A High-Performance Adaptive Incremental Conductance MPPT Algorithm for Photovoltaic Systems

Abstract

Abstract:The output characteristics of photovoltaic (PV) arrays vary with the change of environment, and maximum power point (MPP) tracking (MPPT) techniques are thus employed to extract the peak power from PV arrays. Based on the analysis of existing MPPT methods, a novel incremental conductance (INC) MPPT algorithm is proposed with an adaptive variable step size. The proposed algorithm automatically regulates the step size to track the MPP through a step size adjustment coefficient, and a user predefined constant is unnecessary for the convergence of the MPPT method, thus simplifying the design of the PV system. A tuning method of initial step sizes is also presented, which is derived from the approximate linear relationship between the open-circuit voltage and MPP voltage. Compared with the conventional INC method, the proposed method can achieve faster dynamic response and better steady state performance simultaneously under the conditions of extreme irradiance changes. A Matlab/Simulink model and a 5 kW PV system prototype controlled by a digital signal controller (TMS320F28035) were established. Simulations and experimental results further validate the effectiveness of the proposed method.

Global Maximum Power Point Tracking (MPPT) of a Photovoltaic Module Array Constructed through Improved Teaching-Learning-Based Optimization

“…To ensure the maximum power output, the duty cycles of a power converter are commonly adopted. Concerning conventional maximum power point tracking (MPPT) techniques, they include the most frequently adopted perturb and observe (P&O) [2][3][4] and incremental conductance (INC) [5,6] methods. Although the P&O method is simple and involves only a few parameters, a drawback of this method is that users must choose between tracking speed and number of oscillations, in which favorable performance of one comes at the expense of the other.…”

Multilevel DC-link converter photovoltaic system with modified PSO based on maximum power point tracking

“…The use of by-pass diodes has limited this problem, but power potentially available from by-passed cells is lost. Various control methods, such as such as perturb and observe (P&O) (Femia et al,2009;Killi and Samanta, 2015;Elbaset et al, 2016), Incremental conductance (IncCond) (Elgendy et al, 2012;Radjai et al, 2014;Li et al, 2016), hill climbing (HC) (Alajmi et al, 2011;Xiao et al, 2016), fuzzy logic (Messai et al, 2011;Letting et al, 2012;Cheng et al, 2015;Rezvani and Gandomkar, 2016), artificial neural network (ANN) ( Liu et al, 2013;Boumaaraf et al 2015;Lin et al, 2016;Messalti et al, 2017), particle swarm optimization (PSO) Cheng et al, 2015;Letting et al, 2012;Manickam et al, 2016;Renaudineau et al, 2015), sliding mode (Kim, 2007;Chu and Chen, 2009;Zhang et al, 2015;Mojallizadeh et al, 2016;Ouchen et al, 2016) and so on, have been proposed to enable optimal power generation from the chained PV strings with by-pass diodes and under partial shading conditions, but satisfactory solutions in terms of simultaneously maximizing the power generated and protecting the PV panels have still been a challenge (Rezk and Eltamaly, 2015;Chen et al, 2015;Liu et al, 2016;Kumar and Chatterjee, 2016;Gupta et al, 2016).…”

Direct Fixed-Step Maximum Power Point Tracking Algorithms with Adaptive Perturbation Frequency

“…Preliminary results demonstrate the superiority of the proposed method over adaptive perturbation step size operation during transients, without compromising the steady state performance.Energies 2019, 12, 399 2 of 16 between transient and steady-state operation [21]. In order to tackle this drawback, adjustable (or adaptive) step size versions of non-model-based algorithms have been proposed [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38], in which the step size is adjusted, typically in proportion to the derivative of PVG power with respect to control variable. Indeed, such algorithms demonstrate superiority over the fixed step versions, achieved at the expense of more complex implementation.…”