector pulse width modulation (SVM) or sine pulse width modulation (SPWM), generate the gate drive signal for driving the power switch tubes of the inverter to obtain the inverter control command.

[0157] The steps of calling the inverter control command, collecting the temperatures at multiple positions of the inverter in real time, combining the real-time inverter load power and ambient temperature information, predicting the temperature change trend of the inverter components, and adjusting the allowable value of the inverter output power according to the rated safety temperature threshold to obtain the predictive power calibration coefficient are as follows:

[0158] S501: Call the inverter control command, use the temperature sensor to collect the temperature data at multiple positions of the inverter in real time, record the real-time measured value of the load power at the output end of the inverter, and establish a real-time operation state data set;

[0159] Invoke the inverter control instruction currently being executed. The instruction determines the switching state of the inverter and the current output power level. Utilize multiple temperature sensors installed at key positions inside the inverter, such as the radiator of the power module (IGBT), DC bus capacitor, filter inductor, control board, etc., to collect the temperature data of these positions in real time. The sensor type is a thermistor or an integrated temperature sensor chip. Read the temperature readings of each sensor through a data acquisition interface (such as an analog input channel or a digital bus). For example, the temperature of the IGBT radiator is collected as 55 degrees Celsius, the temperature of the capacitor is 48 degrees Celsius, and the temperature of the inductor is 52 degrees Celsius. At the same time, record the instantaneous values measured by the voltage and current sensors at the output end of the inverter, and calculate the real-time measured value P of the current load active power. load , for example, calculate that the current load power is 3500 watts, and obtain the current ambient temperature value T from the external ambient temperature sensor. amb , for example, the current ambient temperature is 28 degrees Celsius. Perform a weighted average of the temperatures collected at multiple key positions to obtain a representative temperature value that comprehensively reflects the current thermal state. Use the formula:

[0160]

[0161] Calculate the weighted average temperature, where T avg is the weighted average temperature of the key components of the inverter, N is the number of temperature sensors, T i is the real-time temperature reading of the i-th sensor, and w i is the weight coefficient of the i-th sensor, satisfying The weight coefficients are set according to the importance of different components to the overall thermal safety. Suppose there are 3 sensors, the IGBT radiator (T1 = 55 °C), the capacitor (T2 = 48 °C), and the inductor (T3 = 52 °C), and their importance weights are set as w1 = 0.5, w2 = 0.3, w3 = 0.2. Substitute the set values into the calculation:

[0162] T avg =(0.5×55)+(0.3×48)+(0.2×52)

[0163] =27.5 + 14.4 + 10.4 = 52.3 °C;

[0164] The calculation result shows that the comprehensive weighted average temperature of the current key components of the inverter is approximately 52.3 degrees Celsius. The temperature data (T1, T2,..., T N ) of each sensor collected in real time, the weighted average temperature (T avg ), the real-time load power (P load ), and the ambient temperature (T amb)Combine the above information and store it as structured data to establish a real-time operation status dataset that includes the current system thermal conditions and operating load.

[0165] S502: Based on the real-time operation status dataset, combine the real-time component temperature, inverter load power, and ambient temperature values to calculate the temperature change trend and obtain the predicted component temperature value;

[0166] The specific formula for calculating the temperature change trend is:

[0167]

[0168] Calculate the predicted component temperature value;

[0169] Among them, TY t+Δt represents the predicted temperature after Δt time in the future, TD t represents the component temperature measured at the current time t, TG t-Δtl represents the component temperature measured at the past time t - Δtl, Δtl represents the historical time interval used to calculate the change rate, Δt represents the predicted time step, t represents the index of the current time, t + Δt represents the index of the target prediction time, and t - Δtl represents the index of the known historical time;

[0170] Formula:

[0171]

[0172] Detailed explanation of the formula and the formula calculation derivation process:

[0173] The formula is used to calculate the predicted short-term temperature of the component in the future based on the recent temperature change trend, and the result is used to evaluate the potential thermal risk of the component and as the basis for subsequent power adjustment;

[0174] Parameter meaning and setting value:

