Method for determining input capacitance of photovoltaic system based on photovoltaic cell model

Abstract

The invention relates to a method for determining input capacitance of a photovoltaic system based on a photovoltaic cell model, which belongs to the technical field of photovoltaic power generation and comprises the following steps of: 1, establishing a mathematical model of a photovoltaic cell and an interface converter of the photovoltaic system, and determining a maximum power point tracking control strategy of the converter; 2, calculating according to the photovoltaic cell model and the converter model to obtain a relational expression between the input capacitance of the photovoltaic system and the sampling period and the adjustment time of the maximum power point tracking control strategy; 3, determining constraint conditions of the sampling period and the adjustment time of the maximum power point tracking control strategy in the relational expression in the step 2; 4, calculating to obtain a parameter value range of the input capacitance according to the relational expression in the step 2 and the constraint condition in the step 3; and 5, selecting the input capacitance for the photovoltaic system according to the input capacitance parameter range. The input capacitance of the photovoltaic interface converter is selected according to the distribution rule of the sampling period of the maximum power point tracking control strategy, the power density of the photovoltaic system can be improved, and stable and economical operation of the system is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic power generation, and particularly relates to a method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model. Background Art

[0002] In existing photovoltaic power generation systems, due to the non-linear operating characteristics of photovoltaic cells, a photovoltaic interface converter needs to be shunted with a capacitor to smooth voltage fluctuations, thereby improving system stability. However, if the shunted capacitor is too large, the system power density will be reduced. Therefore, selecting a suitable input capacitance for a photovoltaic power generation system has become a key issue, which is directly related to the efficiency, stability, and economy of the system. At present, the input capacitance of photovoltaic power generation systems is often selected based on the experience of relevant technicians, and the capacitance values selected by different technicians vary, resulting in different power densities of photovoltaic systems and further causing fluctuations in photovoltaic systems. Summary of the Invention

[0003] The object of the present invention is to provide a method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model to improve the power density and stability of the photovoltaic system, aiming at the problems existing in the prior art.

[0004] The technical solution is as follows:

[0005] A method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model includes the following steps:

[0006] Step 1: Establish a mathematical model of a photovoltaic cell and an interface converter of a photovoltaic system, and determine the maximum power point tracking (MPPT) control strategy of the converter;

[0007] Step 2: Calculate the relationship between the input capacitance of the photovoltaic system and the sampling period and regulation time of the maximum power point tracking control strategy according to the photovoltaic cell model and the converter model;

[0008] Step 3: Determine the constraint conditions of the sampling period and regulation time of the maximum power point tracking control strategy in the relationship of Step 2;

[0009] Step 4: Calculate the parameter value range of the input capacitance according to the relationship in Step 2 and the constraint conditions in Step 3;

[0010] Step 5: Select the input capacitance for the photovoltaic system according to the input capacitance parameter range.

[0011] Further, the photovoltaic system includes a photovoltaic cell, an input capacitor, an interface converter, an inverter, and an information acquisition module; wherein the input capacitor is connected in parallel with the photovoltaic cell, the positive and negative input terminals of the interface converter are connected to the positive and negative terminals of the photovoltaic cell, the output terminal of the interface converter is connected to the input terminal of the inverter, and the output terminal of the inverter is connected to the power grid.

[0012] Furthermore, the information acquisition module respectively monitors and acquires the output voltage and current signals of the photovoltaic cell, and the voltage and current signals of the load or the power grid, and generates a control signal for the interface converter and a control signal for the inverter therefrom.

[0013] Further, in step 1, the interface converter is a DC-DC boost converter or buck converter, and the small-signal transfer functions of the buck converter and the boost converter are: In the formula, G ud (s) is the transfer function from the converter duty cycle to the voltage, μ is the amplitude of the output voltage, ω n is the natural frequency, ξ is the damping ratio, and the mathematical model of the buck circuit is: r PV is the photovoltaic equivalent resistance, L is the circuit inductance, C in is the input capacitor, R is the load resistance; the mathematical model of the boost circuit is:

[0014] Further, the maximum power point tracking control strategy in step 1 includes: adopting one of the constant voltage method that realizes maximum power point tracking by keeping the output voltage of the photovoltaic system constant at the maximum power point voltage, the conductance increment method that realizes maximum power point tracking by making the incremental derivative between the voltage and current at the maximum power point of the photovoltaic system zero, and the perturbation observation method that realizes photovoltaic maximum power tracking by periodically perturbing the operating point of the photovoltaic system to reach the maximum power point.

