utilizing analytics to model distribution system...
TRANSCRIPT
Utilizing Analytics to Model Distribution System Losses with
Smart Grid Data
Scott Albrechtsen BC Hydro, Load Analysis
February 19, 2014
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.
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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
Business Problem • How do we model hourly distribution grid system losses?
– Losses at the substation, feeder, feeder section, or transformer
– Technical & Non-Technical Losses
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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
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Hourly Pi SCADA Feeder metering data (One Week)
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Smart Meter (SMI / AMI) hourly data
• We have hourly Smart Metering at most customer points within the Distribution Grid
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Smart Meter (SMI / AMI) hourly data 8
kWh
/ Hou
r
We aggregate many customer kWh / hour loads along various segments of the distribution grid
Smart Meter (SMI / AMI) hourly data
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0
20
40
60
80
100
120
1401 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
kWh
/ Hou
r
Aggregated
Grid Topology Example : Feeder 25122 XXX
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Feeder 25122XXX
Grid Topology Example : Feeder 25122 XXX
• Example for one distribution feeder with 2,162 Residential customers and 89 commercial customers
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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
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
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Street-lighting 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
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kWh
/ Hou
r
How do we estimate non-SMI loads?
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Customer Hourly kWh Consumption (Post-SMI)
0
1
2
3
4
5
6
26-May-09
27-May-09
29-May-09
31-May-09
02-Jun-09
04-Jun-09
06-Jun-09
08-Jun-09
10-Jun-09
11-Jun-09
13-Jun-09
15-Jun-09
17-Jun-09
19-Jun-09
21-Jun-09
23-Jun-09
25-Jun-09
26-Jun-09
28-Jun-09
30-Jun-09
02-Jul-09
04-Jul-09
06-Jul-09
08-Jul-09
10-Jul-09
11-Jul-09
13-Jul-09
15-Jul-09
17-Jul-09
19-Jul-09
21-Jul-09
23-Jul-09
Day
Tota
l kW
h
Customer kWh Billed Bi-Monthly (Pre-SMI)
0
500
1,000
1,500
2,000
2,500
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
Tota
l kW
h
How do we estimate non-SMI loads? 15
Customer Hourly kWh Consumption (Post-SMI)
0
1
2
3
4
5
6
26-May-09
27-May-09
29-May-09
31-May-09
02-Jun-09
04-Jun-09
06-Jun-09
08-Jun-09
10-Jun-09
11-Jun-09
13-Jun-09
15-Jun-09
17-Jun-09
19-Jun-09
21-Jun-09
23-Jun-09
25-Jun-09
26-Jun-09
28-Jun-09
30-Jun-09
02-Jul-09
04-Jul-09
06-Jul-09
08-Jul-09
10-Jul-09
11-Jul-09
13-Jul-09
15-Jul-09
17-Jul-09
19-Jul-09
21-Jul-09
23-Jul-09
Day
Tota
l kW
h
Customer kWh Billed Bi-Monthly (Pre-SMI)
0
500
1,000
1,500
2,000
2,500
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
Tota
l kW
h
We can expand bi-monthly, monthly, or daily register kWh data into hourly data via Load Research Load Profiles
Load Research Load Profiles? 16
Feeder Load Components
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Street Light load
SMI Meter Customers Traffic Light Load
Modeled Load Customers
Feeder Load Components
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SMI Meter Customers
Modeled Load Customers
Street & Traffic Lights (very small)
Feeder Load Components
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Pi SCADA Metering vs. Customer Loads
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Pi SCADA Metering
All Customer Loads
Calculated Losses Losses (Technical & Non-Technical)
21 kW
h / H
our
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
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Estimating Technical Losses Primary Losses
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
Secondary Losses
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)
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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
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 load2) + (-. 0.0004)*(Total Load) + 1.14)
Transformer Core Loss = (5.47026E-07) *(Secondary Load2) + 0.006017749)
Secondary Loss = (1.761E-06) *(Secondary Load2))
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Estimated Technical Losses 25
Transformer Core Losses
Primary Losses
Secondary Losses
Losses 26
Non-Technical Losses
Technical Losses
Extension 27
The methodology can be extended to the whole distribution system with feeder metering (hundreds of points)
Extension
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The methodology can be extended to the whole distribution system with feeder metering (hundreds of meters)
Extension
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Where do we have high non-technical losses?
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
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