[0175] TY t+Δt represents the predicted temperature at the future prediction time, in degrees Celsius °C;

[0176] TD t represents the component temperature measured at the current time, and set its reading to 55 °C;

[0177] TG t-Δtl represents the component temperature measured at the past historical time, and set the temperature record collected 180 seconds ago to 53.5 °C;

[0178] Δtl represents the retrospective historical time interval used to calculate the temperature change rate, and the set value is 180 seconds;

[0179] Δt represents the predicted time step, and the set value is 30 seconds;

[0180] Substitute the parameters into the formula for calculation:

[0181] TD t -TG t-Δtl = 55°C - 53.5°C = 1.5°C;

[0182]

[0183] TY t+Δt = TD t + 0.25°C = 55°C + 0.25°C = 55.25°C;

[0184] The result of 55.25°C indicates that based on the temperature change trend extrapolation over the past 180 seconds, it is predicted that the temperature of the component will reach 55.25 degrees Celsius after 30 seconds in the future. The predicted value will be used to provide a data basis for thermal management decisions.

[0185] S503: Call the predicted component temperature value, compare it with the rated safe operating temperature threshold, and adjust the allowable value of the inverter output power in real time to obtain the predictive power calibration coefficient;

[0186] Call the predicted component temperature value, that is, the expected temperature of each key component in the short future calculated in the previous step. For example, it is predicted that the temperature of the IGBT radiator will reach 68 degrees Celsius after 5 minutes. By comparing it with the pre-set rated safe operating temperature thresholds of each component, these thresholds are determined according to the device specification sheet and system design, representing the highest allowable temperature at which the component can operate safely for a long time. For example, the upper safety temperature limit threshold T limit,IGBT of the IGBT module is set to 85 degrees Celsius, and the threshold T limit,Cap of the capacitor is set to 70 degrees Celsius. For each key component, compare its predicted temperature value T pred with the corresponding safety threshold T limit , find the component with the smallest safety margin (i.e., the predicted temperature is closest to or exceeds the threshold), and adjust the allowable value of the inverter output power in real time. The adjustment logic usually sets a temperature point T derate_start (lower than T limit , for example, T derate_start of IGBT = 75°C) and a temperature point at which zero power output is reached (usually T limit ). When the predicted temperature enters the [T derate_start , T limit interval, linearly reduce the proportion of the allowable output power, using the formula:

[0187]

[0188] Calculate the predictive power calibration coefficient (i.e., derating coefficient), where α derate is the predictive power calibration coefficient, with a value range from 0 to 1 (1 means no derating, 0 means completely prohibiting output), T pred is the predicted temperature of the key component, T derate_start is the temperature threshold for starting derating, T limit is the upper threshold of the safe operating temperature. Assume the predicted IGBT temperature is 68°C, its starting derating temperature is 75°C, and the upper threshold is 85°C. Substitute the set values for calculation:

[0189]

[0190] The calculation results show that since the predicted temperature of 68°C is lower than the starting derating temperature of 75°C, the power calibration coefficient is 1, that is, no power limit is imposed. If the predicted temperature is 80°C, then:

[0191]

[0192] At this time, the calibration coefficient is 0.5, which means that the maximum output power allowed by the inverter will be reduced to 50% of its rated power. The minimum value among the respective calibration coefficients calculated based on the predicted temperatures of all key components is used as the final predictive power calibration coefficient and applied to the power control link of the inverter to obtain the predictive power calibration coefficient.

[0193] Please refer to Figure 2 , a photovoltaic off-grid inverter control system. The photovoltaic off-grid inverter control system is used to execute the above-mentioned photovoltaic off-grid inverter control method. The system includes:

[0194] The interaction identification module applies a test signal to the output terminal of the inverter, collects voltage and current response data, analyzes the amplitude ratio and phase difference in the disturbance frequency band, calculates the line impedance, combines the dynamic monitoring of the output current, extracts the waveform timing characteristics of the transient current, calculates the load power factor, and obtains the output interaction characteristic parameters;

