Maximum power point tracking device for a photovoltaic system using an adjustable step size approach under varying atmospheric conditions

Abstract

The present invention relates to a maximum power point tracking (MPPT) device for photovoltaic systems. The device comprises a measurement unit for measuring the input voltage and the current of the photovoltaic panel, a control unit comprising an Adjustable Step Size Theta Approach (ASSTA) MPPT algorithm for extracting the generated optimal power. The ASSTA algorithm uses a high disturbance value when the system is far from the maximum power point and a low disturbance value when the system is close to the MPP, thereby enabling efficient and fast tracking of the MPP even under complicated static and dynamic weather conditions. In addition, the ASSTA MPPT algorithm has better tracking performance, response time, speed convergence, and power loss compared to MPPT methods, thereby significantly improving tracking efficiency and power generation in photovoltaic systems.

Description

[0001] Maximum power point tracking device for photovoltaic system using adjustable angle step approach under varying atmospheric conditions

[0002] Description of the invention

[0003] Technical field

[0004] This invention relates to a novel technique for maximum power point (MPP) tracking in photovoltaic generation. More specifically, this approach is designed for use in stand-alone photovoltaic generation systems.

[0005] State of the art

[0006] In a stand-alone photovoltaic (PV) system, the DC output of the PV panel or array is directly connected to a DC load. However, the voltage-current characteristics of the PV panel are nonlinear, meaning that the power-voltage curves have only one operating point. This point is called the maximum power point (MPP), and it changes depending on weather conditions such as irradiance and temperature. To make the most of the available power from the PV module or array, a tracking mechanism is required to locate the MPP. This mechanism is called the Maximum Power Point Tracker (MPPT).

[0007] The MPPT mechanism adjusts the pulse width modulation (PWM) signal to control the DC-DC converter, which is located between the PV array and the DC load. The converter's purpose is to match the impedance of the electrical load to the MPP of the PV array, as shown in Figure 1.

[0008] There are several techniques to ensure the MPPT function, including classical algorithms such as: perturbation and observation (P&O) and incremental conductance (INC) techniques. Or recent algorithms [1,2, 3, 4, 5]; However, all these approaches have some limitations when the solar photovoltaic energy conversion system is exposed to variable weather conditions. These limitations may include low MPP tracking efficiency, as well as ripple and drift issues.

[0009] The present invention aims to provide a new approach called ASSTA (Adjustable Step Size Theta Approach) to address the challenges posed by existing maximum power point tracking (MPPT) methods in stand-alone photovoltaic generation systems. These challenges include complex control systems, high implementation costs, oscillations around the MPP during steady-state operation, and long convergence times to reach the actual MPP. The ASSTA approach effectively addresses these issues and is capable of performing well under various harsh atmospheric conditions.

[0010] Figure 1 illustrates the proposed stand-alone photovoltaic system which comprises a solar panel 01, a DC-DC converter 02, a load 03, a control unit 04 and voltage 05 and current 06 sensors. The control unit 04 is equipped with a microcontroller (PIC16X, Arduino...) 07 which implements the MPPT algorithm and a pulse width modulation (PWM) controller 08. The solar panel 01 is tracked to find its maximum power point, which is then rectified by the DC-DC converter 02 and applied to a load 03. The load can be a battery for a satellite, a street light, an electric heating system, an electric motor or a combination of these.

