{"version":"1.0","provider_name":"Salzburg Research Forschungsgesellschaft","provider_url":"https:\/\/www.salzburgresearch.at\/en\/","author_name":"dgnad","author_url":"https:\/\/www.salzburgresearch.at\/en\/author\/dgnad\/","title":"Automated fault diagnostics in the power grid - Salzburg Research Forschungsgesellschaft","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"ZopafdBaqG\"><a href=\"https:\/\/www.salzburgresearch.at\/en\/2022\/automated-fault-diagnostics-in-the-power-grid\/\">Automated fault diagnostics in the power grid<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/www.salzburgresearch.at\/en\/2022\/automated-fault-diagnostics-in-the-power-grid\/embed\/#?secret=ZopafdBaqG\" width=\"600\" height=\"338\" title=\"&#8220;Automated fault diagnostics in the power grid&#8221; &#8212; Salzburg Research Forschungsgesellschaft\" data-secret=\"ZopafdBaqG\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/www.salzburgresearch.at\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/www.salzburgresearch.at\/wp-content\/uploads\/2022\/04\/c_shutterstock_Sawat-Banyenngam.jpg","thumbnail_width":1000,"thumbnail_height":545,"description":"Salzburg Research tapped the potential of telecom diagnostics data for automated fault diagnostics in the low-voltage network for an electricity distribution network operator: with the help of machine learning, the cause of approximately 70 per cent of low-voltage network faults can be detected automatically without additional hardware. The starting position The client operates approx. 5,300 transformer stations throughout the supply area. The sooner a fault can be detected, the quicker the fault repair can be initiated. Therefore, the electricity distribution network operator wanted to extend its fault diagnostics in the high and medium voltage network to the low voltage network. Until now, customers had to report faults by telephone. In the low-voltage networks of every transformer station there are also telecom devices that can be used for fault diagnosis. However, it was unclear whether the available telecom network diagnostic data contained sufficient information to detect a fault in the low-voltage network. Machine learning helps identify [&hellip;]"}