BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:US/Eastern BEGIN:DAYLIGHT DTSTART:20220313T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20221106T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20220705T182754Z UID:115FA8FB-E4B6-48F8-A2A0-687995CA5759 DTSTART;TZID=US/Eastern:20220609T093000 DTEND;TZID=US/Eastern:20220609T105000 DESCRIPTION:Data Analytics from the Application of Smart Meters (AMI)\n\nDa te: THURSDAY\, June 9th\, 2022\n\nPlace: WEB - ON-LINE TECHNICAL SEMINAR – See Link below and in Flyer\n\nAbstract:\n\nSmart meters\, also known as Advanced Metering Infrastructure or AMI\, have been installed across mo st of the distribution networks in the United States. There is a tremendou s amount of available data collected through this metering network. Howeve r\, distilling this data into useful information and insights is a tremend ous challenge. Without a way to get information out of the data\, there wo uld be little added value to installing smart meters and the associated ca pital investment. In this webinar\, three industry experts will talk about how they apply automation processes and data analysis techniques to get u seful information for a variety of power system applications including iss ue identification\, voltage analysis\, load modeling\, and transformer hea lth monitoring.\n\nPDHs: 2 professional development hours (PDHs) may be is sued to those completing this course.\n\nAgenda: \nSeminar Outline:\n\n9:3 0 am to 9:40 am Opening Remarks\n\n9:40 am to 10:10 am Identifying Issues from AMI Meters’ Instrumentation Profiles\n\n10:10 am to 10:40 am AMI Da ta for Voltage Analysis and Load Modeling in Distribution Planning\n\n10:4 0 am to 10:50 am Break\n\n10:50 am to 11:00 am Chapter Announcement\n11:00 am to 12:00 am Big Data Analytics for Transformer Health at Oncor\n\nPres entation Abstract and Speaker Bios:\n\nMark Hubbard - Dominion Energy\n\nP resentation title: Identifying Issues from AMI Meters’ Instrumentation P rofiles\n\nAbstract: AMI meters are capable of reporting a complete instru mentation profile of their service characteristics remotely. Using this da ta\, service issues are identified\, and field personnel can be dispatched to perform maintenance. This presentation will review the process for the automation of this analysis and some examples of service issues identifie d.\n\nMark Hubbard has worked in metering for Dominion Energy for more tha n 14 years. After his internship\, he was hired as the metering engineer r esponsible for evaluating new metering technology and capabilities. Today\ , Mark supervises the Metering Engineering & Planning group.\n\nMelissa Pe skin - Dominion Energy\n\nPresentation title: AMI Data for Voltage Analysi s and Load Modeling in Distribution Planning\n\nAbstract: Voltage data was one of Dominion’s early drivers for AMI meters\, and it will be key to the rollout of Voltage Optimization (VO) through the Grid Transformation P lan and Demand-Side Management programs. Real-world examples of AMI voltag e will be shown to demonstrate how service issues and inadequate facilitie s are identified and upgraded to improve customer power quality. The prese ntation will also touch on how interval load data from AMI meters is used to improve load models in Distribution Planning. Continued enhancement of the load model will be a key driver of Integrated Distribution Planning to respond to an evolving distribution grid.\n\nMelissa Peskin\, P.E.\, has worked on Dominion Energy’s Conservation Voltage Reduction and Voltage O ptimization programs since their inception in 2009. She started with the c ompany in 2005 as an intern and worked in Electric Distribution Planning u ntil 2011. She joined Dominion Voltage Inc.\, where she delivered Dominion ’s patented CVR solution to utilities across the United States and Canad a\, as well as leading the product management team. She returned to Electr ic Distribution Grid Planning in 2018\, where she works on building and ma intaining the distribution system electric model and performing system-wid e planning and reliability analyses.