Adaptive Dynamic Control Based Optimization of Renewable Energy Resources for Grid-Tied Microgrids

Muhammad Asghar Majeed, Furqan Asghar, Muhammad Imtiaz Hussain, Waseem Amjad, Anjum Munir, Hammad Armghan and Jun-Tae Kim
Additional contact information
Muhammad Asghar Majeed: Department of Electrical Engineering, The University of Faisalabad, Faisalabad 38000, Pakistan
Furqan Asghar: Department of Energy Systems Engineering, University of Agriculture, Faisalabad 38000, Pakistan
Muhammad Imtiaz Hussain: Agriculture and Life Sciences Research Institute, Kangwon National University, Chuncheon 24341, Korea
Waseem Amjad: Department of Energy Systems Engineering, University of Agriculture, Faisalabad 38000, Pakistan
Anjum Munir: Department of Energy Systems Engineering, University of Agriculture, Faisalabad 38000, Pakistan
Hammad Armghan: School of Electrical Engineering, Shandong University, Jinan 250061, China
Jun-Tae Kim: Department of Architectural Engineering, Kongju National University, Cheonan 31080, Korea

Sustainability, 2022, vol. 14, issue 3, 1-14

Abstract: Renewable-energy-resource-based microgrids can overcome excessive carbon footprints and increase the overall economic profile of a country. However, the intermittent nature of renewables and load variation may cause various control problems which highly affect the power quality (frequency and voltages) of the overall system. This study aims to develop an adaptive technique for the optimization of renewable energy resources (RERs). The proposed grid-tied microgrid has been designed using a wind-turbine (WT) based distributed generation, a photovoltaic (PV) system, a diesel generator as an emergency backup, and battery energy storage system (BESS). The flexible (residential) and non-flexible (industrial) loads are connected with the proposed grid. Matlab/Simulink has been used to evaluate the performance of the proposed optimization technique. Comparison with different in-use techniques shows that the proposed technique is more reliable and efficient than the state of the art optimization techniques currently in use. Moreover, this proposed system provides robust optimization of parameters of concern such as frequency and voltages, makes efficient use of the maximum power point tracking while regulating voltages, reduces the overall system cost, and increases economic profitability.

Keywords: adaptive dynamic programming; grid-tied microgrid; flexible and non-flexible load; parameters optimization; maximum power point tracking; frequency and voltage stabilization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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