[0011] The proposed MPPT method is based on observing the variation of angle 9 and its derivative with respect to voltage V, as illustrated in Figure 2. This figure shows that at any point (Vx, P(Vx)) of the power characteristic as a function of voltage (PV), the tangent line forms an angle 9 with the V axis. This angle 9 is the arc tangent of the variation of the PV panel power with respect to the variation of the PV panel voltage. This angle 9 can be expressed mathematically as follows:

[0012] 9 = arctan(— — — )

[0013] Furthermore, its derivative with respect to the PV panel voltage can be estimated by:

[0014] In this context, based on the observation of the geometry of angle 0 in Figure 2, it is evident that angle 0 is positive to the left of the MPP, negative to the right of the MPP, and zero at the MPP. Therefore, it can be described mathematically as follows:

[0015] (0=0 at MPP 0>0 to the left of the MPP (.0 <0 to the right of the MPP

[0016] Additionally, the derivative of angle 0 with respect to the PV panel voltage (dO / dVpv) can be geometrically observed in Figure 2. When examining the dO / dVpv curve, it is important to note that this value is generally zero outside the MPP region and greater than zero within the MPP region. In order to better locate the MPP region, in addition to the condition on angle 0, a Z value (0.02 in this study) is chosen as a threshold parameter, as shown in Figure 2, to enable accurate MPP localization.

[0017] In order to improve the tracking speed, accuracy and dynamic performance under fast varying conditions, and overcome the drawbacks of several conventional MPPT algorithms, such as long convergence time and oscillations around the steady-state MPP, a new adjustable step value M is proposed, as shown in Figure 3. Accordingly, depending on the working conditions, the proposed approach needs to find an appropriate trade-off between dynamics and steady-state fluctuations.

[0018] The proposed new adjustable step value is automatically updated according to the variation of the photovoltaic power dPpv, the voltage dVpv and the current dlpv, as shown in the following equation:

[0019] M= | (dP pv + dV pv x dl pv ) |

[0020] Thus, in the new Adjustable Step Size Theta Approach (ASSTA), the duty cycle becomes dynamic. The ASSTA algorithm uses a high disturbance value when the system is far from the MPP (to the left and right of the MPP), a very low disturbance value close to the MPP, and a zero disturbance value at the MPP.

[0021] Therefore, the duty cycle d(k) at time k can be adjusted as follows: d(k)=d(kl )± SFxM

[0022] The SF term (0.005 in this case) is a scaling factor that is manually adjusted to find the best compromise between response time and minimizing steady-state fluctuations.

[0023] Figure 4 presents the flowchart of the proposed ASSTA approach for maximum power point tracking (MPPT). At the beginning of the algorithm, in step E001, the ASSTA method measures the actual value of the input voltage Vpv(k) and the current Ipv(k). Then, in step E002, the values ​​of the generated power Ppv(k), the difference of the input voltage dVpv, the current dlpv, the power dPpv, the adjustable step AT, the angle θ and its derivative dd / dVpv are calculated.

[0024] After the measurement and calculation steps, a first decision regarding the size of the adjustable step M is made in step E003. When there is no change in the weather conditions, M takes a value lower than the value C (a constant that takes the value 0.003 in this study) and the new duty cycle d(k+l) in step E006 remains constant by receiving the value of the previous duty cycle d(k). If this is not the case, in step E004, a test is performed on the condition of the angle 0 and its derivative dd / dVpv. If the angle 0 is equal to zero and dd / dVpv is greater than the value Z (a constant that takes the value 0.02 in this study), the duty cycle remains unchanged (E006). Then, if these two tests are not verified, the algorithm goes to step E005, which is dedicated to verifying the sign of angle 9.If the angle θ is positive, i.e., the PV panel operating point is located to the left of the MPP, the algorithm decrements the duty cycle in step E007 to reach the MPP. Otherwise, if the PV panel operating point is located to the right of the MPP, the algorithm increments the duty cycle in step E008. Finally, in step E009, after storing the values ​​of voltage V, current I, and power P, as well as the duty cycle d of time k+1, the next duty cycle command d(k+1), which was decided in steps E006, E007, and E008, is returned. Subsequently, the DC / DC converter is controlled by this duty cycle through the pulse width modulation (PWM) signal generator to extract the optimal power from the photovoltaic generation.From the comparative results in Table 1, it has been shown that the proposed ASSTA has better performance compared to other methods in terms of response time, convergence speed and capturing the actual PPM. Indeed, the ASSTA algorithm is the fastest to locate the exact PPM without fluctuations in a minimum time under the abrupt change of insolation. In this regard, more power can be harvested, resulting in a better tracking efficiency (99.55% in dynamic conditions). On the other hand, other MPPT techniques have many drawbacks; for example, in the case of INC and P&O methods, although they manage to track the PPM, they have a longer response time with significant oscillations around the PPM.Regarding the PSO method, despite its robustness, it is evident that it is not able to track the PPM in case of sudden changes in insolation, in addition, its tracking time is the longest.

