Utilizing Analytics to Model Distribution System Losses with Smart Grid Data Scott Albrechtsen BC Hydro, Load Analysis February 19, 2014
2 Author Scott Albrechtsen is a Senior Load Advisor at BC Hydro. He holds a Master s degree in Applied Economics from the University of Arizona (2007). Scott joined the BC Hydro Load Analysis Team 6 years ago doing predictive modeling and data mining for BC Hydro Rates, Load Forecast and Distribution Planning. He is a SAS Certified Programmer and Vancouver SAS User Group (VanSUG) Vice-President.
3 Agenda Business Problem Pi SCADA Distribution Feeder metering data Smart Meter (SMI / AMI) hourly data Grid Topology Estimating Loads Streetlights Non-SMI The Arithmetic Technical Losses Non-technical Losses
4 Business Problem How do we model hourly distribution grid system losses? Losses at the substation, feeder, feeder section, or transformer Technical & Non-Technical Losses
5 SCADA Feeder Metering Data We have hourly metering at different points of the distribution grid Substations, Feeders, Feeder Sections, Customers SCADA metering system (Plant Information Pi ) A single feeder (circuit) is examined here
Hourly Pi SCADA Feeder metering data (One Week) 6
7 Smart Meter (SMI / AMI) hourly data We have hourly Smart Metering at most customer points within the Distribution Grid
8 Smart Meter (SMI / AMI) hourly data We aggregate many customer kwh / hour loads along various segments of the distribution grid kwh / Hour
140 Smart Meter (SMI / AMI) hourly data Aggregated 9 120 100 kwh / Hour 80 60 40 20 0 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126 131 136 141 146 151 156 161 166 171 176 181 186 191
Grid Topology Example : Feeder 25122 XXX 10 Feeder 25122XXX
11 Grid Topology Example : Feeder 25122 XXX Example for one distribution feeder with 2,162 Residential customers and 89 commercial customers Customer Type Analogue Metered Customers SMI Meter Customers Street Light Accounts Traffic Light Accounts Total Commercial Customers 23 57 1 8 89 Residential Customers 140 2,105 0 0 2,245 Total 163 2,162 1 8 2,334
12 Estimating Loads? Not all distribution nodes & customers have hourly metering. Even in a Smart Meter (SMI) environment We must estimate unmetered loads, non-smi loads, and SMI meters with data issues
13 Transformer # Watts of Lighting 1210835383 100 19778937 100 1449355981 150 19778937 100 29956066 100 19778987 100 29955655 150 29955668 150 29955668 150 29955668 150 29955668 150 29955690 100 29955690 200 29955690 100 29955690 100 29955690 150 29955690 150 29955690 100 1449356032 150 1449356032 100 29955972 100 29956132 100 29956154 100 635456294 100 562003382 100 29956187 100 19778976 100 19778998 100 29955668 150 29955679 150 29955679 150 kwh / Hour Street-lighting
14 How do we estimate non-smi loads? 2,500 Customer kwh Billed Bi-Monthly (Pre-SMI) 2,000 1,500 Total kwh 1,000 500 0 26-May-09 02-Jun-09 09-Jun-09 16-Jun-09 23-Jun-09 30-Jun-09 07-Jul-09 14-Jul-09 21-Jul-09 Day 6 Customer Hourly kwh Consumption (Post-SMI) 5 4 Total kwh 3 2 1 0 19-Jun-09 17-Jun-09 15-Jun-09 13-Jun-09 11-Jun-09 10-Jun-09 08-Jun-09 06-Jun-09 04-Jun-09 02-Jun-09 31-May-09 29-May-09 27-May-09 26-May-09 23-Jun-09 21-Jun-09 23-Jul-09 21-Jul-09 19-Jul-09 17-Jul-09 15-Jul-09 13-Jul-09 11-Jul-09 10-Jul-09 08-Jul-09 06-Jul-09 04-Jul-09 02-Jul-09 30-Jun-09 28-Jun-09 26-Jun-09 25-Jun-09 Day
How do we estimate non-smi loads? 15 2,500 Customer kwh Billed Bi-Monthly (Pre-SMI) 6 Customer Hourly kwh Consumption (Post-SMI) 2,000 5 Total kwh 1,500 1,000 Total kwh 4 3 500 2 0 1 26-May-09 02-Jun-09 09-Jun-09 16-Jun-09 23-Jun-09 30-Jun-09 07-Jul-09 14-Jul-09 21-Jul-09 Day 0 19-Jun-09 17-Jun-09 15-Jun-09 13-Jun-09 11-Jun-09 10-Jun-09 08-Jun-09 06-Jun-09 04-Jun-09 02-Jun-09 31-May-09 29-May-09 27-May-09 26-May-09 23-Jun-09 21-Jun-09 Day 23-Jul-09 21-Jul-09 19-Jul-09 17-Jul-09 15-Jul-09 13-Jul-09 11-Jul-09 10-Jul-09 08-Jul-09 06-Jul-09 04-Jul-09 02-Jul-09 30-Jun-09 28-Jun-09 26-Jun-09 25-Jun-09 We can expand bi-monthly, monthly, or daily register kwh data into hourly data via Load Research Load Profiles
Load Research Load Profiles? 16
17 Feeder Load Components Modeled Load Customers Street Light load SMI Meter Customers Traffic Light Load
18 Feeder Load Components SMI Meter Customers Modeled Load Customers Street & Traffic Lights (very small)
Feeder Load Components 19
20 Pi SCADA Metering vs. Customer Loads Pi SCADA Metering All Customer Loads
21 Calculated Losses Losses (Technical & Non-Technical) kwh / Hour
22 What are Technical & Non-Technical Losses? Technical Losses Losses through primary drivers, secondary conductors, and distribution transformers They are a function of customer load Non-Technical Losses: Abnormalities and electricity theft A prevalent issue in British Columbia
23 Estimating Technical Losses Primary Losses Secondary Losses Feeder ID A (Primary) B (Primary) C (Primary) Series Feeder Reactor 25122 XXX 0.000000603-0.0004 1.14 3.831E-08 Bin (12 kv) A B C 0-0.1 0.00001-0.0041 2.4568 0.1-0.2 0.000004-0.0017 1.8555 0.2-0.3 0.000004-0.0046 7.3681 0.3-0.4 0.000004-0.0072 14.496 0.4-0.5 0.000004-0.0072 14.496 0.5-0.6 0.000004-0.0072 14.496 0.6-0.7 0.000004-0.0072 14.496 0.7-1.0 0.000004-0.0072 14.496 Feeder ID A coefficient (coil) A coefficient (secondary) C coefficient (core losses, units in kw) 25122 XXX 5.47026E-07 1.761E-06 0.006017749 1261 JJJ 2.01176E-07 6.03862E-07 0.001602495 2552 AAA 3.01972E-07 6.37666E-07 0.007239995 2554 AAA 4.88699E-07 9.87196E-07 0.008613023 2531 AEX 4.70728E-07 1.01248E-06 0.005430171 2532 AEX 7.01646E-07 8.89259E-07 0.00312757 2533 AEX 1.97161E-07 3.42676E-07 0.003157964 2541 AEX 9.19078E-07 2.30123E-06 0.004715778 2542 AEX 1.53944E-06 5.19576E-07 0.003636877 Best-fit A coeff (Coil) Best-fit A coeff (Secondary) Average Constant Decay Constant Decay C coeff (Core) 4 kv 0.0233-1.2389 4 kv 0.0007-0.6346 4 kv 4.3156723 12 kv 0.027784-1.2347 12 kv 0.0387132-1.2497 12 kv 17.868827 25 kv 0.025674-1.1747 25 kv 0.0387735-1.2055 25 kv 45.488023 A Coefficient = Constant * (Load ^ Decay)
24 Equations from Engineering We use these equations to determine Technical Losses as a function of Primary, Secondary Loads Feeder 25122 XXX: Primary Loss = (0.000000603*(Total load 2 ) + (-. 0.0004)*(Total Load) + 1.14) Transformer Core Loss = (5.47026E-07) *(Secondary Load 2 ) + 0.006017749) Secondary Loss = (1.761E-06) *(Secondary Load 2 ))
25 Estimated Technical Losses Transformer Core Losses Secondary Losses Primary Losses
26 Losses Non-Technical Losses Technical Losses
27 Extension The methodology can be extended to the whole distribution system with feeder metering (hundreds of points)
28 Extension The methodology can be extended to the whole distribution system with feeder metering (hundreds of meters)
29 Extension Where do we have high non-technical losses?
30 Conclusions Modeling distribution system losses is a straightforward approach that requires: A high degree of data quality Computing capacity Analytical tools Important Caveats! The Pi Metering data quality must be acceptable The Grid Topology of the Feeder must be accurate