[0195] The power generation prediction module calls the output interaction characteristic parameters, obtains the regional meteorological data, extracts the values of the dirt sensors and calculates the optical attenuation ratio of the photovoltaic modules. Combining the irradiance prediction data, temperature prediction data, and optical attenuation ratio, it predicts the power generation of the photovoltaic grid in multiple time periods and generates a power generation prediction profile;

[0196] The stability adjustment module loads the power generation prediction profile, calculates the volatility of the predicted photovoltaic power value, analyzes the influence degree of the power change rate on the bus voltage stability, and establishes a set of current control parameters;

[0197] The compensation control module retrieves the output interaction characteristic parameters and the current control parameter set, calculates the line voltage drop compensation amount based on the line impedance and the real-time output current, calculates the reactive power compensation demand based on the load power factor and the real-time active power, and generates an inverter control instruction.

[0198] The thermal management module receives the inverter control instruction, collects the temperature data at multiple positions of the inverter, the real-time load power data, and the ambient temperature data, predicts the temperature evolution trend, and combines the rated safety temperature threshold to adjust the allowable value of the inverter output power to obtain a predictive power calibration coefficient.

[0199] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more sets of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0200] It should be understood that the term "and / or" in this article is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context before and after.

[0201] In the present invention, "at least one" means one or more, and "a plurality of" means two or more. "At least one of the following" or a similar expression means any combination of these items, including any combination of single item(s) or plural item(s). For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or plural.

[0202] It should be understood that in various embodiments of the present invention, the magnitudes of the sequence numbers of the above - mentioned processes do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0203] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0204] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0205] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the couplings, direct couplings, or communication connections shown or discussed with each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0206] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0207] In addition, in each embodiment of the present invention, each functional unit can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0208] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0209] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, and all of them should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A photovoltaic off-grid inverter control method, characterized in that, The method includes: S1: Apply a test signal to the output terminal of the inverter, collect voltage and current response data, analyze the amplitude ratio and phase difference in the disturbance frequency band, extract the line impedance characteristics, monitor the dynamic change of the output current and conduct transient analysis, extract the waveform timing characteristics and analyze the load power factor characteristics, and obtain the output interaction characteristic parameters; S2: Call the output interaction characteristic parameters, obtain regional meteorological data, predict the irradiance in multiple periods, combine with the dirt sensor, evaluate the optical attenuation degree of the components in real time, combine with the environmental temperature value to predict the power generation of the photovoltaic grid in multiple periods, and generate a power generation prediction profile; S3: Call the power generation prediction profile, calculate the volatility of the photovoltaic power prediction value, evaluate the impact of the volatility on the DC bus stability, and adjust the current control operation parameters to establish a current control parameter set; S4: Call the current control parameter set and the output interaction characteristic parameters, evaluate the line voltage drop according to the line impedance characteristics, calculate the voltage adjustment parameter at the inverter output terminal, calculate the reactive power compensation amount according to the load power factor characteristics and combine with the active power, obtain the reactive current adjustment parameter, and generate an inverter control instruction.

2. The photovoltaic off-grid inverter control method according to claim 1, wherein, The output interaction characteristic parameters are specifically line impedance parameters, load power factor parameters, current transient characteristic parameters and disturbance response parameters. The power generation prediction profile includes irradiance distribution values, component attenuation coefficients, temperature-related power generation prediction values. The current control parameter set is specifically a power fluctuation threshold, a bus voltage tolerance parameter, and a current loop gain coefficient. The inverter control instruction specifically refers to a voltage compensation amount, a reactive current component, and an impedance compensation factor.

