scholarly journals Drift Free Variable Step Size Perturb and Observe MPPT Algorithm for Photovoltaic Systems Under Rapidly Increasing Insolation

2018 ◽  
Vol 22 (1) ◽  
pp. 19 ◽  
Author(s):  
Deepthi Pilakkat ◽  
S. Kanthalakshmi
Keyword(s):  
Maximum Power ◽  
Variable Step Size ◽  
Maximum Output ◽  
Solar Pv ◽  
Step Size ◽  
Maximum Power Point ◽  
Power Extraction ◽  
Perturb And Observe ◽  
Variable Step ◽  
Power Point

The characteristic of a Photovoltaic (PV) panel is most affected by the incident solar insolation temperature, shading, and array configuration. Maximum power point tracking (MPPT) algorithms have an important role in harvesting maximum power from the solar PV arrays. Among the various MPPT methods Perturb and Observe (P&O) algorithm is the simple and efficient one. However, there will be a drift problem in case of increase in insolation. This drift will be more under rapid increase in insolation. To improve the speed of tracking the Maximum Power Point (MPP), a variable step size P&O (VSSPO) is developed. The drift problem will be more in the case of VSSPO as it will have a larger step size for an increase in insolation. In this paper, the maximum output power extraction from Solar PV under rapidly increasing insolation conditions by a drift free P&O (DFP&O) as well as drift free VSSPO (DFVSSPO) method is presented.

Implementation in Arduino of MPPT Using Variable Step Size P&O Algorithm in PV Installations

2017 ◽  
Vol 8 (1) ◽  
pp. 434 ◽  
Author(s):  
Mustapha Elyaqouti ◽  
Safa Hakim ◽  
Sadik Farhat ◽  
Lahoussine Bouhouch ◽  
Ahmed Ihlal
Keyword(s):  
Electric Energy ◽  
Maximum Power ◽  
Variable Step Size ◽  
Step Size ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Perturb And Observe ◽  
Variable Step ◽  
Power Point

In order to maximize the electric energy production of a photovoltaic generator (PVG), the maximum power point tracking (MPPT) methods are usually used in photovoltaic systems. The principle of these techniques is to operate the PVG to the maximum power point (MPP), which depends on the environmental factors, such as solar irradiance and ambient temperature, ensuring the optimal power transfer between PVG and load. In this paper, we present the implementation of two digital MPPT commands using the Arduino Mega type. The two proposed MPPT controls are based on the algorithm of perturb and observe (P&O), the first one with fixed perturbation step and the second one with two perturbations step varying with some conditions. The experimental results show that the P&O algorithm with variable step perturbation gives good results compared to the P&O algorithm with fixed perturbation step in terms of the time response and the oscillations around the MPP.

scholarly journals Recursive Bit Assignment With Neural Reference Adaptive Step (RNA) MPPT Algorithm for Photoviolatic System

2021 ◽  
Author(s):  
Eman Hegazy ◽  
Mona Shokair ◽  
waleed saad
Keyword(s):  
Neural Network ◽  
Boost Converter ◽  
Maximum Power ◽  
Duty Ratio ◽  
Variable Step Size ◽  
Maximum Output ◽  
Step Size ◽  
Maximum Power Point ◽  
Variable Step ◽  
Power Point

Abstract BackgroundNowadays, most of the recent research is directed towards photovoltaic harvesting systems due to their great characteristics. To increase the efficiency of a photoviolatic harvesting system, Maximum Power Point Tracking algorithms are utilized to achieve the maximum output power of the PV. This is done by optimizing the duty ratio of the DC-DC boost converter. ResultsIn this paper, a proposed RNA algorithm is introduced as an efficient MPPT algorithm for the PV system. This proposed RNA algorithm depends on two main parts. The First part is an artificial neural network to produce a reference power. The Second one is a proposed Recursive Bit Assignment network to present the variable step size of the duty ratio of the DC-DC boost converter. The RBA network consists of N-bit memory. The instantaneous PV power value sets the contents of the memory to generate the variable step size of the duty ratio. Moreover, the design of the neural network to give its best performance is explained. ConclusionsThe performance of the chosen PV module is simulated for a variable solar radiation and a constant temperature. Simulation studies are performed using MATLAB to evaluate the system performance. From simulation results, the proposed RNA can achieve a fast tracking time, a high power efficiency, an actual maximum power point and an acceptable ripple. Additionally, comparisons between the RNA algorithm and other related algorithms such as Perturbe and Observe, Neural Network, and Adaptive Neural Interference System algorithms are executed. The proposed RNA achieves the best performance in all terms.

