Assessment of Cost of
Service to Agriculture
Consumers
New Delhi
June 17, 2010
Structure of Presentation
Module 1: Introductory
Module 2: Agricultural background of utilities
Module 3: Important Consideration in assessing agriculture CoS
Module 4: Model for determination of cost of service
Module 5: Conclusions
Module 1
Introductory
Key objective of the study
To formulate methodology to determine the
cost of service for agricultural consumers and
examination of issues related to it taking into
account quality of supply, including hours of
supply, voltage fluctuations, reliability of
supply etc.
Selection of utilities
Utilities selected have
significant agricultural
load
Approach to the study
Selection of
Utilities
Development
of Model
Gujarat
UGVCL
PGVCL
Andhra Pradesh
APCPDCL
National & International
Literature Review
Standing
Committee
Identification of Data
Requirements
Respective
SERC
BESCOM
Haryana
UHBVN
In consultation
with
Developing an Excel Based
Model
APNPDCL
Karnataka
Finalization
of Model
Improvising Model with feedback
from FOIR Standing Committee
Module 2
Agricultural background of utilities
Power Consumption in Agriculture
sector Sources of irrigation in States
100%
1%
3%
16%
52%
60%
35%
40%
10%
Tube wells forms important
source of irrigation in all states
which consumes substantial
quantum of power supply.
28%
80%
51%
11%
27%
1%
29%
5%
47%
20%
36%
1%
29%
18%
0%
Andhra Pradesh
Karnataka
Haryana
Gujarat
States
Canals
Tanks
Tubewells
Other wells
Other sources
Share of power consumption in agriculture
57%
60%
40%
Agriculture sector forms a
substantial part of the total
power consumed
50%
48%
50%
36%
30%
24%
30%
20%
10%
0%
APCPDCL APNPDCL
Data sources of 2007/08
BESCOM
UGVCL
PGVCL
UHBVN
Module 3
Important Consideration in
assessing agriculture CoS
Important considerations in
assessing Agriculture CoS….i
 Agriculture gets supply during odd hours of the day
 In most cases agriculture category gets supply during odd
hours
 Few exceptions are there. E.g. UGVCL- Time schedule for supply to
agriculture is announced weekly and is divided into various group
which receives 8 hours of power during the day on rotational basis
 Administered peak for agriculture
 Usually agriculture category does not receive round the
clock supply. Supply is regulated and rostered leading to
“Administered Peak”
 Flexibility in usage hours could further increase class peak
and coincident peak
Important considerations in
assessing Agriculture CoS….ii
 Low growth of agriculture power demand
 Growth in agriculture consumption lower than other
categories
 Higher cost of power purchase due to growth of overall
demand need not be allocated to agriculture
 Poor quality of power supply to agriculture
 Often characterised with poor voltage profile and
unreliable supply
 Tariff design for agriculture consumers should take this
into consideration
Important considerations in
assessing Agriculture CoS….iii
 Diversity in agriculture power demand over the year
 Wide variations in demand across seasons &cropping pattern
 Methodology to determine CoS to reflect the seasonality in
agriculture demand
 Estimation of losses incurred in supplying to agriculture
category
 Agriculture category has substantial unmetered consumption
 Losses are not known appropriately (including the breakup in
terms of technical and commercial component)
 Proper treatment to losses in methodology for assessing CoS
Module 4
Model for determination of cost
of service
Model for Determination of CoS
Functionalisation of
Costs:
Power Purchase
Transmission
Distribution
Classification of Costs
:
Demand
Energy
Customer
Sample Feeder Data
Derivation of Load Curve
Class Load Factor
Estimation of Coincident Factor
Estimation of Coincident Peak
Estimation of
Cross
Subsidies
Allocation of Costs to
agriculture category
Estimation of cost of supply to
agriculture consumer category
Block Approachfor assessing
energy component of power
purchase
Information Requirement










Utility system load details
Power purchase details (base year and relevant year)
Energy details of the utility
Profit & loss accounts of the utility
Balance sheet and its respective schedules of the utility
Revenue details of the utility
Detailed composition of all costs incurred by the utility
Details of technical and commercial losses in agricultural category
Voltage level wise classification of cost
Load data of the sample feeders
Sources for Data Collection
Secondary sources such as Tariff orders, Profit & Los Accounts, Trial balance, Balance sheet etc.
Discussions with the concerned utilities and State Electricity Regulatory Commission.
Load studies are based on sample survey in consultation with the concerned utilities.
