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Open AccessArticle

Comparative Study of Passive and Active Islanding Detection Methods for PV Grid-Connected Systems

Department of Electrical Engineering, College of Engineering, Majmaah University, Al Majmaah 11952, Saudi Arabia
Electrical Engineering Department, Assiut University, Assiut 71515, Egypt
Author to whom correspondence should be addressed.
Sustainability 2018, 10(6), 1798;
Received: 17 April 2018 / Revised: 23 May 2018 / Accepted: 26 May 2018 / Published: 30 May 2018
(This article belongs to the Section Energy Sustainability)
Photovoltaic (PV) power grid-connected systems have the advantages of being prompt and reliable supplies of electrical power. Nevertheless, the installation and operation requirements from the grid side have to be fulfilled in order to guarantee the security of the PV system technicians and the efficiency of the power system. Particularly, the potential for “islanding” is one of the dreads that are brought about by PV grid-connected systems. To be able to tackle these concerns, this paper investigates recent islanding detection techniques and topologies for PV systems. Active islanding detection techniques apply regular disturbances to the inverter system and then analyze the output voltage or frequency to investigate the islanding and stability of the grid. If the injected disturbances influence the load voltage or frequency, the controller forces the intermediate inverter to stop sending power to the connected load. In addition, several islanding detection techniques that inject a periodical signal to the reference current that causes a change in the magnitude of inverter output voltage when islanding happens in a three-phase photovoltaic grid-connected system are discussed. The validity of the proposed technique is tested and verified through PSIM software. View Full-Text
Keywords: photovoltaic; islanding detection; active; passive photovoltaic; islanding detection; active; passive
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Abokhalil, A.G.; Awan, A.B.; Al-Qawasmi, A.-R. Comparative Study of Passive and Active Islanding Detection Methods for PV Grid-Connected Systems. Sustainability 2018, 10, 1798.

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