A new MPPT control strategy: Study of auto-adapted step size incremental conductance method based on segmented numerical approximation

Author(s):  
Sun Jianping ◽  
Li Xiaozheng
2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
M. Abdulkadir ◽  
A. H. M. Yatim ◽  
S. T. Yusuf

This paper presents a control strategy proposed for power maximizing which is a critical mechanism to ensure power track is maximized. Many tracking algorithms have been proposed for this purpose. One of the more commonly used techniques is the incremental conductance method. In this paper, an improved particle swarm optimization- (IPSO-) based MPPT technique for photovoltaic system operating under varying environmental conditions is proposed. The approach of linearly decreasing scheme for weighting factor and cognitive and social parameter is modified. The proposed control scheme can overcome deficiency and accelerate convergence of the IPSO-based MPPT algorithm. The approach is not only capable of tracking the maximum power point under uniform insolation state, but also able to find the maximum power point under fast changing nonuniform insolation conditions. The photovoltaic systematic process with control schemes is created using MATLAB Simulink to verify the effectiveness with several simulations being carried out and then compared with the conventional incremental conductance technique. Lastly, the effectiveness of the intended techniques is proven using real data obtained form previous literature. With the change in insolation and temperature portrait, it produces exceptional MPPT maximization. This shows that optimum performance is achieved using the intended method compared to the typical method.


2020 ◽  
Vol 24 (8) ◽  
pp. 6039-6046
Author(s):  
Li Shengqing ◽  
Li Fujun ◽  
Zheng Jian ◽  
Chen Wen ◽  
Zhang Donghui

2020 ◽  
Vol 10 (15) ◽  
pp. 5214
Author(s):  
Man-Tsai Chuang ◽  
Yi-Hua Liu ◽  
Song-Pei Ye

In this paper, a novel variable step size (VSS) incremental conductance (INC) method with an adaptive scaling factor is proposed. The proposed technique utilizes the model-based state estimation method to calculate the irradiance level and then determine an appropriate scaling factor accordingly to enhance the capability of maximum power point tracking (MPPT). The fast and accurate tracking can be achieved by the presented method without the need for extra irradiance and temperature sensors. Only the voltage-and-current sets of any two operating points on the characteristic curve are needed to estimate the irradiance level. By choosing a proper scaling factor, the performance of the conventional VSS INC method can be improved. To validate the studied algorithm, a 600 W prototyping circuit is constructed and the performances are demonstrated experimentally. Compared to conventional VSS INC methods under the tested conditions, the tracking time is shortened by 31.8%. The tracking accuracy is also improved by 2.1% and 3.5%, respectively. Besides, tracking energy loss is reduced by 43.9% and 29.9%, respectively.


Increasing the efficiency of MPPT techniques is the essential aspects of the Solar Photovoltaic System. This efficiency is affected by the chattering available with the MPPT techniques. An MPP technique which generates less chattering in the system is more efficient than the others. This paper presents the chattering analysis of the popular Maximum Power Point Tracking (MPPT) techniques Perturb & Observe (P&O) and Incremental conductance method for the fixed and variable step size. The algorithms are simulated under similar load and environment conditions. In the result it is found that the incremental conductance method has very less chattering in comparison with the P&O for the fixed step size and variable step size. Further, for the different solar radiation chattering is observed and tabulated


2021 ◽  
Vol 10 (3) ◽  
pp. 1183-1192
Author(s):  
Zakaria Massaq ◽  
Abdelouahed Abounada ◽  
Mohamed Ramzi

In this work, an efficient control scheme for a double stage pumping system is proposed. On the DC side, a three-level boost converter is employed to maximize the photovoltaic power and to step-up the DC-link voltage. For maximum power point tracking, the classical incremental conductance method is substituted by a fuzzy logic controller. The designed controller estimates the optimal step size which speeds up the tracking process and improves the accuracy of the extracted photovoltaic power. Afterwards, the voltages across the three-level boost converter (TLBC) capacitors are balanced by phase shifting the applied duty ratios. On the motor pump side, a two-level inverter drives the motor pump with the cascaded nonlinear predictive control. The predictive controller is preferred over the conventional field-oriented control because it accelerates the torque response and resists to the change of the engine parameters. The designed controllers are evaluated using MATLAB/Simulink, and compared with the conventional controllers (incremental conductance algorithm and field-oriented control). The robust control scheme of the entire system has increased the hydraulic power by up to 23% during the system start-up and up to 10% in steady state.


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