Maximum power point tracking of solar photovoltaic panels using advanced perturbation and observation algorithm

Abstract

An efficient maximum power point tracking (MPPT) scheme is necessary to improve the efficiency of a solar photovoltaic (PV) panel. This paper proposes an advanced perturbation and observation (P&O) algorithm for tracking the maximum power point (MPP) of a solar PV panel. Solar PV cells have a non-linear V-I characteristic with a distinct MPP which depends on environmental factors such as temperature and irradiation. In order to continuously harvest maximum power from the solar PV panel, it always has to be operated at its MPP. The proposed P&O algorithm can reduce the main drawbacks commonly related to the P&O algorithm. This is achieved with determining the short-circuit current before each perturbation and observation stage. The obtained simulation results are compared with MPPs achieved using the conventional P&O algorithm under various atmospheric conditions. The results show that the advanced P&O algorithm is better than the conventional P&O algorithms for tracking MPPs of solar PV panels. Additionally, it is simple and can be easily implemented in digital signal processor (DSP). Keywords-solar photovoltaic panel; maximum power point tracking; perturbation and observation algorithmI.

Overview of Maximum Power Point Tracking Techniques for Photovoltaic Energy Production Systems

“…An algorithm for dynamically adapting the perturbation size, according to the solar irradiation conditions was presented in [27] for increasing the response speed of the P&O algorithm and reducing the steadystate oscillation around the MPP. The short-circuit current of the PV source was estimated in [28] during the execution of the P&O algorithm by applying the measured values of the current and voltage in the single-diode model of the PV modules. The resulting value is used to detect whether a variation of the PV source output power is due to a change of the solar irradiation conditions or the MPPT process itself.…”

Accurate modeling and maximum power point detection of photovoltaic module using a few collected data

“…So, there are many investigations are proposed for this purpose such as (Abdelsalam et al, 2011;Jain and Agarwal, 2007;Kok Soon et al, 2013;Kamarzaman and Tan, 2014;Sera et al, 2013;Chun and Kwasinski, 2011;Huynh et al, 2013;Hohm and Ropp, 2003;Sher et al, 2015;Salam et al, 2013;Ishibashi et al, 2008;Chegaar et al, 2003;Faranda and Leva, 2008;López-Lapeña et al, 2010;Khezzar et al, 2009;Simjee and Chou, 2008;Dondi et al, 2008;Walker, 2001;Ma et al, 2013;Roman et al, 2006;Bahgat et al, 2005;El-Sayed and Leeb, 2014;Enslin et al, 1997;Noguchi et al, 2002). The simplest methods (open circuit voltage method and short circuit method are presented) in (Enslin et al, 1997;Noguchi et al, 2002) which are easy in implementation, but these methods have less accuracy.…”

“…Although IC MPPT is better than the (P&O) (Ramani et al, 2017) but its response is poor in the steady-state operation. Although, many improvements are proposed on the (P&O) and IC (Huynh et al, 2013;Hohm and Ropp, 2003;Sher et al, 2015), still there is a bad oscillatory behavior. The MPP estimation process can be carried out by using Soft Computing (SC) (Salam et al, 2013).…”

Maximum Power Point Tracking Using an Adaptive Perturbation and Observation Algorithm For A Grid-Connected Solar Photovoltaic System

“…However, there is always a unique point on the V-I or V-P curve called the maximum power point (MPP). This point is not known on these characteristics, but it can be located by MPPT algorithms categorized generally as follows: Perturbation and Observation (P&O) algorithms [3]- [5], Incremental Conductance (InC) algorithm [6][7][8], Constant Current (CC) or Voltage (CV) algorithm [9]- [10] and other algorithms such as Fuzzy Logic (FL) algorithm [11]- [12], Artificial Neural Network (ANN) algorithm [13] and the Particle Swarm Optimization (PSO) algorithm [14][15]. These existing algorithms have several advantages and disadvantages concerned with simplicity, convergence speed, extra hardware and cost.…”