Low Voltage Grid Monitoring

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Joan Lang
5 years ago
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1 Smart Grid Gotland Subproject Power Quality Low Voltage Grid Monitoring EUW Amsterdam

2 Why monitor the low voltage grid? Power outages have so far been identified only by customers, not acceptable in the future To understand how the power quality and available capacity will change over the time due to large numbers of EV and PV. Fuse has tripped Power Quality affected Lines and cables has been damaged

3 Project objectives Based on smart metering data and functions develop solutions for: A cost effective monitoring of the LV grid identifying 3-phase outages and phase loss regardless of customer calls. Benefits: Through increased quality assurance of power outage events from the metering system, creating conditions for proactive behavior regarding awareness, fault localization and customer information. An automatic, fast and precise system for customer information regarding power outages based on smart metering information. Benefits: Customers will always be aware of the status of the power supply regardless if they are at home, at work or on holiday. Continuously measure power and voltage per phase in secondary substations as well as customer sites, identifying abnormalities and negative trends like unbalanced phases and voltage drops and peaks. Benefits: The most cost-effective way to early identify upcoming problems caused by customers' new behaviors with more intermittent power such as EV and PV installations. Grid mapping functionality identifying the structure of the low voltage grid; feeders, cable cabinets and customers point of delivery. Benefits: The most cost-effective way to over time guarantee that the grid documentation is correct.

4 Smart Metering System Meter: NES 3-phase meters DC (concentrator): NES DCN 3000 NES DC 1000 Communication: ETM Purple modems AMI Head-End: SE Titanium 4 GPRS Titanium 4

Power outage detection AMI Head-End Outage events from meters and concentrators Last gasp events from concentrators GPRS Titanium 4 Smart algorithms using GIS data Secondary substation effected: Last

5 Power outage detection AMI Head-End Outage events from meters and concentrators Last gasp events from concentrators GPRS Titanium 4 Smart algorithms using GIS data Secondary substation effected: Last gasp events from DCN3000 or DC ETM modem (retrofit) identifying substations out of power, latency 2 minutes Outages in the LV grid: Outage events from meters and concentrators, quality control functions in AMI Head-End using smart algorithms and GIS data identifying 3-phase outages Response time / latency: Normally 4 to 10 minutes for an event. For a ping of meters normally 1 to 2 minutes.

Improved power outage information to customers Outage events from meters and concentrators Last gasp events from concentrators GPRS AMI Head-End Titanium 4 A prototype of a Smart

6 Improved power outage information to customers Outage events from meters and concentrators Last gasp events from concentrators GPRS AMI Head-End Titanium 4 A prototype of a Smart customer info system has been developed based on meter events and GIS data. Customers will always be updated about the status in 5 to 10 minutes. SMS service Smart Customer Info System ABB DMS

Long-term monitoring; identifying PQ and maintenance issues PQ data and events from meters and concentrator GPRS AMI Head-End Titanium 4 NES apps Continuously measure power and voltage per phase in

7 Long-term monitoring; identifying PQ and maintenance issues PQ data and events from meters and concentrator GPRS AMI Head-End Titanium 4 NES apps Continuously measure power and voltage per phase in secondary substations as well as customer sites, identifying abnormalities and negative trends like unbalanced phases, transformer overload, voltage drops and peaks. Data transferred daily from the DC to Titanium and the NES appsolution for analysis. Power Quality analysis Network planning

Grid mapping AMI Head-End Titanium 4 Interaction between meters and concentrator GPRS NES apps Grid documentation Network info system Grid mapping functionality identifying

8 Grid mapping AMI Head-End Titanium 4 Interaction between meters and concentrator GPRS NES apps Grid documentation Network info system Grid mapping functionality identifying the structure of the low voltage grid, namely how a meter is connected to cable cabinets, feeder and secondary substation. Incorrectly documented power grid can be corrected

9 Critical success factors Reliability Short response times Systems for data analytics available Documentation of the LV grid has to be reliable

10 Thanks for your attention! Lars Garpetun Vattenfall Eldistribution AB Preferred suppliers:

DISCERN demonstration sites from design to implementation.

0 DISCERN demonstration sites from design to implementation www.discern.eu The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/007 0) under