scholarly journals Performance Improvement of PEM Fuel Cell Using Variable Step-Size Incremental Resistance MPPT Technique

2020 ◽  
Vol 12 (14) ◽  
pp. 5601 ◽  
Author(s):  
Hegazy Rezk ◽  
Ahmed Fathy
Keyword(s):  
Fuel Cell ◽  
Water Content ◽  
Operating Conditions ◽  
Maximum Power ◽  
Variable Step Size ◽  
Step Size ◽  
Maximum Power Point ◽  
Tracking Method ◽  
Variable Step ◽  
Power Point

The output power of a fuel cell mainly depends on the operating conditions such as cell temperature and membrane water content. The fuel cell (FC) power versus FC current graph has a unique maximum power point (MPP). The location of the MPP is variable, depending on the operating condition. Consequently, a maximum power point tracker (MPPT) is highly required to ensure that the fuel cell operates at an MPP to increase its performance. In this research work, a variable step-size incremental resistance (VSS-INR) tracking method was suggested to track the MPP of the proton exchange membrane (PEMFC). Most of MPPT methods used with PEMFC require at least three sensors: temperature sensor, water content sensor, and voltage sensor. However, the proposed VSS-INR needs only two sensors: voltage and current sensors. The step size of the VSS-INR is directly proportional to the error signal. Therefore, the step size will become small as the error becomes very small nearby the maximum power point. Accordingly, the accuracy of the VSS-INR tracking method is high in a steady state. To test and validate the VSS-INR, nine different scenarios of operating conditions, including normal operation, only temperature variation, only variation of water content in the membrane, and both variations of temperature and water content simultaneously, were used. The obtained results were compared with previously proposed methods, including particle swarm optimization (PSO), perturb and observe (P&O), and sliding mode (SM), under different operating conditions. The results of the comparison confirmed the superiority of VSS-INR compared with other methods in terms of the tracking efficiency and steady-state fluctuations.

scholarly journals Modified Variable Step-Size Incremental Conductance MPPT Technique for Photovoltaic Systems

Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2331
Author(s):  
Isaac Owusu-Nyarko ◽  
Mohamed A. Elgenedy ◽  
Ibrahim Abdelsalam ◽  
Khaled H. Ahmed
Keyword(s):  
Slope Angle ◽  
Scaling Factor ◽  
Maximum Power ◽  
Variable Step Size ◽  
Step Size ◽  
Maximum Power Point ◽  
Angle Variation ◽  
Incremental Conductance ◽  
Variable Step ◽  
Power Point

A highly efficient photovoltaic (PV) system requires a maximum power point tracker to extract peak power from PV modules. The conventional variable step-size incremental conductance (INC) maximum power point tracking (MPPT) technique has two main drawbacks. First, it uses a pre-set scaling factor, which requires manual tuning under different irradiance levels. Second, it adapts the slope of the PV characteristics curve to vary the step-size, which means any small changes in PV module voltage will significantly increase the overall step-size. Subsequently, it deviates the operating point away from the actual reference. In this paper, a new modified variable step-size INC algorithm is proposed to address the aforementioned problems. The proposed algorithm consists of two parts, namely autonomous scaling factor and slope angle variation algorithm. The autonomous scaling factor continuously adjusts the step-size without using a pre-set constant to control the trade-off between convergence speed and tracking precision. The slope angle variation algorithm mitigates the impact of PV voltage change, especially during variable irradiance conditions to improve the MPPT efficiency. The theoretical investigations of the new technique are carried out while its practicability is confirmed by simulation and experimental results.

scholarly journals A Maximum Power Point Tracking Algorithm of Load Current Maximization-Perturbation and Observation Method with Variable Step Size

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 244
Author(s):  
Lieping Zhang ◽  
Zhengzhong Wang ◽  
Peng Cao ◽  
Shenglan Zhang
Keyword(s):  
Photovoltaic Cell ◽  
Maximum Power ◽  
Variable Step Size ◽  
Step Size ◽  
Maximum Power Point ◽  
Load Current ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Variable Step ◽  
Power Point

