The most important thing in the implementation of MPPT technology is to find a suitable MPPT control algorithm. MPPT implementation methods include Constant Voltage Tracking (CVT), Perturbation and Observation Method (P&O), and Incremental Conductance Method (Inc method) and fuzzy logic control method.
1) Constant pressure tracking mode.
The I-U curve of the battery under solar radiation is shown in Figure 1.
According to the principle shown in Figure 1, when the temperature is constant, the maximum power points of solar panels under different light intensities are almost on both sides of the same vertical line, which makes it possible to approximate the maximum power line as a voltage U is a constant vertical line, which makes the solar panel work at a certain fixed voltage. The vertical line A’B’ in Figure 1 is the constant voltage tracking line, and the dashed line AE is the maximum tracking point line. The constant voltage tracking method is a tracking method that approximates the maximum power.
The constant voltage tracking method has a certain power loss. Especially when the temperature changes, the open circuit voltage of the solar panel changes accordingly, and the voltage of the constant voltage tracking method is a constant value, so the tracking efficiency is not high.
2) Disturbance observation method.
The perturbation observation method is to increase or decrease the working voltage of the solar panel by comparing the output power of the solar panel with the last time to achieve MPPT. Suppose that at a certain time t, the output power of the solar panel is P1, and the processor output signal makes the working voltage of the solar panel increase by △U. After a period of △t, solar energy is detected at time t2 (t2=t1+△t) The output power of the battery panel is P2. If △P (△P=P2-P1) is positive, the working voltage of the solar panel should be increased by △U until △P=0; if △P is negative, the working voltage of the solar panel should be reduced △U, until △P=0.
For △U, an appropriate value should be selected. If the value of △U is too large, the output of the solar panel will fluctuate around the maximum power point; if the value of △U is too small, although the tracking accuracy can be ensured, it will take more time, which is effective when the maximum power point changes frequently. Will get worse.
3) Incremental conductance method.
The conductance increment method compares the conductance increment of the solar panel with the instantaneous conductance to output a control signal. According to the P-U curve of the solar cell in Figure 2, the first derivative is used to find the extreme value, that is, the total derivative of P=UI can be obtained.
Divide both sides by dU at the same time, we can get
Let dP/dU=0, we can get
When the above formula is satisfied, the solar panel works at the maximum power point.
Assuming that the working point of the current photovoltaic array is on the left side of the maximum power point, at this time dP/dU>0, that is, dI/dU>-I/U, indicating that the reference voltage should change in the direction of increase.
Assuming that the working point of the current photovoltaic array is on the right side of the maximum power point, at this time, dP/dU<0, that is, dI/dU<-I/U, indicating that the reference voltage should change in a decreasing direction.
The conductance increment method has precise control and relatively fast response speed, which is suitable for occasions where atmospheric conditions change rapidly. However, the requirements for hardware, especially the accuracy of the sensor, are relatively high, and the response speed of each part of the system is required to be relatively fast, so the hardware cost of the entire system will be relatively high.
In terms of theory, the theoretical expression of the conductance increment method is impeccable. However, when the accuracy of the sensor is limited, the processor will have errors in calculating the conductance increment and instantaneous conductance of the solar panel, so it will be inevitable Inaccurate tracking occurs.
4) Fuzzy logic control mode.
To achieve accurate tracking of the maximum power point of a photovoltaic array, there are many factors that need to be considered, such as changes in the temperature of the photovoltaic array, changes in load conditions, and the nonlinear characteristics of the output characteristics of the photovoltaic array. For such a non-linear system, using fuzzy logic control (Fuzzy logic control) method to control, can obtain a more ideal effect.
Fuzzy logic control is used in photovoltaic power generation system to realize MPPT control, which can be easily executed by DSP. The design of the controller mainly includes the following aspects:
① Determine the input variables and output variables of the fuzzy controller.
② Summarize and summarize the control rules of the fuzzy controller.
③Determine the method of fuzzification and de-fuzzification.
④Choose the domain of discourse and determine the relevant parameters.
The use of fuzzy logic control method for photovoltaic system MPPT control has good dynamic characteristics and accuracy, and has a broader application prospect in the field of photovoltaic grid-connected power generation. However, the MPPT controller of photovoltaic power generation system based on fuzzy logic control method usually passes DSP chip implementation is not suitable for small independent photovoltaic power generation systems due to the high cost.