{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:39:07Z","timestamp":1760060347897,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T00:00:00Z","timestamp":1755648000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2022YFE01406"],"award-info":[{"award-number":["2022YFE01406"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Recent advancements in synchrophasor measurement technologies have introduced an unprecedented level of visibility in power distribution networks (PDNs), providing a high-quality data foundation for the accurate perception of event source locations. However, the high cost and deployment expense pose a significant challenge in balancing system observability and event source location identification (ESLI) accuracy. In this paper, we propose a staged ESLI scheme based on voltage measurement deviation (VMD), which can achieve high-precision ESLI and event current calculations under extremely low-observability conditions, where the measurement devices are deployed only at the head substation and terminal buses. By setting an unknown event injection current and traversing each bus along the target feeder to derive the terminal bus voltage and its outgoing current, an ESLI model based on virtual event current injection (VCI) is constructed, which not only assists in the ESLI task but also confers the solving capability of the event current. Leveraging the event current calculation ability of the ESLI model, a VMD-based staged ESLI algorithm is developed, achieving an ordered and accurate search for the exact location of the event source in a goal-oriented manner. The effectiveness of the developed ESLI algorithm is evaluated on the IEEE 33-bus test system. Experimental results demonstrate that our VMD achieves high-precision ESLI and event current solving in PDNs under extremely low observability, significantly outperforming the state-of-the-art ESLI methods.<\/jats:p>","DOI":"10.3390\/s25165169","type":"journal-article","created":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T15:53:37Z","timestamp":1755705217000},"page":"5169","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Staged Event Source Location Identification Scheme in Power Distribution Networks Under Extremely Low Observability"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9164-4757","authenticated-orcid":false,"given":"Xi","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianyong","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China"},{"name":"School of Electrical Engineering, Southeast University, Nanjing 210096, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5379-6522","authenticated-orcid":false,"given":"Fei","family":"Mei","sequence":"additional","affiliation":[{"name":"College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1821","DOI":"10.1109\/TSG.2023.3295240","article-title":"A generic bayesian method for faulted section identification in distribution systems against wind-induced extreme events","volume":"15","author":"Bian","year":"2024","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tao, Y., Yu, T., and Yang, J. (2025). Photovoltaic array fault diagnosis and localization method based on modulated photocurrent and machine learning. Sensors, 25.","DOI":"10.3390\/s25010136"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4256","DOI":"10.1049\/iet-gtd.2017.0656","article-title":"Wavelet-based extreme learning machine for distribution grid fault location","volume":"11","author":"Shafiullah","year":"2017","journal-title":"IET Gener. Transm. Distrib."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3189","DOI":"10.1109\/TPWRS.2021.3049443","article-title":"Block-sparse bayesian learning method for fault location in active distribution networks with limited synchronized measurements","volume":"36","author":"Jiang","year":"2021","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1187","DOI":"10.1109\/TPWRD.2014.2372045","article-title":"Fault location scheme for power distribution system with distributed generation","volume":"30","author":"Alwash","year":"2015","journal-title":"IEEE Trans. Power Del."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.energy.2018.06.111","article-title":"Fault location in power distribution network with presence of distributed generation resources using impedance-based method and applying \u03c0 line model","volume":"159","author":"Dashti","year":"2018","journal-title":"Energy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1109\/TSG.2016.2566673","article-title":"High frequency impedance based fault location in distribution system with DGs","volume":"9","author":"Jia","year":"2018","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5484","DOI":"10.1109\/TPWRD.2022.3214746","article-title":"A generalized closed-from solution for wide-area fault location by characterizing the distributions of superimposed errors","volume":"37","author":"Jegarluei","year":"2022","journal-title":"IEEE Trans. Power Del."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/MPE.2018.2790818","article-title":"Distribution synchrophasors: Pairing big data with analytics to create actionable information","volume":"16","author":"Mohsenian","year":"2018","journal-title":"IEEE Power Energy Mag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1109\/TPWRS.2013.2285578","article-title":"Optimal PMU placement considering controlled islanding of power system","volume":"29","author":"Huang","year":"2014","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1109\/JSAC.2019.2951971","article-title":"Phasor measurement units optimal placement and performance limits for fault localization","volume":"38","author":"Jamei","year":"2020","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_12","first-page":"138","article-title":"Distribution network fault location based on limited PMU configuration","volume":"42","author":"Yang","year":"2022","journal-title":"Electr. Power Auto. Equip."