Review A comparative investigation of maximum power point tracking methods for solar PV system Ankit Gupta ⇑ , Yogesh K. Chauhan, Rupendra Kumar Pachauri Department of Electrical Engineering, School of Engineering, Gautam Buddha University, Greater Noida 201312, Uttar Pradesh, India article info Article history: Received 12 January 2016 Received in revised form 8 June 2016 Accepted 1 July 2016 Keywords: Solar cell Maximum power point tracking Solar PV system Artificial intelligent techniques DC/DC converter Renewable energy abstract In recent years, the solar energy has been considered as one of principal renewable energy sources for electric power generation. However, the maximization of extracted power from PV system is a matter of concern as its conversion efficiency is low. Therefore, a maximum power point tracking (MPPT) con- troller is necessary in a PV system for maximum power extraction. In this paper, several MPPT methods have been studied and implemented in MATLAB/Simulink environment. Based on the generation of con- trol signal, the MPPT methods have been innovatively proposed to be categorized into three classes i.e. conventional, artificial intelligence (AI) based and hybrid methods. Further, the considered MPPT meth- ods are modeled and compared on the basis of various parameters. For achieving this purpose, MATLAB/ Simulink modeling of a double diode equivalent circuit based PV panel is developed and validated with commercially available solar panel. Then, the designed MPPT methods are implemented on this PV sys- tem under varying solar irradiation conditions to study their dynamic response for tracking the maxi- mum power point. Based on this study, a novel comparison of various class of MPPT method is carried out in terms of output voltage, current, power, rise time, fall time, tracking efficiency etc. Ó 2016 Elsevier Ltd. All rights reserved. Contents 1. Introduction ......................................................................................................... 237 2. System description .................................................................................................... 240 3. Modeling of PV panel .................................................................................................. 240 4. MPPT algorithms ..................................................................................................... 240 5. Description of various MPPT methods .................................................................................... 240 5.1. Conventional methods ........................................................................................... 240 5.1.1. Constant voltage controller (CVC) method .................................................................... 241 5.1.2. Perturb & Observe (P&O) method ........................................................................... 241 5.1.3. Incremental Conductance (IC) method ....................................................................... 242 5.2. AI based methods ............................................................................................... 243 5.2.1. Fuzzy logic controller (FLC) method ......................................................................... 244 5.2.2. Artificial neural network (ANN) method ...................................................................... 245 5.2.3. Adaptive Neuro-fuzzy Inference (ANFIS) method ............................................................... 245 5.3. Hybrid methods................................................................................................. 248 5.3.1. Modified Perturb and Observe method (Modified P&O) ......................................................... 248 5.3.2. PI modified Fuzzy logic controller (PI-FLC) method ............................................................. 249 5.3.3. Neural-Fuzzy logic (N-FL) method........................................................................... 249 http://dx.doi.org/10.1016/j.solener.2016.07.001 0038-092X/Ó 2016 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. E-mail address: guptaankit299@gmail.com (A. Gupta). Solar Energy 136 (2016) 236–253 Contents lists available at ScienceDirect Solar Energy journal homepage: www.elsevier.com/locate/solener