Step 1 - Functionalisation of costs
Process of dividing the total cost of the distribution utilities on basis of the functions
performed - power purchase, transmission and distribution
Power Purchase Function
All costs related to purchase of power; inclusive of in-house
generation cost, power purchase through long term, short term power
purchase contracts, trading and unscheduled interface mechanism.
Transmission Function
All costs associated with the transfer of power from power plant to
boundaries of utility; predominantly fixed costs
Distribution Function
All costs associated with the transfer of power from the transmission
system through the distribution system to the consumer (end user);
inclusive of costs incurred by the utility in activities such as R&M,
A&G, and employees related expenses etc.
Costs breakup between different
functions
100%
80%
60%
40%
20%
0%
APCPDCL APNPDCL BESCOM
Power Purchase
UGVCL
Transmission
PGVCL
UHBVN
Distribution
Power Purchase costs forms about 75-85% of the total utility cost
Transmission cost forms about 5-10% of the total utility cost
Distribution cost forms about 10-15% of the total utility cost
Source: Annual Report of 2007/08 of respective utilities
Step 2 - Classification of costs
Cost
Classification
Explanation
Functions
Cost
Classification
Demand
Fixed in nature
Power
Purchase
Demand Related
Energy Related
Energy
Vary with volume of
energy consumed
Transmission
Demand Related
Distribution
Demand Related
Energy Related
Customer Related
Customer
Depend on number
of consumer served
Explained in next few slides for one utility- UGVCL
Classification of Power Purchase &
Transmission
Illustrative example- UGVCL- 2007/08
Functions
Rs Cr
Demand
Energy
Power Purchase
2700
32.88%
67.12%
(Rs 888 Cr) (Rs 1812 Cr)
Transmission
231
100%
(Rs 231Cr)
0%
Power Purchase cost is classified into fixed and variable
costs in the ratio as stated in the tariff order
Transmission cost being fixed in nature is classified as
demand cost
Classification of distribution costs
Illustrative example- UGVCL
Costs related to Distribution function are first classified voltage wise and
thereafter based on the nature of costs based on the discussion with the
officials of the utility
Distribution
R&M
Employee Costs
A&G expenses
Other debits
Prior period items
Interest on WC
Depreciation
Interest & Financial Charges
Income Tax & RoR
Expenses capitalised
(Interest and Finance Charges)
Distribution- 11 KV
Demand Energy
81%
10%
70%
0%
50%
0%
100%
0%
100%
0%
80%
0%
80%
0%
80%
0%
80%
0%
80%
0%
Cus.
9%
30%
50%
0%
0%
20%
20%
20%
20%
20%
Distribution- LT net work
Demand Energy
Cus.
52%
10%
38%
70%
0%
30%
50%
0%
50%
100%
0%
0%
100%
0%
0%
56%
44%
0%
80%
0%
20%
80%
0%
20%
80%
0%
20%
80%
0%
20%
Retail supply
Demand Energy
20%
0%
70%
0%
50%
0%
100%
0%
100%
0%
11%
52%
72%
0%
72%
0%
72%
0%
72%
0%
Cus.
80%
30%
50%
0%
0%
37%
28%
28%
28%
28%
Distribution-Total
Demand Energy
65%
9%
70%
0%
50%
0%
100%
0%
100%
0%
62%
27%
79%
0%
79%
0%
79%
0%
79%
0%
Cus.