3. The photovoltaic off-grid inverter control method according to claim 1, characterized in that The steps of applying a test signal to the output terminal of the inverter, collecting voltage and current response data, analyzing the amplitude ratio and phase difference in the disturbance frequency band, extracting the line impedance characteristics, monitoring the dynamic change of the output current and conducting transient analysis, extracting the waveform timing characteristics and analyzing the load power factor characteristics, and obtaining the output interaction characteristic parameters are specifically as follows: S101: Apply a test signal to the output terminal of the inverter, collect voltage and current response data, combine with band-pass filtering to isolate the test frequency components, calculate the voltage response amplitude, voltage response phase, current response amplitude, and current response phase at the test frequency, and establish a disturbance frequency response phasor; S102: Based on the disturbance frequency response phasor, calculate the impedance modulus value of the transmission line according to the voltage response amplitude and the current response amplitude, calculate the impedance phase angle according to the voltage response phase and the current response phase, combine the impedance modulus value and the impedance phase angle, obtain the line equivalent resistance value and the line equivalent reactance value, and obtain the line impedance characteristic parameters; S103: Call the line impedance characteristic parameters, monitor the change rate of the inverter output current, record the transient waveform, extract the timing characteristics of the waveform, calculate the load power factor angle, obtain the load power factor characteristics, and generate the output interaction characteristic parameters.

4. The photovoltaic off-grid inverter control method according to claim 3, wherein, The steps of calling the output interaction characteristic parameters, obtaining regional meteorological data, predicting irradiance for multiple time periods, combining with a soiling sensor to evaluate the optical attenuation degree of components in real time, and predicting the power generation of a photovoltaic power grid for multiple time periods based on the ambient temperature value to generate a power generation prediction profile are as follows: S201: Call the output interaction characteristic parameters, obtain regional meteorological data, extract irradiance prediction data and ambient temperature prediction data, and obtain a sequence of irradiance prediction values by combining time series interpolation; S202: Based on the sequence of irradiance prediction values, call the soiling sensor, calculate the optical attenuation ratio of the surface of the photovoltaic module by analyzing the difference between the current sensor reading and the calibrated sensor reading in real time, and obtain the optical attenuation evaluation value; S203: Call the optical attenuation evaluation value, combine the ambient temperature prediction data and the irradiance prediction data, calculate the predicted power generation of each photovoltaic module for multiple time periods, obtain the predicted data of the power generation of the power grid for multiple time periods, and establish a power generation prediction profile.

5. The photovoltaic off-grid inverter control method according to claim 4, characterized in that, The formula for calculating the predicted power generation of each photovoltaic module for multiple time periods is: P PV (k′) = η STC ·A·G(k′)·η·[1 + γ·(TCE(k′) - T STC )]; Calculate the predicted power generation value of a single photovoltaic module; Among them, P PV (k′) represents the predicted power for time period k′, η STC represents the module efficiency under standard test conditions, A represents the module area, G(k′) represents the interpolated irradiance prediction value for time period k′, η represents the optical attenuation evaluation value, γ represents the power temperature coefficient, TCE(k′) represents the estimated operating temperature of the photovoltaic cell for time period k′, T STC represents the temperature under standard test conditions, and k′ represents the index number of the prediction time period.

6. The photovoltaic off-grid inverter control method according to claim 4, wherein The steps of calling the power generation prediction profile, calculating the volatility of the photovoltaic power prediction value, evaluating the impact of the volatility on the stability of the DC bus, and adjusting the current control operation parameters to establish a set of current control parameters are as follows: S301: Call the power generation prediction profile, calculate the volatility of the photovoltaic power prediction value, and generate a predicted power fluctuation index; S302: Based on the predicted power fluctuation index, obtain the rated voltage value of the DC bus and the capacitance value parameter of the bus capacitor, analyze the impact of the photovoltaic power volatility on the stability of the DC bus, and obtain the risk level of bus voltage disturbance; S303: According to the risk level of bus voltage disturbance, adjust the current control operation parameters, including the proportional-integral gain value of the current loop and the parameter group of the disturbance observer, to establish a set of current control parameters.