A photovoltaic power supply with a simple structure and high tracking efficiency is needed in self-powered, wireless sensor networks. First, a maximum power point tracking (MPPT) algorithm, including the load current maximization-perturbation and observation (LCM-P&O) methods, with a fixed step size, is proposed by integrating the traditional load current maximization (LCM) method and perturbation and observation (P&O) method. By sampling the changes of load current and photovoltaic cell input current once the disturbance is applied, the pulse width modulation (PWM) regulation mode, i.e., increasing or reducing, can be determined in the next process. Then, the above algorithm is improved by using the variable step size strategy. By comparing the difference between the absolute value of the observed current value and the theoretical current value at the maximum power point of the photovoltaic cell with the set threshold value, the variable step size for perturbation is determined. MATLAB simulation results show that the LCM-P&O method, with a variable step size, has faster convergence speed and higher tracking accuracy. Finally, the two MPPT algorithms are tested and analyzed under constant voltage source input and indoor fluorescent lamp illumination through an actual circuit, respectively. The experimental results show that the LCM-P&O method with variable step size has a higher tracking efficiency, about 90%–92%, and has higher stability and lower power consumption.

Research on MPPT Technology Based on Adaptive Area Algorithm

2011 ◽  
Vol 347-353 ◽  
pp. 1044-1048
Author(s):  
Yun Yun Chen ◽  
Jun Ji Wu ◽  
Zhan Feng Ying
Keyword(s):  
Maximum Power ◽  
Variable Step Size ◽  
Step Size ◽  
Pv System ◽  
Maximum Power Point ◽  
Climate Conditions ◽  
Pv Systems ◽  
Observation Methods ◽  
Variable Step ◽  
Power Point

Considering the fact that when the cell temperature and solar insolation change rapidly, traditional variable step size(VSS) perturbation and observation(P&O) methods exist the defects that their tracking speed is relatively slow, there is small power oscillation around MPP(Maximum Power Point) and even some of them exist the situation of tracking unsuccessfully. This paper proposes a MPPT(Maximum Power Point Tracing) technology based on adaptive area algorithm. The simulation model of PV system is established by MATLAB. The simulation results show that the proposed method can track the MPP fast and accurately, and ensure the steady state characteristics of PV systems even when the climate conditions change rapidly. It effectively overcomes the defects of traditional variable step size perturbation and observation methods.

scholarly journals Modeling and Test Results of an Innovative Gyroscope Wave Energy Converter

2021 ◽  
Vol 11 (10) ◽  
pp. 4359
Author(s):  
Zhongcai Pei ◽  
Hao Jing ◽  
Zhiyong Tang
Keyword(s):  
Steady State ◽  
Wave Energy ◽  
Maximum Power ◽  
Variable Step Size ◽  
Energy Converter ◽  
Step Size ◽  
Maximum Power Point ◽  
Variable Step ◽  
Steady State Oscillation ◽  
Power Point

An improved Maximum Power Point Tracking (MPPT) method based on a purely mechanical wave energy converter (WEC) of gyroscope precession is proposed. The method adopts dynamic perturbation step adjustment, which improves the stability of power output and reduces steady-state oscillation. The paper introduces the principle of the device, establishes the mathematical model, and obtains the complete expression of power. The effect of wave frequency, pitch amplitude, power take-off (PTO) damping coefficient, and flywheel rotating speed on power output is analyzed. The output regression equation is established, and the extraction conditions of the maximum power are summarized and predicted. Aiming at the time-varying nature of actual ocean waves, a variable step size modified maximum power point (MPP) tracking control algorithm based on perturbation and observation (P&O) method is proposed. The algorithm has a unique technology to dynamically change the perturbation size, which not only improves the dynamic response but also reduces the oscillation. Besides, the boundary conditions ensure that the algorithm will not deviate from the motion trajectory, and the average filtering method and steady-state judgment can further reduce steady-state oscillation. In various ocean conditions, the proposed method has better output stability compared with other variable step size algorithms. Finally, different wave working conditions are given in the experiment, and the results verify the effectiveness of the proposed MPPT control strategy in experimental equipment. The device will be suitable for distributed power sources in small islands and ports.

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