Tracking Strategy of Maximum Power Point Based on Three-Stage Variable Step-Size Incremental Conductance Algorithm

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.

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

Sustainability ◽

10.3390/su12145601 ◽

2020 ◽

Vol 12 (14) ◽

pp. 5601 ◽

Cited By ~ 3

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.

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

Symmetry ◽

10.3390/sym12020244 ◽

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.

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

International Journal of Power Electronics and Drive Systems (IJPEDS) ◽

10.11591/ijpeds.v8.i1.pp434-443 ◽

2017 ◽

Vol 8 (1) ◽

pp. 434 ◽

Cited By ~ 2

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.

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Improvement of Self-Predictive Incremental Conductance Algorithm with the Ability to Detect Dynamic Conditions

Energies ◽

10.3390/en14051234 ◽

2021 ◽

Vol 14 (5) ◽

pp. 1234

Author(s):

Sanaz Jalali Zand ◽

Kuo-Hsien Hsia ◽

Naser Eskandarian ◽

Saleh Mobayen

Keyword(s):

Output Power ◽

Maximum Power ◽

Step Size ◽

Maximum Power Point ◽

Dynamic Conditions ◽

Simulink Simulation ◽

Incremental Conductance ◽

Perturb And Observe ◽

Incremental Conductance Algorithm ◽

Power Point

This paper presents a new version of the incremental conductance algorithm for more accurate tracking of the maximum power point (MPP). The modified algorithm is called self-predictive incremental conductance (SPInC), and it recognizes the operational region. It is capable of detecting dynamic conditions, and it detects sudden changes in power resulting from changes in the intensity of radiation or temperature. By selecting the appropriate step size, it obtains maximum power from the panel at any moment. The improved algorithm reduces output power ripple and increases the efficiency of the system by detecting the operating area and selecting the appropriate step size for each region. The SPInC algorithm divides the system’s work areas into three operating zones. It calculates the size of the appropriate step changes for each region after identifying the regions, which allows for more accurate tracking of the MPP and increases the system efficiency at a speed equal to the speed of the conventional method. These additional operations did not result in a system slowdown in the tracking maximum power. According to the MATLAB/Simulink simulation results, the SPInC algorithm is more efficient than conventional InC, and the ripple output power is reduced. SPInC is also compared to the improved perturb and observe (P&O) algorithm. In general, SPInC can compete with the popular algorithms that have been recently proposed for MPPT in the other researches.

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Research on MPPT Technology Based on Adaptive Area Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.347-353.1044 ◽

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.

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Modeling and Test Results of an Innovative Gyroscope Wave Energy Converter

Applied Sciences ◽

10.3390/app11104359 ◽

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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