http://www.iaeme.com/IJECET/index.asp 47 editor@iaeme.com International Journal of Electronics and Communication Engineering & Technology (IJECET) Volume 7, Issue 2, March-April 2016, pp. 47–59, Article ID: IJECET_07_02_007 Available online at http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=7&IType=2 Journal Impact Factor (2016): 8.2691 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6464 and ISSN Online: 0976-6472 © IAEME Publication MAXIMUM POWER POINT TRACKING WITH ARTIFICIAL NEURAL NET WORK ARTI SAXENA Department of Electronics Engineering, PSIT College of Engineering, Kanpur ABSTRACT Fossil fuels’ rapid depletion and need to protect the environment has left us to think upon alternatives and solutions to curb the excess use of conventional sources and shift focus on the renewable energy. In this paper we have designed a prototype model inclusive of techniques that support the need to harness the solar energy. Index terms: Maximum Power Point, Buck-Boost Converter, Neural Network Architecture Cite this Article: Arti Saxena. Maximum Power Point Tracking with Artificial Neural Network, International Journal of Electronics and Communication Engineering & Technology, 7(2), 2016, pp. 47–59. http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=7&IType=2 1. INTRODUCTION MAXIMUM Power Point Tracking is a technique that Grid Tie Inverters, Solar Battery Chargers, and other similar devices use to get the maximum possible power from one or more solar panels. Solar cells have a complex relationship between solar irradiation, temperature and total resistance that produces a non-linear I-V curve. The MPPT System samples out the output of the cells and applies the proper load to obtain maximum power for any given environmental conditions, ranging from a clear sky to a heavily clouded one, from rainfall to misty, and even foggy. PV cells have a complex relationship between their operating environment and the maximum power they can produce. The fill factor, FF, is a parameter that characterizes the non-linear electrical behavior of the cell. In tabulated data it is often used to estimate the maximum power that a cell can provide. With an optimal load under given conditions, power oc sc P FF V I    ; V oc being Open circuit Voltage and ISC being Short Circuit Current. For most purposes, FF, VOC, and ISC are enough pieces of information to give a useful conclusions on the electrical behavior of a cell operating under typical conditions [2, 3] . For any given set of operating conditions, cells have a single operating point where the values of V & I of each cell result in a maximum power output. These values correspond to a particular load resistance which is equal