Improving Distribution Circuit Performance without Circuit Rebuilds. John Lauletta, CEO

Transcription

1 Improving Distribution Circuit Performance without Circuit Rebuilds John Lauletta, CEO

2 Maintenance Strategies Reliability Centered Maintenance Reactive Maintenance (Run To Failure) Preventive Maintenance (Time Based) Predictive Maintenance (Conditions Based) Proactive Maintenance (Improvement) Small, non critical items Inconsequential, not likely to fail Redundant Subject to wear Consumable Known failure pattern Random Failure Pattern Not Subject to wear PM Induced Failures Root Cause Failure Analysis (RCFA) Failure Mode Effects Analysis (FMEA)

3 Predictive Maintenance (PdM) To use data from an entire process to find any measurable characteristics that may serve to warn that these detrimental situations are approaching. PdM techniques are designed to help determine the condition of inservice equipment in order to predict when maintenance should be performed. This approach promises cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted. PdM inspections are performed while equipment is in service, thereby minimizing disruption of normal system operations. Adoption of PdM can result in substantial cost savings and higher system reliability.

4 Predictive Maintenance (PdM) RF Emission Grid Inspection Ultrasonic Detection Infrared Detection Visual Inspection

5 Impacts of Maintenance Strategies Periodic/Preventive Maintenance Failure Rate Predictive Maintenance Early Failure Period Constant Failure Period Wear-out Failure Period

6 PdM How? To evaluate equipment condition, predictive maintenance utilizes non-destructive testing technologies such as infrared photography, ultrasonic acoustic, radio frequency (RF) emissions, corona detection, vibration analysis, sound level measurements, oil analysis, and other specific online tests.

7 PdM Why? Benefits of PdM Strategies Maintenance costs - down by 50% Unexpected failures - reduced by 55% Repair and overhaul time - down by 60% Spare parts inventory - reduced by 30% 30% increase in machinery MTBF 30% increase in uptime

8 Applying a PdM Strategy to the Grid 1. Assess System Condition 2. Schedule Maintenance 3. Measure Results 4. Repeat Process

9 U.S. Non Weather-Related Outages on the Electric Distribution System 31% of outages are caused by failing equipment 32% of outages are caused by trees Data Source: Miscellaneous 19% Animals 18%

10 Maintenance Techniques 31% of outages are caused by failing equipment 32% of outages are caused by trees Miscellaneous 19% Animals 18% Data Source:

11 Detecting Equipment Failure Device Insulator Failure Mechanism Internal Damage Contamination External Damage Dry Band Arcing Leakage Tracking Failure Detection Technology RF US-AC IR Failure Mechanism

12 Detecting Equipment Failure Device Lightning Arrester Failure Mechanism MOV Damage Contamination External Damage Dry Band Arcing Leakage Tracking Failure Detection Technology RF US-AC IR

13 Detecting Equipment Failure Device Cutout Failure Mechanism Internal Damage Contamination External Damage Dry Band Arcing Leakage Tracking Failure Detection Technology RF US-AC IR

14 Detecting Equipment Failure Device Transform er Bushing Damage Contamination Internal Arcing Low Oil Failure Detection Technology RF US-AC IR Failure Mechanism

15 Detecting Equipment Failure Use Technologies that measure specific failure symptoms Apply Technologies in most cost-effective manner Manage conditions-based analytics for proactive maintenance action Technical Tutorials

16 Utility Experience with PdM Programs Case Studies

17 Case Study: PG&E (EEI TD&M, Oct, 2016)

18 Case Study: UNITIL (T&D World, Oct. 2015)

19 Case Study: COSERV (RE Magazine, Oct. 2016)

20 Process & Technologies Exacter s predictive process utilizes two technologies and proprietary analysis to identify non-temporary & consistent, problematic conditions that are related to the overhead electric system Predictive Process 1. Patented Radio Frequency (RF) Technology Captures PD & EMI emissions present in the field Correlates emissions with GPS location 2. Proprietary Analysis (Failure Signature Library) Analyzes and discriminates field data to identify specific structures where arcing, leaking, & tracking are present 3. Ultrasonic Acoustic Technology Field Engineers visit identified structure Pinpoint component responsible for problematic conditions

21 Process & Technologies Exacter Radio Frequency Assessment Data collection Capture Partial Discharge & EMI Correlate with GPS Multiple passes Non-temporary Consistent Failure Signature Analysis Analyze & Discriminate Field Data Identify emissions related to overhead system Specific location where PD/EMI is present

22 Exacter Process & Technologies The 1,161 RED Failure Signature Events are captured by the EXACTER RF Assessment. The Failure Signature Analysis identified 77 BLUE Maintenance Groups where problematic conditions (PD/EMI) are present.