26%
30%
50%
0%
0%
11%
21%
21%
21%
21%
Classification of distribution costs
(in Rs Cr)
Illustrative example- UGVCL
Distribution
Costs
Repairs & Maintenance
Employee Costs
Administration & General expense
Depreciation & Related
Interest on WC
Interest & Financial Charges
Other Debits (incl. Bad debts)
Provison of Income Tax
Rate of Retun
SUB-TOTAL
Less
Expenses capitalised
Net Prior Period Charges/Credits
TOTAL
11KV
LT network Retail supply
75.86
187.20
29.30
89.27
28.36
61.36
1.84
0.99
0.85
475.04
39.41
65.56
5.86
48.75
15.49
33.51
0.00
0.54
0.46
209.59
30.03
65.56
11.72
36.15
11.48
24.85
1.08
0.40
0.34
181.62
6.42
56.19
11.72
4.36
1.39
3.00
0.75
0.05
0.02
83.91
Demand
31.95
45.89
2.93
38.95
26.78
26.78
0.00
0.43
0.37
174.08
50.79
-6.67
430.92
27.74
-1.16
183.01
20.57
-0.76
161.81
2.48
-4.73
86.16
22.16
-1.16
153.08
Distribution 11KV
Distribution LT network
Retail supply
Distribution Total
Energy Customer Demand Energy Customer Demand Energy Customer Demand Energy Customer
3.94
3.52
15.74
3.00
11.28
1.28
0.00
5.14
48.98
6.94
19.94
0.00
19.67
45.89
0.00
19.67
39.33
0.00
16.86
131.11
0.00
56.19
0.00
2.93
5.86
0.00
5.86
5.86
0.00
5.86
14.65
0.00
14.65
0.00
9.80
28.85
0.00
7.30
3.14
0.00
1.22
70.95
0.00
18.32
0.00
6.74
6.39
5.10
0.00
0.15
0.72
0.52
17.64
7.71
3.00
0.00
6.74
19.83
0.00
5.02
2.16
0.00
0.84
48.77
0.00
12.59
0.00
0.00
1.08
0.00
0.00
0.75
0.00
0.00
1.84
0.00
0.00
0.00
0.11
0.32
0.00
0.08
0.04
0.00
0.01
0.79
0.00
0.20
0.00
0.09
0.27
0.00
0.07
0.02
0.00
0.01
0.67
0.00
0.17
3.94
49.59
124.23
8.10
49.28
52.73
0.72
30.46
335.40
14.66
125.08
0.00
0.00
3.94
5.58
0.00
44.01
16.41
-0.76
108.58
0.00
0.00
8.10
4.16
0.00
45.13
1.79
0.00
50.94
0.00
-4.73
5.45
0.70
0.00
29.76
40.37
-1.92
296.96
0.00
-4.75
19.41
10.43
0.00
114.66
Step 3- Sample Feeder Analysis
 Identification of sample feeders
 Predominantly agriculture load (80%)
 Representative of the different circle to capture the geographical spread
 Identification of sample days for data collection
 18 days uniformly spread across the entire year to capture the seasonality
in agricultural demand of the utility.
 1 day of utility peak day
 Derivation of load curve from the above data
 Estimation of Class Load Factor
 Average Demand/ Peak demand
 Estimation of load loss factor
 Empirical formula by EPRI to estimate energy losses
 (0.3 *Load Factor +0.7 (Load Factor)^2
Step 4 - Estimation of Coincident
Factor
Coincident factor is the ratio of agricultural demand at the time of the
system peak to the agricultural peak demand
Estimation of CF using average peak
•Agriculture category faces administered peak with lack of voluntary
consumption, thus usage of single peak gives biased results
•States witness large variation in monthly peak, thus usage of average
peak will capture the overall seasonality during the year.
Steps in Calculating Coincident Factor
 Ascertain the time and magnitude of system peak for each of the 12
months separately
 Establish the corresponding load from the sample feeder data (average if
there are more than two readings for the month)
 From the above, take a simple average of above 12 monthly readings.
 This average divided by the feeder sample peak gives the CF
Illustration- UGVCL Estimation of CF
Selected Days
for sample
collection
Prescribed
Date*
06.04.2007
22.04.2007
02.05.2007
19.05.2007
14.06.2007
15.07.2007
25.07.2007
15.08.2007
04.09.2007
26.09.2007
08.10.2007
18.11.2007
01.12.2007
11.12.2007
25.12.2007
12.01.2008
14.01.08
20.02.2008
14.03.2008
Sample Feeder Data for 24 Hours of a day
0100
0200
6.073
5.503
5.892
3.780
2.184
0.561
1.504
0.247
0.370
0.635
5.043
7.033
7.445
7.312
7.401
6.231
6.818
6.236
8.300
4.452
5.620
5.088
3.652
2.564
0.592
1.529
0.296
0.246
0.803
4.775
6.825
6.278
6.391
6.219
6.064
6.185
5.886
8.253
0300
5.814
5.586
5.003
3.685
2.760
0.681
1.430
0.328
0.246
0.686
4.856
6.421
6.824
6.538
6.606
5.998
5.906
4.319
6.920
0400
5.836
5.586
5.716
3.523
2.543
0.900
1.612
0.228
0.599
0.837
4.833
5.134
6.940
5.824
7.100
6.590
4.703
4.859
6.719
0500
4.607
4.270
5.932
1.243
3.375
0.997
2.460
0.562
1.018
0.650
4.043
4.979
6.105
5.807
6.207
4.356
4.583
3.902
8.164
0600
0700
5.363
5.929
5.937
4.729
3.979
1.814
2.900
0.827
1.307
0.701
3.366
5.112
4.310
3.868
2.669
4.323
5.805
3.596
6.874
4.196
8.393
5.718
2.727
3.339
1.953
3.550
0.866
1.994
1.050
3.648
