A new global maximum power point tracking technique for solar photovoltaic (PV) system under partial shading conditions (PSC) J. Prasanth Ram, N. Rajasekar * Solar Energy Research Cell (SERC), School of Electrical Engineering (SELECT), VIT University, Vellore, India article info Article history: Received 22 June 2016 Received in revised form 19 September 2016 Accepted 20 October 2016 Available online xxx Keywords: Global maximum power point (GMPP) Partial shaded conditions (PSC) Photovoltaic (PV) abstract Over a period of years, Maximum Power Point Tracking has become a mandatory requirement for Solar Photo Voltaic (PV) systems. Being dependent to environmental changes, the PV power constantly fluc- tuates due to change in irradiation. Under such conditions, large PV array connected in interconnection will experience non-uniform irradiation thus results multiple peaks in P-V characteristics. Although many conventional and soft computing techniques have been proposed in literature, the ability to identify global peak under strong shading conditions is not guaranteed. Particularly, local peak in close agreement to global peak makes most of the algorithms to get trapped in local peaks. This condition often occurs due to insufficient randomness in algorithm hence, a new Flower Pollination Algorithm (FPA) is investigated in this research. Proposed method has dual mode search ability which creates required randomness in every iteration is the key reason to suit FPA for MPPT. Simulation and experi- mental results verified with different patterns portray FPA excellence under all irradiated conditions. Further performance of FPA is verified with Particle swarm Optimization method and conventional P&O method. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction Owing to numerous advantages such as Environmental friendly, absence of moving parts, less maintenance, zero noise and abun- dant availability, power generation via PhotoVoltaic (PV) panels nowadays has become an unavoidable source of power generation [1,2]. However, low panel efficiency dependent to climatic changes still prevail as a drawback with solar PV panels. Therefore to convert the available useful power, PV systems employ Maximum Power Point Tracking (MPPT) techniques [2,3]. Generally PV array is formed by connecting panels in series- parallel, bridged link and total cross ties however, PV array under Partial Shading Condition (PSC) experience uneven distribution of irradiation that create multiple peaks in P-V curve [3]. Under such conditions identifying global peak with highest power output is a challenging task hence, MPPT controller is incorporated. Various methodologies have been put forward in literature to track maximum power and these techniques can be categorized into (i) conventional techniques [4e6] (ii) Evolutionary/swarm Algorithm (EA) and bio inspired techniques [2,3]. Conventional algorithms suffer due to fixed step size moreover its inherent oscillating nature results in low average power values and deviates the operating point away from Maximum Power Point [2]. To overcome the inability of conventional methods adaptive and modified conven- tional techniques were proposed. These algorithms show good performance under constant change in environmental conditions [4]. Further, it is noteworthy to mention that conventional methods miserably fail when non-homogeneous insolation occur. Failure of conventional methods compelled PV researchers to use evolutionary/Swarm intelligence algorithms like Genetic Al- gorithm (GA) [7], Artificial Neural Network (ANN) [8] and Fuzzy Logic Control (FLC) [9,10] method. These methods are known for their ability to solve non linear objective functions and suit to reach global peak under PSC. However, GA method follows complex computations via crossover, selection and mutation while ANN method performs training of neurons. FLC method requires the knowledge base to create rules for tracking. Thus large memory size, complex computation and prior knowledge for training limit its usage [3]. Moreover both conventional and EA MPPT imple- mentation do not provide convergence to global peak point at all the times. Hence, these methods are blended with conventional * Corresponding author. Solar Energy Research Cell (SERC), School of Electrical Engineering (SELECT), VIT University, Vellore, 632014 Tamil Nadu India. E-mail addresses: jkprasanthram@gmail.com (J. Prasanth Ram), natarajanrajasekar@gmail.com (N. Rajasekar). Contents lists available at ScienceDirect Energy journal homepage: www.elsevier.com/locate/energy http://dx.doi.org/10.1016/j.energy.2016.10.084 0360-5442/© 2016 Elsevier Ltd. All rights reserved. Energy xxx (2016) 1e14 Please cite this article in press as: Prasanth Ram J, Rajasekar N, A new global maximum power point tracking technique for solar photovoltaic (PV) system under partial shading conditions (PSC), Energy (2016), http://dx.doi.org/10.1016/j.energy.2016.10.084