\n\nDr. Yannan Sun - Oncor Electric De livery\n\nPresentation tile: Big Data Analytics for Transformer Health at Oncor\n\nAbstract: As the largest utility company in the state of Texas (U SA)\, Oncor provides power to more than 3.7 million customers. Monitoring and maintaining the assets in Oncor’s system is a crucial task that impr oves system reliability and customer satisfaction. We apply powerful compu ting platforms and advanced analytics to data collected from over 3.6 mill ion smart meters at 15 minute intervals\; this is truly big data analytics . This talk will present a few use cases using AMS data for transformer he alth at Oncor. In distribution systems\, transformer failures could be cau sed by\, for example coil damage or overload issues. Reactive replacements may take 4-5 hours\, but proactive replacements usually take less than on e hour. We use 15-minute voltage data collected from AMS meters to detect pre-fault signatures so that the transformers can be replaced proactively before failure. Load data is also analyzed to discover overloaded transfor mers. We developed a ranking system to prioritize all the distribution tra nsformers in Oncor’s system. The impact of these projects will also be s hared.\n\nYannan Sun is a data scientist at Oncor Electric Delivery. She i s currently in Distribution Operation Center Technical Support Group\, and previously in Maintenance Strategy and Transmission Planning. She has con tributions in many data analytics use cases at Oncor by providing insights \, designing data-driven approaches and implementing machine learning algo rithms. She is also an expert on process improvement using Lean Six Sigma tools. Prior to Oncor\, she was a Senior Scientist at Pacific Northwest Na tional Laboratory in the Electricity Infrastructure group for 7 years.\n\n Virtual: https://events.vtools.ieee.org/m/315592 LOCATION:Virtual: https://events.vtools.ieee.org/m/315592 ORGANIZER:Alan.ott@dominionenergy.com SEQUENCE:16 SUMMARY:Data Analytics from the Application of Smart Meters (AMI) - Part 1 URL;VALUE=URI:https://events.vtools.ieee.org/m/315592 X-ALT-DESC:Description: <br /><p><strong><em>Data Analytics from the Applic ation of Smart Meters (AMI) </em></strong></p>\n<p><strong><u>Date:</u></s trong><strong>&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbs p\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;& nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp \;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&n bsp\;&nbsp\;&nbsp\;&nbsp\; </strong><strong>THURSDAY\, June 9th\, 2022</st rong></p>\n<p><strong><u>Place:</u></strong><strong> &nbsp\;&nbsp\;&nbsp\; &nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbs p\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;& nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp \;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\; WEB - ON-LINE &nbsp\;& nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;TECHNICAL SEMINAR &ndash\; See Li nk below and in Flyer</strong></p>\n<p><strong><u>Abstract: </u></strong>< /p>\n<p>&nbsp\;</p>\n<p>Smart meters\, also known as Advanced Metering Inf rastructure or AMI\, have been installed across most of the distribution n etworks in the United States. There is a tremendous amount of available da ta collected through this metering network. However\, distilling this data into useful information and insights is a tremendous challenge. Without a way to get information out of the data\, there would be little added valu e to installing smart meters and the associated capital investment. In thi s webinar\, three industry experts will talk about how they apply automati on processes and data analysis techniques to get useful information for a variety of power system applications including issue identification\, volt age analysis\, load modeling\, and transformer health monitoring.</p>\n<p> &nbsp\;</p>\n<p><strong><u>PDHs:</u></strong><strong> 2 </strong>professio nal development hours (PDHs) may be issued to those completing this course .</p><br /><br />Agenda: <br /><p><strong><u>Seminar Outline:</u></strong> </p>\n<p>9:30 am to 9:40 am&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp \;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&n bsp\; Opening Remarks</p>\n<p>9:40 am to 10:10 am&nbsp\;&nbsp\;&nbsp\;&nbs p\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;& nbsp\;&nbsp\;&nbsp\; Identifying Issues from AMI Meters&rsquo\; Instrument ation Profiles</p>\n<p>10:10 am to 10:40 am&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nb sp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\; AMI Da ta for Voltage Analysis and Load Modeling in Distribution Planning</p>\n<p >10:40 am to 10:50 am&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbs p\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\; Break</p>\n<p>10:50 am to 11 :00 am &nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbs p\;&nbsp\;&nbsp\;&nbsp\; Chapter Announcement<br />11:00 am to 12:00 am&nb sp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\; &nbsp\;&nbsp\;&nbsp\; Big Data Analytics for Transformer Health at Oncor</ p>\n<p>&nbsp\;</p>\n<p><strong><u>Presentation Abstract and Speaker Bios:< /u></strong></p>\n<p>&nbsp\;</p>\n<p><strong>Mark Hubbard - Dominion Energ y</strong></p>\n<p><strong>Presentation title</strong>: Identifying Issues from AMI Meters&rsquo\; Instrumentation Profiles</p>\n<p><strong>Abstract </strong>:&nbsp\; AMI meters are capable of reporting a complete instrumen tation profile of their service characteristics remotely.