[0015] Further, in step 2, the photovoltaic cell model is a single-diode model or a double-diode model, and the single-diode model is: Wherein I sh is the photocurrent, I D is the reverse saturation current of the diode, q is the electron charge constant, A is the diode quality factor, K is the Boltzmann constant, R sh is the equivalent bypass resistance of the photovoltaic array, R s is the equivalent series resistance of the photovoltaic array; the double-diode model is: Wherein I sh is the photocurrent, I D1 and I D2 are respectively the reverse saturation currents of diodes D1 and D2.

[0016] Further, the input capacitor C of the buck circuit in step 2 in and the maximum power point tracking sampling period T a and the adjustment time T s have the following relationship: where i PV is the output current of the photovoltaic cell, u PV is the output voltage of the photovoltaic cell, r PV is the equivalent resistance of the photovoltaic, L is the inductor of the converter, T a is the sampling period, T s is the adjustment time; the input capacitor C of the boost circuit in and the maximum power point tracking sampling period T a and the adjustment time T s have the following relationship: T a ≤T s +ln(0.03)·2r PV C i n , r PV is calculated through the photovoltaic cell model.

[0017] Further, the sampling period of the maximum power point tracking control strategy in step 3 is not less than the switching period of the converter switch tube, and the adjustment time needs to be determined according to the system performance requirements and application scenarios. The adjustment time range requirement of the maximum power point tracking control strategy for the grid-connected system is 100 ms - 1 s, the adjustment time requirement of the maximum power point tracking control strategy for the off-grid system is 500 ms - 3 s, and the adjustment time of the maximum power point tracking control strategy for the high-dynamic scenario is less than 100 ms.

[0018] Beneficial effects:

[0019] 1) The present invention combines the internal characteristics of the photovoltaic cell, selects the size of the input capacitor of the photovoltaic interface converter through the distribution law of the MPPT sampling period, can improve the power density of the photovoltaic system, and realize the stable and economic operation of the system. Description of the drawings

[0020] Figure 1 is the schematic diagram of the method flow of the present invention;

[0021] Figure 2 is the schematic diagram of the overall structure of the photovoltaic power generation system in the present invention;

[0022] Figure 3 is the schematic diagram of the photovoltaic single-diode circuit of the present invention;

[0023] Figure 4 is the photovoltaic parallel capacitor C in = 100 μF, the MPPT sampling period T aPhotovoltaic output power waveform at 0.1 ms;

[0024] Figure 5 is the photovoltaic parallel capacitor C in = 100 μF, MPPT sampling period T a Photovoltaic power waveform at 1 ms;

[0025] Figure 6 is the photovoltaic parallel capacitor C in = 1000 μF, MPPT sampling period T a Photovoltaic power waveform at 0.1 ms. Specific implementation manner

[0026] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments:

[0027] As Figure 1 shown, a method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model includes the following steps:

[0028] Step 1: Establish a mathematical model of the photovoltaic cell and the interface converter of the photovoltaic system. As Figure 2 shown, the photovoltaic system includes a photovoltaic cell, an input capacitance, an interface converter, an inverter, and an information acquisition module; wherein the input capacitance is connected in parallel with the photovoltaic cell, the positive and negative input terminals of the interface converter are connected to the positive and negative terminals of the photovoltaic cell, the output terminal of the interface converter is connected to the input terminal of the inverter, the output terminal of the inverter is connected to the power grid, and the information acquisition module monitors and acquires the output voltage and current signals of the photovoltaic cell, the voltage and current signals of the load or the power grid, and generates the control signal of the interface converter and the control signal of the inverter therefrom. The interface converter is a boost converter or a buck converter for converting DC to DC. The small-signal transfer functions of the buck converter and the boost converter are: In the formula, G ud (s) is the transfer function from the duty ratio of the converter to the voltage, μ is the amplitude of the output voltage, ω n is the natural frequency, ξ is the damping ratio, and the mathematical model of the buck circuit is: r PV is the photovoltaic equivalent resistance, L is the inductance of the circuit, C in is the input capacitance, and R is the load resistance; the mathematical model of the boost circuit is: The photovoltaic cell model is a single-diode model or a double-diode model. As Figure 3 shown, the single-diode model is: Wherein I sh is the photocurrent, I Dis the reverse saturation current of the diode, q is the electron charge constant, A is the diode quality factor, K is the Boltzmann constant, and R sh is the equivalent bypass resistance of the photovoltaic array, and R s is the equivalent series resistance of the photovoltaic array; the double-diode model is: where I sh is the photocurrent, and I D1 and I D2 are the reverse saturation currents of diodes D1 and D2 respectively; determine the control strategy for the maximum power point tracking (MPPT) of the converter, including: adopting the constant voltage method that realizes the maximum power point tracking by keeping the output voltage of the photovoltaic system constant at the maximum power point voltage, the incremental conductance method that realizes the maximum power point tracking by making the incremental derivative between the voltage and current at the maximum power point of the photovoltaic system zero, and the perturbation and observation method that realizes the maximum power point tracking of the photovoltaic system by periodically perturbing the operating point of the photovoltaic system to reach the maximum power point, choosing one of the three methods;

