Open AccessIndependent Component Analysis and Sophisticated Distribution Control Algorithmsbased Improving the Efficecny of Solar Power Generation
Author(s) -
Prof.V.M. Madhavan*,
D Senthil Kumar,
M. Loganathan
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c5540.118419
Subject(s) - maximum power point tracking , photovoltaic system , renewable energy , computer science , automotive engineering , electricity generation , duty cycle , power (physics) , reliability engineering , electrical engineering , engineering , voltage , inverter , physics , quantum mechanics
Today, people are increasingly worried about environmental problems due to fuel shortage and generation of renewable energy sources. Among the renewable resources, wind generators and photovoltaic panels are primary competitors. For most of their applications, they have the advantages of having a load interface with different power converter circuits for maintenance and free of contamination, but their installation costs are high. Normally Photovoltaic modules also have relatively low conversion efficiency and Overall system cost of PV using Maximum Power Point Tracking (MPPT) techniques are high. The volume can be reduced by the use of high-performance power conditioners that allow for maximum energy consumption. Existing solar power generation systems have some disadvantages of being all day as a result of less direct exposure to true sunlight. This work is aimed at exploring the functions of a MPPT system that includes installations of sophisticated distribution control (SDC) and Independent Component Analysis (ICA) methods. The duty cycle of power converter is significantly controlled using proposed SDC and ICA algorithms and guarantee MPPT operation at its highest efficiency. The function of proposed ICA and SDC has been compared with widely used in traditional algorithms in the MATLAB Simulink environment. Over 97% of capacity is achieved through the respective SDC and ICA methods.