Wind‐assisted microgrid grid code compliance employing a hybrid Particle swarm optimization‐Artificial hummingbird algorithm optimizer‐tuned STATCOM

Author:

Imtiaz Saqif12ORCID,Yang Lijun12,Azib Khan Hafiz Muhammad3,Mudassir Munir Hafiz4ORCID,Alharbi Mohammed5ORCID,Jamil Mohsin6ORCID

Affiliation:

1. School of Electrical Engineering Yanshan University Qinhuangdao 066004 China

2. Key Laboratory of Power Electronics for Energy Conservation and Drive Control of Hebei Province Yanshan University Qinhuangdao 066004 China

3. School of Electrical Engineering NFC Institute of Engineering and Technology Multan Multan Pakistan

4. Department of Electrical Engineering Sukkur IBA University Sukkur 65200 Pakistan

5. Department of Electrical Engineering, College of Engineering King Saud University Riyadh 11421 Saudi Arabia

6. Department of Electrical and Computer Engineering, Faculty of Engineering and Applied Science Memorial University of Newfoundland 230 Elizabeth Ave St. John's Newfoundland A1C 5S7 Canada

Abstract

AbstractThe importance of resolving stability concerns in weak AC grid‐connected doubly fed induction generator (DFIG) wind energy systems during low‐voltage ride‐through (LVRT) events cannot be ignored, given the increasing popularity of wind power‐based microgrids. Furthermore, the emergence of generation loss and postfault oscillation within a microgrid (MG) due to grid faults has also become a significant concern. The static synchronous compensator (STATCOM) under consideration in this study is tuned using particle swarm optimization (PSO), the artificial hummingbird algorithm (AHA), and a hybrid approach incorporating both PSO and AHA. Faults of both a symmetrical and an asymmetrical nature have occurred on the power grid side. The proposed hybrid PSO‐AHA‐tuned STATCOM strategy aims to improve LVRT, minimize power generation loss during faults, and reduce oscillations after a fault by controlling the flow of reactive power between point of common coupling (PCC) and MG. The MATLAB simulation environment was used to simulate the 16 MW MG test system. The performance of the PSO‐AHA‐tuned STATCOM was assessed by comparing results with those from conventional STATCOM, PSO, and AHA optimizer‐tuned STATCOM in four fault situations. A comparison of the results shows that the proposed strategy performed better than other approaches mentioned in this paper and achieved the desired objectives.

Publisher

Wiley

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