[0025] Industrial applications:

[0026] Given the significant performance of the proposed ASSTA technique, its scope of applicability is so vast for photovoltaic generation systems. We can cite as examples:

[0027] • Electrical power systems.

[0028] • Emergency power supplies.

[0029] • Solar pump irrigation systems

[0030] • Electrification of isolated sites.

[0031] • Autonomous security systems.

[0032] • Smart grids

[0033] • Electric vehicles.

[0034] • Robotics

[0035] • Satellite References

[0036] [1] Soon TK, Mekhilef S. A fast-converging MPPT technique for photovoltaic system under fast-varying solar irradiation and load resistance. IEEE Trans Ind Informatics 2015;l l. https: / / d01.0rg / l 0.1109 / TH2014.2378231.

[0037] [2] Wang SC, Pai HY, Chen GJ, Liu YH. A Fast and Efficient Maximum Power Tracking Combining Simplified State Estimation with Adaptive Perturb and Observe. IEEE Access 2020;8. https: / / doi.org / 10.1109 / ACCESS.2020.3019197.

[0038] [3] Gopahanal Manjunath M, Vyjayanthi C, Modi CN. Adaptive step zise based drift-free P&O algorithm with power optimiser and load protection for maximum power extraction from PV panels in stand-alone applications. IET Renew Power Gener 2021; 15. https: / / doi.org / 10.1049 / rpg2.12105.

[0039] [4] EP2551986B1

[0040] [5] EP2722725B1

Claims

Claims 1. A device for maximum power point tracking (MPPT) in stand-alone photovoltaic systems, comprising: • a measuring unit configured to measure the actual values ​​of the input voltage (Vpv(k)) and current (Ipvfk)) of the photovoltaic panel; • a control unit comprising an MPPT algorithm with adjustable step Theta (AS S TA), configured to calculate the generated power (Ppv(k) the input voltage difference (dVpv), the current (dlpv), the power (dPpv), the adjustable step (AT), the angle (0 and its derivative (dO / dVpv); • a decision unit configured to adjust the step size (AT) based on the measured values ​​and to make a decision regarding the next control action based on the value of the angle (0 and its derivative (d6 / dVpv) with respect to predetermined threshold values; • a modulation unit configured to generate a pulse width modulation (PWM) signal based on the control action decision made by the decision unit.

2. The device according to claim 1, wherein the step size (AT) is dynamically adjusted according to the measured values ​​of the input power (Vpv(k) of the voltage (Vpv k)) and the current (Ipv(k) of the photovoltaic panel.

3. The device according to claim 1 or 2, wherein the MPPT ASSTA algorithm is configured to use a high disturbance value when the system is far from the maximum power point (MPP) and a low disturbance value when the system is close to the MPP, and a zero disturbance value at the MPP.

4. The device according to any one of the preceding claims, wherein the MPPT ASSTA algorithm comprises a scale factor (Scale Factor: SF) which is manually regulated to obtain the best compromise between response time and minimization of steady-state fluctuations.

5. A device according to claim 1, characterized in that it can track the true MPP with high accuracy in case of sudden changes in insolation and temperature. The device according to any one of the preceding claims, wherein the ASSTA MPPT approach has better performance compared to conventional MPPT methods in terms of tracking efficiency, response time, speed convergence and power loss, particularly under static and dynamic climatic conditions.

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