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However, the measurements are imprecise, and not every node is instrumented. Therefore, the measured data must be corrected and augmented with pseudo-measurements to obtain an accurate and complete picture of the distribution grid. Hence, we present and evaluate a novel method for distribution grid monitoring. This method uses smart plugs as measuring devices and a feature propagation algorithm to generate pseudo-measurements for each grid node. The feature propagation algorithm exploits the homophily of buses in the distribution grid and diffuses known voltage values throughout the grid. This novel approach to deriving pseudo-measurement values is evaluated using a simulation of SimBench benchmark grids and the IEEE 37 bus system. In comparison to the established GINN algorithm, the presented approach generates more accurate voltage pseudo-measurements with less computational effort. This enables frequent updates of the distribution grid monitoring with low latency whenever a measurement occurs.<\/jats:p>","DOI":"10.1186\/s42162-024-00427-y","type":"journal-article","created":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T10:31:46Z","timestamp":1731407506000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Distribution grid monitoring based on feature propagation using smart plugs"],"prefix":"10.1186","volume":"7","author":[{"given":"Simon","family":"Grafenhorst","sequence":"first","affiliation":[]},{"given":"Kevin","family":"F\u00f6rderer","sequence":"additional","affiliation":[]},{"given":"Veit","family":"Hagenmeyer","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,12]]},"reference":[{"issue":"18","key":"427_CR1","doi-asserted-by":"publisher","first-page":"4756","DOI":"10.3390\/en13184756.","volume":"13","author":"S Fatima","year":"2020","unstructured":"Fatima S, P\u00fcvi V, Lehtonen M (2020) Review on the PV Hosting Capacity in Distribution Networks. 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