[0029] Step 2: Calculate the relationship between the input capacitance of the photovoltaic system, the sampling period of the maximum power point tracking control strategy, and the adjustment time according to the photovoltaic cell model and the converter model. For the buck circuit, the relationship between the input capacitance C in and the sampling period T a of the maximum power point tracking and the adjustment time T s is: where i PV is the output current of the photovoltaic cell, u PV is the output voltage of the photovoltaic cell, r PV is the equivalent resistance of the photovoltaic, L is the inductor of the converter, T a is the sampling period, and T s is the adjustment time; for the boost circuit, the relationship between the input capacitance C in and the sampling period T a of the maximum power point tracking and the adjustment time T s is:,, T a ≤T s +ln(0.03)·2r PV C i n , r PV is calculated through the photovoltaic cell model;

[0030] Step 3: Determine the constraint conditions for the sampling period and regulation time of the maximum power point tracking control strategy in the relationship formula of Step 2. The sampling period of the maximum power point tracking control strategy shall not be lower than the switching period of the converter switching device, and the regulation time shall be determined according to the system performance requirements and application scenarios. The requirement for the regulation time range of the maximum power point tracking control strategy for the grid-connected system is 100 ms - 1 s, the requirement for the regulation time of the maximum power point tracking control strategy for the off-grid system is 500 ms - 3 s, and the regulation time of the maximum power point tracking control strategy for the high-dynamic scenario is less than 100 ms;

[0031] Step 4: Calculate the parameter value range of the input capacitor according to the relationship formula in Step 2 and the constraint conditions in Step 3;

[0032] Step 5: Select the input capacitor for the photovoltaic system according to the input capacitor parameter range.

[0033] Embodiment: In the simulation model, the photovoltaic part consists of a group of 11 series-connected photovoltaic cells, which are composed of 5 groups in parallel. The open-circuit voltage of a single photovoltaic cell is 59.1 V, the maximum power point voltage is 47.9 V, and the maximum power is 214.592 W.

[0034] The converter is a Boost converter, with an inductor of 6 mH and a switching frequency of 10 kHz. The DC bus capacitor is 5 mF. The Boost converter adopts the MPPT control method based on the conductance increment method.

[0035] As Figures 4-6 shown is the output power waveform p PV during the operation of photovoltaic MPPT at the simulation time t = 1 s. Among them, Figure 4 is the photovoltaic parallel capacitor C in = 100 μF, and the output power waveform of the photovoltaic when the MPPT sampling period T a = 0.1 ms; Figure 5 is for C in = 100 μF, T a = 1 ms, the photovoltaic power waveform, Figure 6 is for C in = 1000 μF, T a = 0.1 ms, the photovoltaic power waveform. It can be seen from the simulation waveform diagram that increasing the sampling period will lead to a longer regulation time. By comparing Figure 4 and Figure 5 it can be seen that when the sampling periods are the same, the larger the capacitor, the longer the time for the system to reach the steady state; by comparing Figure 5 and Figure 6 it can be seen that when the capacitor value is fixed, the larger the sampling period, the longer the time for the system to reach the steady state. To optimize the system power density, when selecting a smaller parallel capacitor value, a shorter steady-state time of the system can be achieved by choosing a smaller sampling period.

