Publication Type : Conference Paper
Publisher : 2018 International Conference on Control, Power, Communication and Computing Technologies (ICCPCCT).
Source : 2018 International Conference on Control, Power, Communication and Computing Technologies (ICCPCCT), 2018
Url : https://www.researchgate.net/publication/329648611_A_Review_on_Advanced_MPPT_methods_for_SPV_system_under_Partial_Shaded_Conditions
Campus : Amritapuri
School : School of Engineering
Department : Electrical and Electronics
Year : 2018
Abstract : Maximum power point tracking (MPPT) is an algorithm to extract maximum available power from a solar photovoltaic system associated with DC-DC power converters. Conventional MPPT methods like Perturb and Observe (P&O) algorithm and Incremental Conductance algorithm are inefficient, as they cannot differentiate between local and global MPP. In addition, they oscillate on reaching MPP due to their fixed step size. Advanced methods using Artificial Neural Networks and Artificial Intelligence based methods were proposed to overcome these problems. These advanced methods have high tracking efficiency and they are fast. Particle Swarm Optimization algorithm based MPPT method a simple and basic method of Artificial Intelligence based MPPT methods. This paper presents a brief review of advanced artificial intelligence based MPPT methods alongside the generic SPV model utilized for simulation
Cite this Research Publication : H. Choutapalli, Bharath K. R., and Dr. P. Kanakasabapathy, “A Review on Advanced MPPT methods for SPV system under Partial Shaded Conditions”, in 2018 International Conference on Control, Power, Communication and Computing Technologies (ICCPCCT), 2018.