@inproceedings{9f5f8bfceb31406cbac93508af8dc9c6,
title = "Model Predictive Control in Photovoltaic Application: A Case Study for Qatar Agriculture",
abstract = "In this paper, a photovoltaic (PV) solar energy-based microgrid was modeled. A model predictive control (MPC), featuring a linear and accurate prediction model to overcome the drawbacks of comparable control schemes, was used to regulate the current (power) in an agricultural farm. The MPC is based on a prediction model along with a cost function that defines the switching states of the voltage source inverter to ensure the stability of the system. Furthermore, to ensure maximum power point tracking, an incremental conductance (IC) technique was used owing to its simplicity. The considered system was modeled based on Matlab/Simulink, and control performance of the proposed scheme was evaluated with simulations.",
keywords = "Agriculture microgrid, Model predictive control, Power management, Renewable energy",
author = "Sertac Bayhan and Ali Elrayyah",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 1st International Conference on Sustainable Energy-Water-Environment Nexus in Desert Climates, ICSEWEN 2019 ; Conference date: 02-12-2019 Through 05-12-2019",
year = "2022",
doi = "10.1007/978-3-030-76081-6\_40",
language = "English",
isbn = "9783030760809",
series = "Advances In Science Technology And Innovation",
publisher = "Springer Nature",
pages = "333--342",
editor = "E Heggy and V Bermudez and M Vermeersch",
booktitle = "Sustainable Energy-water-environment Nexus In Deserts",
}