&nbsp\; Using thi s data\, service issues are identified\, and field personnel can be dispat ched to perform maintenance.&nbsp\; This presentation will review the proc ess for the automation of this analysis and some examples of service issue s identified.</p>\n<p>Mark Hubbard has worked in metering for Dominion Ene rgy for more than 14 years.&nbsp\; After his internship\, he was hired as the metering engineer responsible for evaluating new metering technology a nd capabilities.&nbsp\; Today\, Mark supervises the Metering Engineering & amp\; Planning group.</p>\n<p>&nbsp\;</p>\n<p><strong>Melissa Peskin - Dom inion Energy</strong></p>\n<p><strong>Presentation title</strong>: AMI Dat a for Voltage Analysis and Load Modeling in Distribution Planning</p>\n<p> <strong>Abstract</strong>: Voltage data was one of Dominion&rsquo\;s early drivers for AMI meters\, and it will be key to the rollout of Voltage Opt imization (VO) through the Grid Transformation Plan and Demand-Side Manage ment programs. Real-world examples of AMI voltage will be shown to demonst rate how service issues and inadequate facilities are identified and upgra ded to improve customer power quality. The presentation will also touch on how interval load data from AMI meters is used to improve load models in Distribution Planning. Continued enhancement of the load model will be a k ey driver of Integrated Distribution Planning to respond to an evolving di stribution grid.</p>\n<p>Melissa Peskin\, P.E.\, has worked on Dominion En ergy&rsquo\;s Conservation Voltage Reduction and Voltage Optimization prog rams since their inception in 2009. She started with the company in 2005 a s an intern and worked in Electric Distribution Planning until 2011. She j oined Dominion Voltage Inc.\, where she delivered Dominion&rsquo\;s patent ed CVR solution to utilities across the United States and Canada\, as well as leading the product management team. She returned to Electric Distribu tion Grid Planning in 2018\, where she works on building and maintaining t he distribution system electric model and performing system-wide planning and reliability analyses.</p>\n<p>&nbsp\;</p>\n<p><strong>Dr. Yannan Sun - Oncor Electric Delivery</strong></p>\n<p><strong>Presentation tile</stron g>: Big Data Analytics for Transformer Health at Oncor</p>\n<p><strong>Abs tract</strong>: As the largest utility company in the state of Texas (USA) \, Oncor provides power to more than 3.7 million customers. Monitoring and maintaining the assets in Oncor&rsquo\;s system is a crucial task that im proves system reliability and customer satisfaction. We apply powerful com puting platforms and advanced analytics to data collected from over 3.6 mi llion smart meters at 15 minute intervals\; this is truly big data analyti cs. This talk will present a few use cases using AMS data for transformer health at Oncor. In distribution systems\, transformer failures could be c aused by\, for example coil damage or overload issues. Reactive replacemen ts may take 4-5 hours\, but proactive replacements usually take less than one hour. We use 15-minute voltage data collected from AMS meters to detec t pre-fault signatures so that the transformers can be replaced proactivel y before failure. Load data is also analyzed to discover overloaded transf ormers. We developed a ranking system to prioritize all the distribution t ransformers in Oncor&rsquo\;s system. The impact of these projects will al so be shared.</p>\n<p>Yannan Sun is a data scientist at Oncor Electric Del ivery. She is currently in Distribution Operation Center Technical Support Group\, and previously in Maintenance Strategy and Transmission Planning. She has contributions in many data analytics use cases at Oncor by provid ing insights\, designing data-driven approaches and implementing machine l earning algorithms. She is also an expert on process improvement using Lea n Six Sigma tools. Prior to Oncor\, she was a Senior Scientist at Pacific Northwest National Laboratory in the Electricity Infrastructure group for 7 years.</p>\n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR