RESEARCH ARTICLE An experimental study on photovoltaic module with optimum power point tracking method Kaliraja Thangamani 1,4 | Martin Leo Manickam 2 | Chellaswamy Chellaiah 3 1 Department of ECE, SV Engineering College for Women, Tirupati, Andrapradesh, India 2 Department of ECE, St. Joseph College of Engineering, Chennai, India 3 Department of ECE, Lords Institute of Engineering and Technology, Hyderabad, India 4 Department of Electronics, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India Correspondence Kaliraja Thangamani, Department of ECE, SV Engineering College for Women, Tirupati, Andrapradesh, India. Email: kaliraja.t@svcolleges.edu.in Summary With the latest development in the area of power electronics, the photovoltaic (PV) cell can be made to operate at the optimum peak point with increased sys- tem efficiency. To maximize the power on photovoltaic cells under various con- ditions, optimum power point tracking (OPPT) methods such as conventional and soft computing methods are used. But it is not providing accurate and effi- cient output due to its randomness, fixed step size, and poor convergence. In this paper, the adaptive differential evolution (ADE) algorithm is introduced in the solar module to obtain the maximum power, and it has the ability to reach the optimum peak with the shorter time period. An Apriori method is used in the proposed ADE algorithm, wherein mutation factor and crossover are used as control parameters to increase the speed. The ruggedness of the ADE algorithm is tested under different shading condition such as no shading, 30% shading, and 50% shading condition. Extensive simulation has been car- ried out using PV solar module, and the analysis has been tabulated and com- pared with the existing results. Various statistical metrics such as root mean square error, the relative error, tracking efficiency, standard deviation, and effi- ciency are used to evaluate the effectiveness and validate the feasibility of the proposed method. Further, hardware has been implemented and tested with this algorithm. KEYWORDS differential evolution algorithm, optimum power point tracking, photovoltaic cell, shading condition 1 | INTRODUCTION The solar energy is used by photovoltaic (PV) cells which have nonlinear electrical characteristics that must be opti- mized for different conditions. The optimum power point tracking is one such technique that will achieve maximum power generation. The main aim of the OPPT technique is to improve and enhance the output power of the PV system under different shading conditions. The voltage and current of the PV system can be adjusted by OPPT to work with the OPP. 1 In recent years, the field of maximum power point tracking attracts great attention of the researchers because it is the economic way to improve the efficiency of the PV system. 2 An optimum power point tracking controller may be used for obtaining maximum output power. 3 This controller is an integral part of the solar panel, power converter, and the load. A lot of research works are going on in the use of OPPT to produce maximum power. The two method- ologies being used in this case are (a) conventional OPPT 4 and (b) OPPT using soft computing methods. 5 The perfor- mance of the solar power transfer can be checked by the Monte Carlo algorithm on a yearly basis under constant Received: 23 March 2019 Revised: 24 July 2019 Accepted: 30 July 2019 DOI: 10.1002/2050-7038.12175 Int Trans Electr Energ Syst. 2019;e12175. https://doi.org/10.1002/2050-7038.12175 © 2019 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/etep 1 of 26