5.079
4.837
4.280
2.071
2.772
6.419
3.547
5.339
0800
0900
2.620
4.622
4.150
2.530
3.267
1.415
3.084
0.885
2.284
1.575
2.741
4.101
5.239
4.041
2.406
1.650
7.181
4.962
5.059
1000
2.783
4.324
4.995
2.606
5.327
1.229
2.429
0.685
2.448
0.999
4.156
3.599
5.463
4.747
4.449
3.693
5.431
6.892
3.247
1.286
4.579
4.545
4.266
4.166
1.341
2.249
0.682
2.375
1.541
5.482
4.210
5.556
4.018
4.383
3.823
5.699
6.591
3.125
Months
Peak
Timings
Corresp
onding
Feeder
data
Oct
12:00 PM
5.19
Nov
9:00 AM
3.60
Dec
11:00 AM
4.81
Jan
5:00 AM
4.47
Months
Peak Timings
Correspon
ding
Feeder
data
Apr
8:00 AM
3.62
May
6:00 AM
5.33
Jun
7:00 AM
3.34
Jul
8:00 AM
2.25
Aug
8:00 AM
0.89
Feb
2:00 PM
4.98
Sep
9:00 AM
1.72
Mar
12:00 AM
1.93
Average
3.51
1100
1.286
4.555
4.562
4.218
3.993
0.741
2.300
0.952
2.315
1.308
5.191
4.281
5.456
5.172
3.788
4.598
5.542
6.403
3.023
1200
3.616
8.370
4.435
4.000
4.354
0.803
2.263
0.872
2.184
1.376
5.192
5.650
7.480
3.450
3.762
4.720
7.296
3.745
1.890
1300
1400
2.403
7.644
5.903
5.041
5.502
0.842
3.853
2.029
4.760
1.270
6.623
7.307
8.097
4.526
5.078
6.767
9.095
7.045
3.605
1.070
6.856
5.770
5.288
5.517
0.426
4.070
2.429
2.627
1.328
7.270
7.191
7.408
5.920
5.094
8.830
9.247
7.240
1.930
1500
4.320
4.217
5.931
3.999
4.732
0.625
3.663
2.194
2.116
2.652
6.529
7.239
7.253
4.673
4.062
7.198
7.075
6.559
3.463
1600
1700
4.486
3.800
4.545
4.365
4.977
0.828
3.480
2.252
1.445
2.425
7.253
6.732
7.162
5.673
5.361
6.707
7.014
6.299
3.343
Max feeder load =
9.25 MW
CF= Agri demand during
system peak/ Max peak
= 3.51/9.25
= 37.97%
4.486
4.373
4.512
4.126
4.761
0.991
3.407
2.169
0.865
1.891
4.343
6.762
6.592
4.973
5.427
6.522
1.933
4.159
1.686
Step 5 - Estimation of Coincident
Peak
Coincident peak is the contribution of the agricultural demand to the
system peak demand
Coincident Peak = Non Coincident peak * Coincident Factor)
Estimating Non Coincident Peak
When segregated technical and commercial losses available
NCP = (Consumption and commercial losses in MU)/(LF*8.76)
+(Technical Loss in MU)/(LLF*8.76)
When losses could not be segregated into technical and
commercial losses
NCP = (consumption + total loss)/ (LF*8.76)
Illustration- UGVCL- Estimation of CP
Particulars
Remarks
Calculations
Agricultural Consumption
As per annual accounts
5837 MU
Losses attributable to agriculture
Estimated to match annual accounts
1900MU
Energy Input to agri
Sum of above two
7737 MU
Load factor (LF)
Derived from Sample Feeder Data
41.97%
Coincident Factor (CF)
Derived from Sample Feeder Data
37.37%
Non Coincident Peak (NCP)
Energy input/ (8.76* LF)
2104 MW
Coincident Peak (CP)
NCP * CF
799 MW
Ratio of CP
CP/System peak
37.09%
Step 6 - Block approach to asses energy
component of power purchase cost
Merit Order Stack for
2007/08
D
Growth Block
Power purchase
over and above
the base block
C
B
Base Block
Power Purchase
for 2005/06
A
Different consumer categories pose different
weights on the incremental power purchase over the
years. Each category should be charged in
accordance with their respective share of the
incremental power purchase
Estimate the per
unit variable
cost for growth
block (X2)
Estimate the per
unit variable
cost for base
block (X1)
Variable cost for
agri: Incremental
Input to agri * X2
Variable cost for
agri: Base year
Input to agri * X1
Variable
cost of
power
purchase
attributable
to
agriculture
category
Illustrative example
14000
“Growth Block”
12000
Power Purchase(Million
kWh)
10000
8000
“Base Block”
6000
Y million kWh
4000
X million kWh
2000
0
Base Year
Agriculture
Relevant Year
Other categories
Cost of PP for Agriculture = Variable cost of base block * X MU +
Variable cost of growth block * Y MU (incremental increase in agri sales)
Step 7 - Allocation of classified
costs
Allocation of Demand Costs
For all functions demand cost is allocated on basis of coincident peak demand
Allocation of Energy Costs:
For power purchase energy cost component is allocated on the basis of block
approach (previous slide)
For transmission & distribution function, energy cost component is allocated on
the basis of ratio of agricultural consumption to the total consumption of the utility
Allocation of Customer Costs:
For three functions, customer related cost is allocated on the basis of the ratio
of number of agricultural consumers to the total consumers of the utility.
