Hybrid Algorithm based PFoPID Control Design of a Grid-connected PV Inverter for MPPT

• Published in: 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA) pp. 992 - 998
• Main Authors: Thangam, Thomas, Muthuvel, K.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2020
• Subjects: Analytical models; Atmospheric modeling; Biological system modeling; CFF-CSO model; Computational modeling; Conferences; Error; FoPID controller; Inverters; Maximum power point trackers; MPPT; P&O system; Voltage analysis
• DOI: 10.1109/ICIRCA48905.2020.9182806

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.