[0036] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principle and spirit of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model, comprising the following steps: Step 1: Establish the mathematical model of photovoltaic cells and interface converters of the photovoltaic system and determine the maximum power point tracking control strategy of the converter; Step 2: Calculate the relationship between the photovoltaic system input capacitance and the maximum power point tracking control strategy sampling period and adjustment time based on the photovoltaic cell model and the converter model; Step 3: Determine the constraints of the maximum power point tracking control strategy sampling period and adjustment time in the relationship in step 2; Step 4: Calculate the parameter value range of the input capacitor according to the relationship in step 2 and the constraint conditions in step 3; Step 5: Select the input capacitor for the photovoltaic system based on the input capacitor parameter range.

2. A method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model according to claim 1, characterized in that: The photovoltaic system includes a photovoltaic cell, an input capacitor, an interface converter, an inverter and an information acquisition module; wherein the input capacitor is connected in parallel with the photovoltaic cell, the positive and negative input ends of the interface converter are connected to the positive and negative ends of the photovoltaic cell, the output end of the interface converter is connected to the input end of the inverter, and the output end of the inverter is connected to the power grid.

3. A method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model as claimed in claim 2, characterized in that: The information acquisition module monitors and acquires the output voltage and current signals of the photovoltaic cell, the voltage and current signals of the load or the power grid, and generates control signals of the interface converter and the inverter accordingly.

4. A method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model according to claim 1, characterized in that: In step 1, the interface converter is a DC-to-DC Boost converter or a Buck converter, and the small signal transfer function of the Buck converter and the Boost converter is: Where G ud (s) is the transfer function from the converter duty cycle to voltage, μ is the output voltage amplitude, ω n is the natural frequency, ξ is the damping ratio, and the mathematical model of the Buck circuit is: r PV is the photovoltaic equivalent resistance, L is the circuit inductance, C in is the input capacitor, R is the load resistor; the mathematical model of the Boost circuit is:

5. The method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model according to claim 1, characterized in that: The maximum power point tracking control strategy in step 1 includes: a constant voltage method for achieving maximum power point tracking by keeping the output voltage of the photovoltaic system constant at the maximum power point voltage; a conductance increment method for achieving maximum power point tracking by using the incremental derivative between the voltage and current of the photovoltaic system at the maximum power point to be zero; and a perturbation observation method for achieving photovoltaic maximum power tracking by periodically perturbing the operating point of the photovoltaic system to reach the maximum power point.

6. A method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model according to claim 1, characterized in that: The photovoltaic cell model in step 1 is a single diode model or a double diode model. The single diode model is: Among them I sh is the photocurrent, I D is the reverse saturation current of the diode, q is the electron charge constant, A is the diode quality factor, K is the Boltzmann constant, R sh is the equivalent bypass resistance of the photovoltaic array, R s is the equivalent series resistance of the photovoltaic array; the double diode model is: Among them I sh is the photocurrent, I D1 and I D2 are the reverse saturation currents of diodes D1 and D2 respectively.

7. A method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model according to claim 1, characterized in that: The buck circuit input capacitor C in step 2 is in The maximum power point tracking sampling period T a and adjustment time T s The relationship is: where i PV is the photovoltaic cell output current, u PV is the photovoltaic cell output voltage, r PV is the photovoltaic equivalent resistance, L is the converter inductance, T a is the sampling period, T s is the adjustment time; the boost circuit input capacitor C in The maximum power point tracking sampling period T a and adjustment time T s The relationship is: a ≤T s +ln(0.03)·2r PV C i n , r PV Calculated using a photovoltaic cell model.

8. The method for determining the input capacitance of a photovoltaic system based on a photovoltaic cell model according to claim 1, characterized in that: The sampling period of the maximum power point tracking control strategy in step 3 is not less than the switching period of the converter switch tube. The adjustment time needs to be determined according to the system performance requirements and application scenarios. The maximum power point tracking control strategy adjustment time range of the grid-connected system is required to be 100ms-1s, and the maximum power point tracking control strategy adjustment time range of the off-grid system is required to be 500ms-3s. The maximum power point tracking control strategy adjustment time in high dynamic scenarios is less than 100ms.

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