Sum total of the different cost (demand, energy and customer related
cost) allocated to the agri consumers gives the total cost of supplying
power to agricultural consumers as incurred by the particular utility.
Illustration- UGVCL- Allocation of cost
Power Purchase Cost
Transmission charges
Energy
Functionalised &
Classified Cost
of UGVCL( Rs Cr)
887.63
1811.73
231.50
296.96
19.41
114.66
3361.88
Allocation of Cost to
Agricultural Category
(Rs Cr)
329.21
1073.93
85.86
110.14
11.55
27.86
1638.55
0.56
1.84
0.15
0.19
0.02
0.05
2.81
Block
approach
Demand
On basis of
Coincident
peak
Energy
Customer
Demand
Energy
Total
Cost
Demand
Per unit Cost to
agriconsumers
(Rs /Kwh)
Customer
Distribution Total
Customer
In ratio of energy
sent to Agricultural
consumers to total
power purchase
In ratio of
Agricultural
consumer to
total
Step 7 - Estimation of Cross
Subsidies
Cross Subsidy to
agricultural consumers = Total Cost of supplying power to agri
consumers – revenue from sale of power to
agri – Subsidy provided by the government
Particulars
Illustrative
ExampleUGVCL
Units
Energy Sold to agri
MU
5837
Revenue from sale to
agriculture
Rs Cr
658
Total Cost of Supply to agri
Rs Cr
1638
Subsidy from govt
Rs Cr
577
Cross Subsidy
Rs Cr
404
Module 5
Conclusions
Conclusions……i
 Move towards the actual cost to serve pricing principle
 It would introduce transparency in rate designing and hence in
subsidy/ cross subsidy assessment
 Special attention to be taken in allocating power purchase costs
 Power purchase costs form significant share (75-80%) in overall
costs (fixed and variable)
 Further, fixed costs ranges between 20% to 50% of the total PP
cost (depending on vintage/type/technology of plant)
 Agriculture CoS to also reflect quality and reliability of supply
 Reliabity of supply -Agriculture consumers mostly get restricted
supply
 When consumers pre informed: No discount on cost of supply
 When consumers not pre informed: Discount on cost of supply
Conclusions……ii
 Quality of supply – Often characterised by poor voltage profile
 Modify the total cost of power purchase on account of agriculture consumers
considering the average voltage deviations beyond permissible limit
 Aggregating the penalty levied on licensees due to poor quality supply and,
thereby, moderating the power purchase cost
 Use of appropriate load curves
 Need of load research study for assessment of power demand of
consumer class
 Sample feeders selected to have predominant load of
agricultural consumers
 Need to capture seasonal diversity in estimation of CF
 Agriculture demand varies across year due to different seasons,
cropping pattern and rainfall
Conclusions……iii
 Capture the diversity in agriculture demand by taking into
account sample load data spread across the year
 Estimation of CF to be based on average monthly peak
 Agriculture faces administered peak
 Consumption curve for agriculture would be different had they
been provided 24hrs access to power
 Use of single “peak” for estimating CoS imposes higher burden
on this category and does not take into account the effect of
seasonality
 Need to change the assets/expenditure accounting
practices
 Utilities should maintain the voltage wise inventory of assets
Thank You