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4640","DOI":"10.1109\/TPWRS.2019.2917794","article-title":"Real-time faulted line localization and PMU placement in power systems through convolutional neural networks","volume":"34","author":"Li","year":"2019","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_14","unstructured":"Han, Z., Shi, F., Jin, Z., Liu, Y., and Xue, G. (2025). Tuning free feeder selection and section location of high impedance grounding fault for distribution network based on the features from synchronous Lissajous curve. Power Syst. Technol., 1\u201312. Available online: https:\/\/link.cnki.net\/urlid\/11.2410.tm.20250515.1236.008."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1109\/TIA.2024.3471997","article-title":"Holistic fault Detection, classification, and localization in ADNs with optimally placed D-PMUs","volume":"61","author":"Anguswamy","year":"2025","journal-title":"IEEE Trans. Ind. Appli."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1843","DOI":"10.1109\/TPWRS.2024.3446237","article-title":"Sparse PMU placement algorithm for enhanced detection and identification of power grid events","volume":"40","author":"Yildiz","year":"2025","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6343","DOI":"10.1109\/TPWRS.2018.2832126","article-title":"Locating the source of events in power distribution systems using Micro-PMU data","volume":"33","author":"Farajollahi","year":"2018","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4295","DOI":"10.1109\/TSG.2021.3081017","article-title":"Synchronous waveform measurements to locate transient events and incipient faults in power distribution networks","volume":"12","author":"Izadi","year":"2021","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1109\/TSG.2023.3277853","article-title":"A remedy to losing time synchronization at D-PMUs, H-PMUs, and WMUs in event location identification in power distribution systems","volume":"15","author":"Ye","year":"2024","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3262","DOI":"10.1109\/TPWRD.2023.3268767","article-title":"Precise PMU-based localization and classification of short-circuit faults in power distribution systems","volume":"38","author":"Sodin","year":"2023","journal-title":"IEEE Trans. Power Del."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1109\/TPWRD.2020.2987892","article-title":"A new method for fault location in distribution networks based on voltage sag measurements","volume":"36","author":"Buzo","year":"2021","journal-title":"IEEE Trans. Power Del."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2062","DOI":"10.1109\/TPWRS.2016.2608927","article-title":"From available synchrophasor data to short-circuit fault identity: Formulation and feasibility analysis","volume":"32","author":"Azizi","year":"2017","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.1109\/TSG.2020.3031400","article-title":"A novel fault location methodology for smart distribution networks","volume":"12","author":"Mirshekali","year":"2021","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1109\/TSG.2019.2926668","article-title":"Enhance High impedance fault detection and location accuracy via \u03bc-PMUs","volume":"11","author":"Cui","year":"2020","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1109\/TPWRS.2021.3094534","article-title":"Sparse tracking state estimation for low-observable power distribution systems using D-PMUs","volume":"37","author":"Akrami","year":"2022","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3982","DOI":"10.1109\/TSG.2020.2988349","article-title":"Graph-based faulted line identification using micro-PMU data in distribution systems","volume":"11","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_27","unstructured":"(2025, May 13). Micro-Pmu Data Sheet. Available online: https:\/\/www.ronexprim.com\/upload\/userfiles\/files\/MicroPMU%20%20Data%20Sheet%20Rev1_3(1).pdf."},{"key":"ref_28","unstructured":"(2011). IEEE Standard for Synchrophasor Measurements for Power Systems. Standard No. IEEE Std C37.118.1."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1109\/61.19265","article-title":"Optimal capacitor placement on radial distribution systems","volume":"4","author":"Baran","year":"1989","journal-title":"IEEE Trans. Power Del."},{"key":"ref_30","first-page":"318","article-title":"Simultaneous placement of Tie-lines and distributed generations to optimize distribution system post-outage operations and minimize energy losses","volume":"7","author":"Shojaei","year":"2021","journal-title":"CSEE J. Power Energy Syst."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/16\/5169\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:31:39Z","timestamp":1760034699000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/16\/5169"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,20]]},"references-count":30,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["s25165169"],"URL":"https:\/\/doi.org\/10.3390\/s25165169","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2025,8,20]]}}}