{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T20:06:13Z","timestamp":1770753973699,"version":"3.50.0"},"reference-count":43,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,6,11]],"date-time":"2020-06-11T00:00:00Z","timestamp":1591833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah","award":["DF-483-135-1441"],"award-info":[{"award-number":["DF-483-135-1441"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper develops an islanding classification mechanism to overcome the problems of non-detection zones in conventional islanding detection mechanisms. This process is achieved by adapting the support vector-based data description technique with Gaussian radial basis function kernels for islanding and non-islanding events in single phase grid-connected photovoltaic (PV) systems. To overcome the non-detection zone, excess and deficit power imbalance conditions are considered for different loading conditions. These imbalances are characterized by the voltage dip scenario and were subjected to feature extraction for training with the machine learning technique. This is experimentally realized by training the machine learning classifier with different events on a     5 \u00a0 kW     grid-connected system. Using the concept of detection and false alarm rates, the performance of the trained classifier is tested for multiple faults and power imbalance conditions. The results showed the effective operation of the classifier with a detection rate of 99.2% and a false alarm rate of 0.2%.<\/jats:p>","DOI":"10.3390\/s20113320","type":"journal-article","created":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T05:56:27Z","timestamp":1592200587000},"page":"3320","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Data Description Technique-Based Islanding Classification for Single-Phase Grid-Connected Photovoltaic System"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0476-3991","authenticated-orcid":false,"given":"Ahteshamul","family":"Haque","sequence":"first","affiliation":[{"name":"Advance Power Electronics Research Lab, Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdulaziz","family":"Alshareef","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1131-5350","authenticated-orcid":false,"given":"Asif Irshad","family":"Khan","sequence":"additional","affiliation":[{"name":"Computer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2127-7183","authenticated-orcid":false,"given":"Md Mottahir","family":"Alam","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8998-3861","authenticated-orcid":false,"given":"Varaha Satya Bharath","family":"Kurukuru","sequence":"additional","affiliation":[{"name":"Advance Power Electronics Research Lab, Department of Electrical Engineering, Jamia Millia Islamia, New Delhi 110025, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6493-0969","authenticated-orcid":false,"given":"Kashif","family":"Irshad","sequence":"additional","affiliation":[{"name":"Center of Research Excellence in Renewable Energy (CoRE-RE), King Fahd University of Petroleum &amp; Minerals, Dhahran 31261, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.esr.2019.01.006","article-title":"The role of renewable energy in the global energy transformation","volume":"24","author":"Gielen","year":"2019","journal-title":"Energy Strategy Rev."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Marinakis, V., Doukas, H., Koasidis, K., and Albuflasa, H. 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