Design model predictive control with swarm inspired MPPT algorithms to extract optimum power for a single-stage grid connected PV inverter
  Brief Description

This project aims to develop a control algorithm using Model predictive control with swarm-inspired MPPT algorithm for a single stage grid connected PV inverter. Single-stage PV inverters are the key to adopting mass-scale PV realisation in the grid. However, it is difficult to achieve a fast and accurate MPPT response due to its single conversion structure. Rapid fluctuations in the irradiance or occurrence of partial shadings make this task even more difficult and induce unexpected oscillations in the outputs (voltage and current) and inverters often fail to extract the maximum possible power out of the PV arrays. Thus, this project aims to
• design and implement swarm-based MPPT algorithms (Particle swarm optimisation, Ant colony optimisation, Artificial bee colony optimisation)
• couple the swarm-based MPPT algorithms with model predictive control to operate the inverter efficiently
• compare the performance of different swarm-based algorithms among themselves and other existing MPPT algorithms in the literature

A one-month secondment (Either in one stretch or 2 visits of two weeks) is required at the Norwegian University of Science and Technology (NTNU)where an extensive setup of PV connected grid emulator exists along with OPAL-RT control set up and other required facilities for PV systems operation research.

  • Start Date:

    1 June 2022

  • End Date:

    30 June 2023

  • Activity Type:

    Externally Funded Research

  • Funder:

    Engineering and Physical Sciences Research Council

  • Value:


Project Team