7. The photovoltaic off-grid inverter control method according to claim 6, wherein The steps of calling the set of current control parameters and the output interaction characteristic parameters, evaluating the line voltage drop according to the line impedance characteristic, calculating the voltage adjustment parameter at the output end of the inverter, calculating the reactive power compensation amount according to the load power factor characteristic and combining with the active power, and obtaining the reactive current adjustment parameter to generate an inverter control instruction are as follows: S401: Call the set of current control parameters and the output interaction characteristic parameters, calculate the line voltage drop according to the line impedance characteristic in combination with the measured value of the real-time output current of the inverter, and obtain the output voltage compensation value according to the target voltage reference value on the load side; S402: Call the output voltage compensation value, obtain the measured value of the real-time output active power of the inverter according to the load power factor characteristic, and calculate the target reactive power compensation amount according to the load power factor characteristic and the measured value of the real-time active power to obtain the target reactive power value; S403: Call the target reactive power value, calculate the reactive current adjustment parameter, and obtain the inverter control instruction.

8. The photovoltaic off-grid inverter control method according to claim 1, characterized in that, The method further includes: S5: Invoke the inverter control instruction, collect the temperatures at multiple positions of the inverter in real time, combine the real-time inverter load power and ambient temperature information, predict the temperature change trend of the inverter components, and adjust the allowable value of the inverter output power according to the rated safety temperature threshold to obtain the predictive power calibration coefficient; The predictive power calibration coefficient includes a temperature safety margin, a load power limit, and a thermal inertia attenuation coefficient.

9. The photovoltaic off-grid inverter control method according to claim 8, characterized in that The steps of invoking the inverter control instruction, collecting the temperatures at multiple positions of the inverter in real time, combining the real-time inverter load power and ambient temperature information, predicting the temperature change trend of the inverter components, and adjusting the allowable value of the inverter output power according to the rated safety temperature threshold to obtain the predictive power calibration coefficient are specifically as follows: S501: Invoke the inverter control instruction, use a temperature sensor to collect the temperature data at multiple positions of the inverter in real time, record the real-time measured value of the load power at the inverter output end, and establish a real-time operation state data set; S502: Based on the real-time operation state data set, combine the real-time component temperature, inverter load power, and ambient temperature values, calculate the change trend of the temperature, and obtain the predicted component temperature value; The specific formula for calculating the change trend of the temperature is: Calculate the predicted component temperature value; Among them, TY t+Δt represents the predicted temperature after a future time interval of Δt, TD t represents the component temperature measured at the current time t, TG t-Δtl represents the component temperature measured at the past time t - Δtl, where Δtl represents the historical time interval used for calculating the rate of change, Δt represents the predicted time step, t represents the index of the current time, t + Δt represents the index of the target prediction time, and t - Δtl represents the index of the known historical time; S503: Invoke the predicted component temperature value, compare it with the rated safe operating temperature threshold in real time, adjust the allowable value of the inverter output power, and obtain the predictive power calibration coefficient.

10. A photovoltaic off-grid inverter control system, characterized in that, The system is used to implement the photovoltaic off-grid inverter control method according to any one of claims 1-9. The system includes: The interaction identification module applies a test signal to the inverter output end, collects voltage and current response data, analyzes the amplitude ratio and phase difference in the disturbance frequency band, calculates the line impedance, combines the dynamic monitoring of the output current, extracts the waveform timing characteristics of the transient current, calculates the load power factor, and obtains the output interaction characteristic parameters; The power generation prediction module invokes the output interaction characteristic parameters, obtains the regional meteorological data, extracts the values of the dirt sensors and calculates the optical attenuation ratio of the photovoltaic modules, combines the irradiance prediction data, temperature prediction data, and optical attenuation ratio, predicts the power generation of the photovoltaic grid at multiple time periods, and generates a power generation prediction profile; The stability adjustment module loads the power generation prediction profile, calculates the volatility of the predicted photovoltaic power value, analyzes the influence degree of the power change rate on the bus voltage stability, and establishes a current control parameter set; The compensation control module retrieves the output interaction characteristic parameters and the current control parameter set, calculates the line voltage drop compensation amount according to the line impedance and the real-time output current, calculates the reactive power compensation demand according to the load power factor and the real-time active power, and generates an inverter control instruction; The thermal management module receives the inverter control instruction, collects the temperature data, real-time load power data, and ambient temperature data at multiple positions of the inverter, predicts the temperature evolution trend, combines the rated safety temperature threshold, and adjusts the allowable value of the inverter output power to obtain the predictive power calibration coefficient.

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