23 Exacter Process & Technologies Ultrasonic Field Locating Exacter Field Engineer visit identified structure Confirm presence of PD/EMI Identify specific component(s) responsible for problematic condition

24 Deteriorated Equipment Population (7 year, 2 million structure survey)

25 U.S. Lightning Density

26 Lightning Arrestors 0% Cutouts 6% Transmission Posts 14% formers 3% tors % Transformers 4% Insulators 4% Dead Ends 14% Regional Deteriorated Equipment Findings Mis 7% Lightning Arrestors 4% Cutouts 12% Insulators Deadends 4% 7% Misc HW 7% Transmission Posts 2% Transformers 2% Lightning Arrestors 7% Cutouts 3% Dead Ends 12% Misc HW 1% Grounds 2% Transformers 0% Insulators 0% Lightning Arrestors 17% Cutouts 2% Deadends 3% Misc HW 2% B Transmission Posts Pin Insulators 10% 55% ransformers 4% ulators 4% C Pin Insulators 69% Non-Utility n Insulators Trans Post Insulators 6% 2% 74% Pin Insulators 57% Dist nsulators 15% Lightning Arrestors 55% Pin Insulators 42% Dea 1 Misc HW 1% ors Dead Ends 4% Transformers 6% Ground 2% Lightning Arrestors Cutouts Ligh Dead Gro Ends Tra Misc HW Dea Pin Pin Insulators Dis Tra Insulators Non Transformers Transmission Posts

27 Hidden Damage No Protection

28 Obvious Physical Damage No Protection Deterioration

29 Laboratory Specimen Test Setup Arrester Under Test RF Emission Instrumentation Adjustable HV AC Source Antenna Array and Ground Plane

30 Comparing New and Deteriorated Arresters Current Sensing Resistor is 25 ohms Resistive voltage divider = 1000/1 Leading current is typical until cutoff voltage is reached 58 Field samples were reviewed New Specimen Deteriorated Specimen

31 RF Emission Spectrum Deteriorated Specimen Emission Spectrum Linear Frequency scale 0 to 1.5 GHz Historical and Instantaneous analysis shown

32 Demodulated RF Emission Analysis End of RF 0.56 MCOV Onset of Failure 0.67 MCOV Condition Signature Development Sensor correlates demodulated emission characteristics to failure signature

33 Case Study South Central U.S. Central Texas Service Territory 6 counties 190,000+ customers served 4,600 Distribution Miles 2,200 Overhead Miles 2,400 Underground Miles

34 Data Analysis: Historical Interruption Data The customer provided the most recent 12 months of interruption data October 1, 2013 September 30, 2014 Outage Cause CMI # of Interruptions % of CMI Equipment 1,619, % (Approx) IEEE Equipment Cause Codes: ** Excludes IEEE days for MEDs // Excludes Momentaries 300 Material or Equipment Failure 400 Decay/Age of Material or Equipment 410 Corrosion/Abrasion of Material or Equipment

35 Data Analysis: Exacter Pareto Analysis Exacter Analysis normalizes the dataset to allow for meaningful comparison of the circuits Divide Total EQ CMI / OH Miles for each circuit The new metric used to compare circuits is Equipment CMI / OH Mile Exacter ranks each circuit by the Equipment Related CMI / OH Mile Circuits with the highest Equipment CMI / OH Mile provide the greatest opportunity to improve performance and reliability

36 Data Analysis: Exacter Pareto Analysis Feeders that represent greatest opportunity for improvement

37 2015 Pilot Assessment Circuit Selection The pilot covers portions of 67 circuits totaling 180 miles of overhead distribution - The majority of overhead miles are 3-phase infrastructure - Eastern area of Service territory - High growth area The option has the opportunity to impact 993,338 equipment related customer minutes of interruption (CMI) - 29 Equipment related outages

38 2015 Pilot Assessment Area

39 2015 Pilot Assessment: Equipment Findings Survey Results

40 2015 Pilot Assessment: Component Finds Exacter assessment identified 1 component every 2.68 miles 3-phase overhead // co-located circuits // overbuild Density of service territory Presence of protective devices on system Exacter assessed 6,446 poles 180 assessed miles = 6,446 poles 67/6,446 = 1.03% of poles with problematic conditions 98.97% of assessed infrastructure does not have presence of problematic conditions

41 2015 Pilot Assessment: Field Report

42 2015 Pilot Assessment: Considerations & Conclusions May 2015: Wettest month on record for Dallas-Ft. Worth area 4.4 million lightning strikes More than 2013 or 2014 total Correlate lightning strike data with Exacter assessment Maintenance Operations for Identified Components Further Lightning Arrester investigation Identify use for Exacter assessments in future maintenance operations

43 Summary and Remaining Work Arresters are a critical component in electric grid equipment reliability Arresters are most deteriorated in areas of greatest need: Southeast/Northeast U.S. Visual damage is not typically apparent and does not necessarily indicate state of protection element RF emissions characterize deterioration that impacts performance In 58 samples, 57 showed deterioration of protective ability More field samples will be evaluated in laboratory conditions to optimize failure signature discrimination and source location for utility maintenance planning