Photovoltaic grid-connected synchronization method and system

Abstract

The present invention belongs to the field of photovoltaics, and provides a photovoltaic grid-connected synchronization method and system, including: constructing a photovoltaic grid-connected synchronization model, and performing initial inverter control parameter estimation on the model based on historical data; collecting the output voltage of the photovoltaic system and the grid voltage calculation error in real time through sensors; updating model parameters online; calculating the inverter duty cycle based on the latest model parameters; and adjusting the photovoltaic system output voltage based on the inverter duty cycle to make it track the grid voltage. The above scheme can accurately and timely track the grid voltage.

Description

Technical Field

[0001] The present invention belongs to the field of photovoltaics, and in particular relates to a photovoltaic grid-connected synchronization method and system. Background Art

[0002] Photovoltaic grid-connected synchronization refers to synchronizing the power generated by the photovoltaic power generation system with the power of the grid so that the power of the photovoltaic system can be integrated into the grid. The synchronization process includes matching voltage, frequency and phase, so that the AC power output by the photovoltaic system can be seamlessly combined with the power of the grid.

[0003] Photovoltaic power generation is intermittent and volatile. Grid connection can ensure the continuity and stability of power supply. Photovoltaic grid connection enables better matching of power generation and consumption, improves energy efficiency and reduces waste. Grid connection can transmit excess photovoltaic power to the power grid, reducing the load pressure on the power grid, especially during peak power demand periods. Photovoltaic grid connection is the key to achieving large-scale renewable energy utilization, helping to reduce fossil fuel use and reduce carbon emissions.

[0004] However, there are many challenges in connecting photovoltaic power to the grid. The grid voltage and frequency will fluctuate due to factors such as load changes and power generation changes. These fluctuations will affect the output quality of the photovoltaic system and even cause grid connection failure, requiring the inverter to respond quickly and adjust the output. Summary of the invention

[0005] In order to solve the problems in the prior art, the present invention provides a photovoltaic grid-connected synchronization method, characterized in that the method comprises the following steps:

[0006] Step 1: construct a photovoltaic grid-connected synchronization model, and calculate initial inverter control parameters based on historical data and the photovoltaic grid-connected synchronization model;

[0007] Step 2: collecting the input voltage of the inverter and the grid voltage in real time through a sensor; and calculating the error between the input voltage of the inverter and the grid voltage;

[0008] Step 3: Substitute the initial inverter control parameters into the photovoltaic grid-connected synchronization model, update the control parameters of the photovoltaic grid-connected synchronization model online according to the real-time collected inverter input voltage and grid voltage, and calculate the system gain of the photovoltaic grid-connected synchronization model;

[0009] Step 4: Calculating an inverter duty cycle according to the system gain and the error;

[0010] Step 5: Adjust the inverter output voltage according to the inverter duty cycle so that it tracks the grid voltage.

[0011] Another aspect of the present invention also discloses a photovoltaic grid-connected synchronization system, comprising the following modules:

[0012] An initialization module is used to construct a photovoltaic grid-connected synchronization model and calculate initial inverter control parameters based on historical data and the photovoltaic grid-connected synchronization model;

[0013] A first calculation module collects the input voltage of the inverter and the grid voltage in real time through a sensor; and calculates the error between the input voltage of the inverter and the grid voltage;

[0014] An online update module, which substitutes the initial inverter control parameters into the photovoltaic grid-connected synchronization model, updates the parameters of the photovoltaic grid-connected synchronization model online according to the real-time collected inverter input voltage and grid voltage, and calculates the system gain of the photovoltaic grid-connected synchronization model;

[0015] A second calculation module, calculating an inverter duty cycle according to the system gain and the error;

[0016] The regulating module is used to adjust the output voltage of the inverter according to the inverter duty cycle so that it tracks the grid voltage.

[0017] The present invention can produce the following beneficial effects through the above technical solution:

[0018] The system parameters can be adjusted according to real-time data to improve the system's adaptability under different working conditions. By continuously updating the parameter estimates, the accuracy of the system model is improved, thereby improving the control accuracy.

[0019] Dynamic error compensation can significantly reduce the deviation between the system output and the target value and improve control accuracy. The error compensation mechanism can effectively suppress oscillation and instability in the system and enhance system stability.

