Optimal Power Management of Interconnected Microgrids Using Virtual Inertia Control Technique

Mahmoud Elshenawy, Ashraf Fahmy (), Adel Elsamahy, Shaimaa A. Kandil and Helmy M. El Zoghby
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Mahmoud Elshenawy: Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, Egypt
Ashraf Fahmy: Faculty of Science and Engineering, Swansea University, Wales SA1 8EN, UK
Adel Elsamahy: Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, Egypt
Shaimaa A. Kandil: Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, Egypt
Helmy M. El Zoghby: Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, Egypt

Energies, 2022, vol. 15, issue 19, 1-30

Abstract: Two interconnected AC microgrids are proposed based on three renewable energy sources (RESs): wind, solar, and biogas. The wind turbine drives a permanent magnet synchronous generator (PMSG). A solar photovoltaic system (SPVS) with an appropriate inverter was incorporated. The biogas genset (BG) consists of a biogas engine coupled with a synchronous generator. Two interconnected AC microgrids, M 1 and M 2 , were considered for study in this work. The microgrid M 2 is connected to a diesel engine (DE) characterized by a continuous power supply. The distribution power loss of the interconnected AC microgrids comprises in line loss. The M 1 and M 2 losses are modeled as an objective function (OF). The power quality enhancement of the interconnected microgrids will be achieved by minimizing this OF. This research also created a unique frequency control method called virtual inertia control (VIC), which stabilizes the microgrid frequency using an optimal controller. In this paper, the following five controllers are studied: a proportional integral controller (PI), a fractional order PI controller (FOPI), a fuzzy PI controller (FPI), a fuzzy fractional order PI controller (FFOPI), and a VIC based on FFOPI controller. The five controllers were tuned using particle swarm optimization (PSO) to minimize the (OF). The main contribution of this paper is the comprehensive study of the performance of interconnected AC microgrids under step load disturbances, step changes in wind/solar input power, and eventually grid following/forming contingencies as well as the virtual inertia control of renewable energy resources used in the structure of the microgrids.

Keywords: contingency of power system; energy storage system (ESS); fuzzy fractional order PI (FFOPI); fuzzy PI (FPI); multi-objective optimization; microgrid; power quality enhancement; particle swarm optimization (PSO); virtual inertia control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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