Real-time implementation of a maximum power point tracking algorithm based on first order sliding mode strategy for photovoltaic power systems

Abstract

This paper focuses on a maximum power point tracking (MPPT) algorithm based on the first order sliding mode approach. This work is aimed at systems that are fed with a photovoltaic (PV) generator. The main objective is to act on the panel to ensure that the energy collected is always at its maximum. Because a PV panel frequently suffers from non-linearity of its P-V curves, we propose to work with MPPT controllers based on the first order sliding mode approach; indeed, this approach in general is recognized as one of the efficient tools to design robust controllers. It has received much more attention within the last two decades, and many researchers are dealing with this type of robust controller to ensure optimal operating point of a PV system. The proposed MPPT algorithm has been implemented using a DSPACE DSP (digital signal processor) controller. To demonstrate the efficiency and the validity of the developed algorithm in real time, an experimental setup around a boost converter and a resistive load is experimentally studied and successfully implemented. The real-time validation and the experimental results show that the proposed algorithm can effectively improve the efficiency of PV array output under climatic variation and load change. It is a favorable algorithm that is easy to realize.

Circle Search Algorithm-Based Super Twisting Sliding Mode Control for MPPT of Different Commercial PV Modules

“…It is desirable to use a nonlinear control technique to pursue MPP since PV systems exhibit nonlinear behavior. In this regard, several novel MPPT algorithms based on SMC have been implemented including current sensor based SMC [31], first order SMC [32], P&O based fractional SMC [33], INC based SMC [34], backstepping SMC [35], improved double integral SMC [36], fast terminal SMC-based direct power control [37], fuzzy neural network approach based terminal SMC [38], double integral SMC [39], second order SMC [40] , super twisting SMC [41], and PSO-based SMC [42].…”

“…Summarizing the literature on MPPT-based SMC above, it can be found that the first-order SMC-MPPTs [31], [32] have the qualities of being robust and straightforward, and they can be easily implemented in hardware. Nevertheless, they exhibit chattering issues and do not reveal good dynamics during rapid-changing environmental conditions.…”

Robust Optimization and Power Management of a Triple Junction Photovoltaic Electric Vehicle with Battery Storage

“…The recharge time is improved by using the PV generator at its maximum power. For this goal, different MPPT algorithms are suggested in the literature: perturb and observe (P & O) [33][34][35], the incremental inductance (IC) [36][37][38], fuzzy logic (FL) [39][40][41], neuronal networks (NN) [42][43][44], particle swarm optimization (PSO) [45][46][47], and sliding mode [48,49] etc. High oscillation remains the major weakness of these MPPT approaches.…”

Analysis, design and implementation of analog circuitry-based maximum power point tracking for photovoltaic boost DC/DC converter

“…Tracking the global peak of a PV module in any conditions is necessary to guarantee the maximum obtainable power. The MPP tracking (MPPT) is a non-linear control algorithm to tune the interfacing converter’s duty ratio continuously, so that it can draw maximum power from the solar arrays irrespective of load or weather conditions (Garraoui et al, 2017; Jiang et al, 2013; Lim and Hamil, 2000; Maity and Sahu, 2016). Over the last two decades, research on several MPPT methods using DC/DC converters has been reported in the literature (Enany et al, 2016; Esram and Chapman, 2007; Subudhi and Pradhan, 2013; Xiao et al, 2007).…”