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Maximum Power Point Tracking Techniques for Micro-Grid Hybrid Wind and Solar Energy Systems - a Review


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DOI: https://doi.org/10.15866/irecon.v8i6.19502

Abstract


The rapid increase of population and city expansion has led to increased demand for electric power, which may tax conventional sources of electricity beyond their limits. Conventional electricity generation is also a source of environmental pollution and greenhouse gas emissions. To overcome these problems and to reduce generation costs, there is a need to employ and integrate economical and clean renewable energy sources. These power sources are mainly solar and wind energy through implementation of micro-grids. This paper presents a survey of how to develop hybrid renewable energy sources, in this case, PV solar systems and small scale wind turbine systems, to convert solar and wind energy into electricity. The survey explains the required equipment for power conditioning and maximum power tracking techniques (MPPT). It also discusses various kinds of DC/DC converters and their operating principles. This survey also deals with MPPT algorithms and techniques including Perturb and Observe, Incremental Conductance, Ripple Correlation Control, Fuzzy Logic, Neural Networks, ANFIS, Neuro-Fuzzy algorithms, and Parasitic Capacitance and comparison is made among them.  The overarching goal is to mitigate atmospheric changes and extract the maximum power and voltage while maintaining power system stability.
Copyright © 2020 Praise Worthy Prize - All rights reserved.

Keywords


ANFIS; Incremental Conductance; Fuzzy; Hybrid; Power; MPPT; Neural; Neuro-Fuzzy; Perturb and Observe; RCC; Solar; Survey; Wind Turbine

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