Model Predictive Control-Based Hybrid Photovoltaic-Battery System for Weak Grid Conditions with Multifunctionality

Fatma Selim*, Mokhtar Aly, Tamer F. Megahed, Masahito Shoyama, Sobhy M. Abdelkader

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Battery integration with photovoltaic (PV) systems is essential for mitigating their intermittency effects due to the dependency of their output power on weather conditions. The single-stage PV structure can achieve higher efficiency, lower cost, and reduced number of components among existing structures. However, control complexity increases with single-stage PV systems in the case of integrating battery storage systems. The situation becomes more complicated with the weak grid conditions and the required multi-functionalities of PV systems with electrical grids. Therefore, This Paper introduces an enhanced control algorithm utilizing the model predictive control (MPC) approach for single-stage hybrid PV-battery systems. The proposed method can rapidly respond to the transients and variations of load, PV output power, and grid requirements. The simulation results show the enhanced transient response, steady-state response, mitigating week grid effects, and satisfying load and grid requirements.

Original languageEnglish
Title of host publication2023 24th International Middle East Power System Conference, MEPCON 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350358469
DOIs
StatePublished - 2023
Event24th International Middle East Power System Conference, MEPCON 2023 - Mansoura, Egypt
Duration: 20232023

Publication series

Name2023 24th International Middle East Power System Conference, MEPCON 2023

Conference

Conference24th International Middle East Power System Conference, MEPCON 2023
Country/TerritoryEgypt
CityMansoura
Period19/12/2321/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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