1 Big Data Analytics Applications in Distribution Operations and Risk Assessment Edwin C. (Ed) Carlsen Manager - Distribution Management Systems, Georgia Power eccarlse@southernco.com, e.carlsen@ieee.org
2 Panel Title / Topic Big Data Analytics Applications Distribution Operations Risk Assessment Trigger some ideas and discussion
3 Big Data and Analytics Just AMI? GPC before AMI 53 million reads per year
4 Big Data and Analytics Just AMI? GPC before AMI 53 million reads per year GPC after AMI 154 billion reads per year not including meter events
Lot s of other data with the distribution grid 5 4.4M Customers 3.4 million distribution poles 1.6 million street lights 1.4 million transformers 150,000 mi. of distribution line
6 Customer Data AMI Data Distribution Grid Data Outage Tamper Temperature Reverse power flow Current Voltage Phase angles Power factor Frequency Business Decisions Operations Billing Revenue Protection Marketing Customer Satisfaction
Analytics = Data Insight Action 7
Analytics = Data Outage Reports 8 Customer Phone or web site SCADA AMI Electrical Model
Analytics = Data Insight Outage Reports OMS Work Agenda 9
Analytics = Data Insight Action Outage Reports OMS Work Agenda OMS Crew Actions 10
11 OMS Enhancement AMI Data Objectives o o Enhance outage response and restoration Improve outage communication to customers Utilize power off and power restore signals from AMI Utilize pinging of meter to obtain current status Simple Concept, but involves complexities B A C
Filtering (analytics) required for AMI-OMS 12
13 AMI-OMS: Enhanced Analytics What % of outages occur in the middle of the night (or the day) without customer calls? What % of AMI meters report outage events? What % of AMI-reported events create incorrect outage predictions (due to data quality, timing or other issues)? How timely was the data reported? Do weather conditions impact data quality? How does data volume impact quality? Can we use the AMI outage info to correct data issues? Data sources needed: AMI, OMS, SCADA, GIS, CIS
Fault Location Analysis (FLA) The Question Can we utilize fault data from electronic relays to accurately locate faults on distribution circuits? 14
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OMS FLA System Integration Data flow from relays via SCADA, ICCP Integrating impedance data and field device data into OMS New functionality in OMS New work processes SCADA ICCP B R 17
Fault Location Analysis (FLA) The Question Can we utilize fault data from electronic relays to accurately locate faults on distribution circuits? The Answer Yes! Predicts in less than 1 minute, often within 5-6 spans of trouble Enhanced Analytics Desired: How often is it correct? How close to actual trouble? If incorrect, why? What additional information is needed? 18
FLA Pinpointing Fault Location / GPS Position Capture Capture trouble location 19
Utilizing AMI Voltage Data 20 Weekly extraction - voltages outside preset ranges
AMI Voltage using Geospatial Views 21
AMI Voltage using Geospatial Views 22
AMI Voltage using Geospatial Views 23
AMI Voltage using Geospatial Views 24
Outages and Reliability Business Intelligence 25
Outages and Reliability Business Intelligence 26
Outages and Reliability Business Intelligence 27
Outages and Reliability Geospatial Historic Analysis 28
Outages Major Storm Restoration 29 Friday 2/7 - Sunday 2/9 Monitoring weather forecast Monday 2/10 Storm Center activated GPC and APC teams in Pennsylvania recalled Mutual Assistance requested Tuesday 2/11 Storm Teams began travel to forecast area Five large staging sites fully operational in the forecast area Total Customers Out by Hour Sunday 2/16 Final stages Clean up begins Wednesday 2/12 Winter precipitation began; outages begin in Metro and North GA Outages expand to Statesboro and East GA by evening Thursday 2/13 Transmission system began to experience outages Resources shifted to Central and East Regions Wintery weather exits GA Service restored to 481,000 customers by 8pm Friday 2/14 Power restored to Metro South and North GA Storm resources shifted to CSRA Service restored to 641,000 customers by 8pm Saturday 2/15 All transmission restored Service restored to 695,000 customers (99%) by 9pm
Key Restoration Facts 30 Customers 701,000 sustained outages to customers Transmission 250 substations impacted 15 structures damaged or destroyed 30+ spans of wire repaired Distribution 700+ poles replaced 3,500+ spans of wire repaired 900+ transformers replaced Personnel Approximately 8,200 Southern Company employees, contractors, and mutual assistance partners supported the restoration.
Outages Major Storm Outage Communication 31
Outages Customer Communication 32
20000 Outage Alert (Notifi) Registrations ifactor Registrations by Channel 33 15000 Voice Email Text 10000 5000 0 11/5 11/12 11/19 11/26 12/3 12/10 12/17 12/24 12/31 1/7 1/14 1/21 1/28 2/4 2/11 2/18 2/25 3/4 3/11 Text Email Voice Pre-Storm 1.4 channels per account 86% 32% 17% 65 accounts added per day Post (including) 1.2 channels per account 80% 22% 22% Storm 222 accounts added per day
Outages Customer Communication 34
35 Customer Outage Communication - Enhanced Analytics Are we providing accurate/timely outage information? Is the information getting to customers in a timely manner? Are customers receiving the information they want? Are we under/over communicating? Are the business processes and technology adequate to provide desired outcome? How much is does it (or will it) cost per channel? Per event? Data sources needed: OMS, Outage Communication Systems (maps, text, voice, email), CIS, Accounting.
Key Technologies / Applications for Distribution Varied and Evolving Outage / Network Management System (OMS/NMS) Dist. Supervisory Control and Data Acquisition (DSCADA) Mapping / Geographic Information System (GIS) Business Intelligence (BI) Distribution Automation (DA) Mobile Work Management System (MWM) Short Cycle (meter orders, outage response) Automated Metering Infrastructure (AMI) Customer Information Systems (CIS) and various communication channels 36 IEEE / PES GM - DMS Task Force Meeting July 22, 2013
DA IEDs Integrated Distribution Operations Suite Sub. Relays Remote tags Fault Data AMI Data Warehouse AFISR Self Healing Distributed/Central DSCADA Device Control Analog and Status AMI Power ON/OFF Status Voltage excursions* External Outage Communication Maps Text, Voice, Email GIS (Geographical Information System) All Dist Assets Electrical Model Source Link Customer to Asset Substation Internals OMS/NMS Dynamic Electrical Model Prediction engine Geospatial and Tabular GUI Crew Management Analysis / Simulation Tools Event Database Fault Location Analysis Two way to DSCADA Outage BI Near Real Time Historical Tabular, graphical Geospatial CIS / VRU Customer Data Source Work Order Initiation Customer Calls (inbound) Active Outage status, ETR (outbound) Mobile WM Various Work Order types Outage Event Dispatch Field Order Updates / Completion WM BI Near Real Time Historical Tabular, graphical 37
Which application is at the Center of the Universe? High Quality, Timely DATA! 38
39 Summary Wide ranging data and systems to run our business GPC has been doing various forms of operational analytics using various tools for several years Many opportunities for much, much more, in ways much different than before Have to be careful to do value analysis Exciting times!