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A control strategy for power management in a PV-battery hybrid system with MPPT

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The paper presents a control strategy which manages the power flow between a Photovoltaic (PV) module, battery and the load. Since PV system provides an unregulated voltage output, it is regulated to a desired voltage level and then given to the charge controller, which distributes the power between battery and load. To extract acme power from PV system, a Maximum Power Point Tracking (MPPT) scheme is employed. The excess energy left, after meeting the load demand, is stored in the battery. The stored energy is utilized to meet the future load demands, when there is a power deficit from the PV system. Hence power requirement of the load is managed. Also a comparison between the three commonly used MPPT techniques: Perturb & Observe (P&O) algorithm, Incremental Conductance (IC) algorithm and Fractional Open Circuit Voltage (FOCV) algorithms is done and the most suitable technique is employed for the hybrid system. When the battery is fully charged, the excess power is absorbed by the dump load, which is also managed by the charge controller. The entire hybrid system is simulated and verified in the MATLAB/Simulink platform.

    Original languageEnglish
    Title of host publication1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781467385879
    DOIs
    Publication statusPublished - 13-02-2017
    Event1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016 - Delhi, India
    Duration: 04-07-201606-07-2016

    Publication series

    Name1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016

    Conference

    Conference1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016
    Country/TerritoryIndia
    CityDelhi
    Period04-07-1606-07-16

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    All Science Journal Classification (ASJC) codes

    • Computer Networks and Communications
    • Control and Optimization
    • Artificial Intelligence
    • Energy Engineering and Power Technology
    • Renewable Energy, Sustainability and the Environment
    • Electrical and Electronic Engineering

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