[0020] Converting the control input into a duty cycle and applying it to the inverter enables precise regulation of the output voltage. The system can flexibly adjust the inverter's operating state to adapt to different operating conditions based on the control input calculated in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0023] Below, the invention is preferably described in conjunction with the accompanying drawings and specific implementation methods.

[0024] This embodiment solves the above problem through the following steps:

[0025] In one embodiment, reference Figure 1 , the present invention provides a photovoltaic grid-connected synchronization method.

[0026] In order to achieve grid-connected synchronization, the output voltage of the inverter is controlled to be synchronized with the grid voltage. The control input can be achieved by adjusting the duty cycle of the inverter. In order to determine the duty cycle parameters, this embodiment adopts the following steps:

[0027] Step 1: construct a photovoltaic grid-connected synchronization model, and calculate initial inverter control parameters based on historical data and the photovoltaic grid-connected synchronization model.

[0028] When the system starts, use historical data or initial experimental data for preliminary parameter estimation. The purpose of using historical data or initial experimental data for preliminary parameter estimation when the system starts is to provide a reasonable initial parameter setting for the adaptive controller. It can ensure that the system has a good control foundation at startup and avoid large control errors or instability in the initial stage of the system. Through initial parameter estimation, the online adjustment time after system startup can be reduced and the system can reach a stable state faster.

[0029] The main components of the photovoltaic grid-connected system include photovoltaic arrays, DC-DC converters, DC-AC inverters and power grids. The following are the specific steps to build the system model.

[0030] The dynamic model of the photovoltaic grid-connected system can be expressed as:

[0031] DC-DC Converter:

[0032]

[0033] in

[0034] L dc It is the inductance value in the DC-DC converter, used to smooth the current waveform;

[0035] I dc is the current flowing through the inductor;

[0036] V pv is the output voltage of the PV array;

[0037] V dc is the DC voltage output by the DC-DC converter

[0038] DC-AC Inverter:

[0039]

[0040] in:

[0041] C dc is the capacitance value at the input of the DC-AC inverter, used to smooth the voltage waveform;

[0042] V dc is the inverter input voltage (DC voltage);

[0043] I inv is the current flowing into the inverter.

[0044] Considering the inverter as a state model, the above equation is converted into a state space model, defining state variables, input variables, and output variables:

[0045] State variables:

[0046]

[0047] Input variables:

[0048] u pv (t) = V pv (t)

[0049] Output variables:

[0050] y dc (t) = V dc (t)

[0051] The state-space model has the form:

[0052]

[0053] y dc (t) = Cx(t)

[0054] in

[0055]

[0056] Based on historical operation data, extract the input and output data of the system from the database or log, and construct regression vectors and output data:

[0057]

[0058] y dc (t) = V dc (t)

[0059] According to the least squares method (LS), we have:

[0060]

[0061] Φ dc is the matrix containing all regression vectors

[0062]

[0063] Y dc is the output data vector:

[0064]

[0065] Through the above steps, the historical data is subjected to least squares regression, and the parameters are estimated by minimizing the sum of squared errors. The initial parameter estimate can be obtained based on the state at the previous moment. At the same time, we get the initial (first iteration) V dc and I dc For initial setup of the adaptive controller.

[0066] It should be noted that in the photovoltaic grid-connected system, the parameters of the photovoltaic system and the power grid are detected at preset intervals (usually in milliseconds), so all processes are performed iteratively. In the above steps, X(t) represents the state at time t (or time slot t), and X(t-1) represents the state at the previous moment (or previous time slot) of time t. The other variables are defined similarly.

[0067] Step 2: The input voltage of the inverter and the grid voltage are collected in real time by sensors; and the error between the input voltage of the inverter and the grid voltage is calculated.

[0068] Sensors are installed at key locations of the photovoltaic grid-connected system to collect the required voltage signals in real time.

[0069] A voltage sensor is installed at the input end of the inverter to measure the input voltage V ac (t)

[0070] A voltage sensor is installed in the power grid to measure the power grid voltage V grid (t)

[0071] Use a data acquisition system for real-time data acquisition, ensuring that the sampling frequency is high enough to capture the dynamic changes of the system.

[0072] According to the dynamic characteristics and control requirements of the system, select an appropriate sampling frequency. For example, for a typical photovoltaic grid-connected system, the sampling frequency can be set to 1kHz or higher.

[0073] Through real-time acquisition of V grid (t) and V ac Data, calculation system error

[0074] e ac (t) = V ac (t)-V grid (t)

[0075] where e ac (t) is the error, V grid (t) is the grid voltage.

[0076] Step 3: Substitute the initial inverter control parameters into the photovoltaic grid-connected synchronization model, update the parameters of the photovoltaic grid-connected synchronization model online according to the real-time collected inverter input voltage and grid voltage, and calculate the system gain of the photovoltaic grid-connected synchronization model.

[0077] Based on the preliminary parameters determined in step 1

[0078]

[0079] Initialize a covariance matrix

[0080] P(0)=αI

[0081] Where α is a large positive number (the specific value is not limited), and I is the unit matrix.

[0082] The subsequent operations of this step are iterative processes, which need to be performed in every time slot, and the parameters of the model are dynamically updated in each time slot to achieve the purpose of tracking the grid voltage.

[0083] The output voltage of the system (that is, the input voltage of the inverter) V is collected in real time through the sensor dc (t) and other related variables to construct the regression vector φ(t).

[0084] Regression vector

[0085]

[0086] Gain calculation is performed at each step

[0087]

[0088] Update the error at the same time

[0089] e ac (t) = V ac (t)-V grid (t)

[0090] Update the model state parameters to facilitate the calculation of subsequent steps

[0091]

[0092] At the same time, the covariance matrix is ​​updated to facilitate the calculation of subsequent steps

[0093]

[0094] This step can be iterated to update The updated parameters can be used for calculations in the next iteration.

[0095] By applying this step in real time, it is ensured that the controller can accurately respond to changes in the system state and improve the stability and control accuracy of the photovoltaic grid-connected system.

[0096] Step 4: Calculate the inverter duty cycle according to the system gain and the error.

[0097] Design a sliding surface for the error in step 2

[0098] s(t)=e ac (t)+λ∫e ac (t)dt

[0099] Where λ is the sliding mode control rate, which determines the response speed of the system and can be set through experimental tests according to the response requirements.

[0100] Control input u inv (t): The control signal calculated by the sliding mode control law is used to adjust the output of the inverter

[0101] u inv (t) = -K(t) sgn(s(t))

[0102] where sgn(s(t)) is the sign function, defined as:

[0103]

[0104] Control input u inv (t) is converted into the duty cycle of the inverter for practical application in inverter control

[0105]

[0106] Step 5: Adjust the inverter output voltage according to the inverter duty cycle so that it tracks the grid voltage.

[0107] The calculated control input is applied to the inverter to adjust the PV system output voltage and make it track the grid voltage.

[0108] Inverters usually use pulse width modulation (PWM) technology to adjust the output voltage. The duty cycle D(t) determines the duty cycle of the PWM signal, thereby controlling the output voltage of the inverter to achieve the purpose of tracking the grid voltage.

[0109] On the other hand, the present invention also provides a photovoltaic grid-connected synchronization system, comprising:

[0110] An initialization module is used to construct a photovoltaic grid-connected synchronization model and calculate initial inverter control parameters based on historical data and the photovoltaic grid-connected synchronization model;

[0111] A first calculation module collects the input voltage of the inverter and the grid voltage in real time through a sensor; and calculates the error between the input voltage of the inverter and the grid voltage;

[0112] An online update module, which substitutes the initial inverter control parameters into the photovoltaic grid-connected synchronization model, updates the parameters of the photovoltaic grid-connected synchronization model online according to the real-time collected inverter input voltage and grid voltage, and calculates the system gain of the photovoltaic grid-connected synchronization model;

[0113] A second calculation module, calculating an inverter duty cycle according to the system gain and the error;

[0114] The regulating module is used to adjust the output voltage of the inverter according to the inverter duty cycle so that it tracks the grid voltage.

[0115] Furthermore, the specific implementation methods of the photovoltaic grid-connected synchronization system described above are the same as a photovoltaic grid-connected synchronization method, and all further technical solutions in a photovoltaic grid-connected synchronization method are completely introduced into a photovoltaic grid-connected synchronization system.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

[0117] The present invention does not particularly specify the structure of some modules, which shall be subject to the contents recorded in the prior art. The prior art mentioned in the above background technology section and the specific embodiment section of the present invention can be used as part of the present invention to understand the meaning of some technical features or parameters. The scope of protection of the present invention shall be subject to the contents actually recorded in the claims.

