Hybrid Algorithm based PFoPID Control Design of a Grid-connected PV Inverter for MPPT
Maximum Power Point Tracking (MPPT) is an extensively deployed control method for extracting more power from the solar cells of PV modules. As the solar cells include nonlinear i-v characteristics, the effectiveness of the PV module becomes lower, which leads to great power loss due to mismatching o...
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Published in | 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA) pp. 992 - 998 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.07.2020
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Subjects | |
Online Access | Get full text |
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Summary: | Maximum Power Point Tracking (MPPT) is an extensively deployed control method for extracting more power from the solar cells of PV modules. As the solar cells include nonlinear i-v characteristics, the effectiveness of the PV module becomes lower, which leads to great power loss due to mismatching of load and source. This work aims to model a new "passive fractional-order proportional-integral-derivative (PFoPID) controller" for MG connected PV inverter and by reshaping energy, the MPPT is attained through the P&O system under varied atmospheres. Depending on the passivity concept, storage related to the DC-link current, DC-link voltage, and q-axis current are build-up for a PV system, in which all variables are examined analytically. In this work, the residual energy is reshaped by the FoPID control theory, where the controlling parameters are optimally tuned by a novel hybrid algorithm is known as the Combined FF-CSO (CFF-CSO) model that combines the concepts of Cat Swarm Optimization (CSO) and Firefly Algorithm (FF). Finally, algorithmic analysis is carried out by varying the parameter c of the proposed algorithm to substantiate the efficiency of the presented model. |
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DOI: | 10.1109/ICIRCA48905.2020.9182806 |