Comparative analysis of the perturb-and-observe and incremental conductance MPPT methods

Author(s):  
Ioan Viorel Banu ◽  
Razvan Beniuga ◽  
Marcel Istrate
Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3043
Author(s):  
Mohamed Louzazni ◽  
Daniel Tudor Cotfas ◽  
Petru Adrian Cotfas

This paper introduces the management control of a microgrid comprising of photovoltaic panels, battery, supercapacitor, and DC load under variable solar irradiation. The battery is used to store the energy from the photovoltaic panels or to supply the load. The supercapacitor is used to reduce stress on batteries, improve their life cycle, and absorb the fluctuations in the energy produced. The generated photovoltaic power is optimized using Perturb and Observe and Incremental Conductance algorithms to extract the maximum power point tracking. The two algorithms are modified by adding an instantaneous step size to change the direction of the power, so as to reach the maximum power point tracking. The currents of the battery and supercapacitor are managed and controlled using the multi-loop proportional integral controllers. The obtained results show that the multi-loop proportionally integral controllers Perturb and Observe are better than the multi-loop proportional integral controllers Incremental Conductance in terms of stability of injected power. The storage system works perfectly for energy supply, system protection, and fluctuation absorption during the transitions in the solar irradiation. The proposed hybrid storage system can be installed in rural areas as an off-grid system for several uses.


2013 ◽  
Vol 3 (3) ◽  
pp. 1070-1078 ◽  
Author(s):  
Dezso Sera ◽  
Laszlo Mathe ◽  
Tamas Kerekes ◽  
Sergiu Viorel Spataru ◽  
Remus Teodorescu

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1234
Author(s):  
Sanaz Jalali Zand ◽  
Kuo-Hsien Hsia ◽  
Naser Eskandarian ◽  
Saleh Mobayen

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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