Claims

1. A photovoltaic grid-connected synchronization method, characterized in that: The method comprises the following steps: Step 1: construct a photovoltaic grid-connected synchronization model, and calculate initial inverter control parameters based on historical data and the photovoltaic grid-connected synchronization model; Step 2: collecting the input voltage of the inverter and the grid voltage in real time through a sensor; and calculating the error between the input voltage of the inverter and the grid voltage; Step 3: Substitute the initial inverter control parameters into the photovoltaic grid-connected synchronization model, update the control parameters of the photovoltaic grid-connected synchronization model online according to the real-time collected inverter input voltage and grid voltage, and calculate the system gain of the photovoltaic grid-connected synchronization model; Step 4: Calculating an inverter duty cycle according to the system gain and the error; Step 5: Adjust the output voltage of the inverter according to the inverter duty cycle so that it tracks the grid voltage; The step 1 comprises: Converting the photovoltaic grid-connected synchronization model into a state space model; Construct regression vectors and output data based on historical operation data; The least squares parameters are calculated by minimizing the squared error; Calculating initial inverter control parameters according to the least squares parameters; The step 2 comprises: Installing a voltage sensor at the input end of the inverter to measure the input voltage of the inverter; Installing a voltage sensor on the power grid to measure the voltage of the power grid; Calculating the error between the input voltage of the inverter and the grid voltage; The step 3 comprises: Initializing the photovoltaic grid-connected synchronization model according to the initial inverter control parameters determined in step 1 and an initial covariance matrix; In each iteration, the real-time collected input voltage of the inverter and the grid voltage are substituted into the photovoltaic grid-connected synchronization model, the system gain of the photovoltaic grid-connected synchronization model is calculated, and the photovoltaic grid-connected synchronization model parameters and the covariance matrix are updated; The step 4 comprises: According to the error in step 2, a sliding surface is set; Calculating a control signal according to the sliding surface and the system gain; The control signal is converted into a duty cycle.

2. A photovoltaic grid-connected synchronization system, characterized in that: The system includes the following modules: An initialization module is used to construct a photovoltaic grid-connected synchronization model and calculate initial inverter control parameters based on historical data and the photovoltaic grid-connected synchronization model; A first calculation module collects the input voltage of the inverter and the grid voltage in real time through a sensor; and calculates the error between the input voltage of the inverter and the grid voltage; An online update module, which substitutes the initial inverter control parameters into the photovoltaic grid-connected synchronization model, updates the parameters of the photovoltaic grid-connected synchronization model online according to the real-time collected inverter input voltage and grid voltage, and calculates the system gain of the photovoltaic grid-connected synchronization model; A second calculation module, calculating an inverter duty cycle according to the system gain and the error; A regulating module, used to adjust the output voltage of the inverter according to the inverter duty cycle so that it tracks the grid voltage; The initialization module is implemented using the following steps: Converting the photovoltaic grid-connected synchronization model into a state space model; Construct regression vectors and output data based on historical operation data; The least squares parameters are calculated by minimizing the squared error; Calculating initial inverter control parameters according to the least squares parameters; The first calculation module comprises the following steps: Installing a voltage sensor at the input end of the inverter to measure the input voltage of the inverter; Installing a voltage sensor on the power grid to measure the voltage of the power grid; Calculating the error between the input voltage of the inverter and the grid voltage; The online update module includes the following steps: Initializing the photovoltaic grid-connected synchronization model according to the initial inverter control parameters determined by the initialization module and an initial covariance matrix; In each iteration, the real-time collected input voltage of the inverter and the grid voltage are substituted into the photovoltaic grid-connected synchronization model, the system gain of the photovoltaic grid-connected synchronization model is calculated, and the photovoltaic grid-connected synchronization model parameters and the covariance matrix are updated; The second calculation module includes: For the error in the first calculation module, setting a sliding surface; Calculating a control signal according to the sliding surface and the system gain; The control signal is converted into a duty cycle.

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