Microgrid Islanding Detection Based on Mathematical Morphology

Fatemeh Ghalavand, Behzad Asle Mohammadi Alizade, Hossam Gaber and Hadis Karimipour
Additional contact information
Fatemeh Ghalavand: Department of Electrical Engineering, Shahid Beheshti University, Tehran 1983969411, Iran
Behzad Asle Mohammadi Alizade: Department of Electrical Engineering, Shahid Beheshti University, Tehran 1983969411, Iran
Hossam Gaber: Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, ON L1H 7K4, Canada
Hadis Karimipour: School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada

Energies, 2018, vol. 11, issue 10, 1-18

Abstract: Voltage and frequency stability are highly important for reliable performance of smart grids. In grid-connected mode, the utility controls these parameters, but when islanding occurs these parameters exceed their limits, which may result in irreparable damage to the system. This paper presents a time-domain approach which uses basic mathematical morphology (MM) operators, dilation and erosion filters, for microgrid islanding detection. The proposed method applies a dilation-erosion differential filter (DED) of the RMS signal (DEDFOR) at the point of common coupling (PCC) in a micro-grid connected to distributed generations (DGs). To evaluate the performance of the proposed approach, it is tested and compared with existing techniques in the literature under various conditions such as capacitor bank switching and motor starting. The results verify the accuracy and efficiency of the proposed technique for islanding detection under different operating conditions and various power mismatches.

Keywords: microgrid; islanding detection; dilation-erosion differential filter of RMS signal; mathematical morphology; passive method; signal processing method (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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/10/2696/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/10/2696/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:10:p:2696-:d:174683

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().