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 Gujarat

UGVCL PGVCL

Andhra Pradesh

APCPDCL APNPDCL

Karnataka

BESCOM

Haryana

UHBVN

Development of Model

National & International Literature Review Developing an Excel Based Model Identification of Data Requirements Improvising Model with feedback from FOIR Standing Committee

Finalization of Model In consultation with

Standing Committee Respective SERC

Module 2 Agricultural background of utilities

Power Consumption in Agriculture sector

100% 3% 16% 80% 60% 40% 35% 10%

Sources of irrigation in States

1% 28% 11% 27% 5% 52% 1% 51% 29% Tube wells forms important source of irrigation in all states which consumes substantial quantum of power supply.

47% 20% 36% 29% 1% 18% 0% Andhra Pradesh Karnataka Haryana Gujarat Tubewells States Other wells Canals Tanks Agriculture sector forms a substantial part of the total power consumed 60% 50% 40% 30% 20% 10% 0% Other sources

Share of power consumption in agriculture

57% 50% 48% 36% 30% 24% APCPDCL APNPDCL BESCOM UGVCL PGVCL UHBVN

Data sources of 2007/08

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

Estimation of Coincident Factor

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 UGVCL PGVCL UHBVN Power Purchase Transmission 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

Demand Energy Customer

Explanation

Fixed in nature Vary with volume of energy consumed Depend on number of consumer served

Functions

Power Purchase Transmission Distribution

Cost Classification

Demand Related Energy Related Demand Related Demand Related Energy Related Customer Related Explained in next few slides for one utility- UGVCL

Classification of Power Purchase & Transmission Illustrative example- UGVCL- 2007/08

Functions Power Purchase Transmission

Rs Cr 2700

Demand

32.88% (Rs 888 Cr) 231 100% (Rs 231Cr)

Energy

67.12% (Rs 1812 Cr) 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) Demand 81% 70% 50% 100% Distribution- 11 KV Energy 10% 0% 0% 0% 100% 80% 80% 80% 80% 0% 0% 0% 0% 0% Cus.

9% 30% 50% 0% 0% 20% 20% 20% 20% 80% 0% 20% Distribution- LT net work Demand 52% 70% 50% 100% Energy 10% 0% 0% 0% Cus.

38% 30% 50% 0% 100% 56% 80% 80% 80% 0% 44% 0% 0% 0% 0% 0% 20% 20% 20% 80% 0% 20% Demand 20% 70% 50% 100% 100% 11% 72% 72% 72% Retail supply Energy 0% 0% 0% 0% 0% 52% 0% 0% 0% Cus.

80% 30% 50% 0% 0% 37% 28% 28% 28% 72% 0% 28% Demand 65% 70% 50% 100% 100% 62% 79% 79% 79% Distribution-Total Energy 9% 0% 0% 0% 0% 27% 0% 0% 0% Cus.

26% 30% 50% 0% 0% 11% 21% 21% 21% 79% 0% 21%

Classification of distribution costs (in Rs Cr) Illustrative example- UGVCL

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

75.86

187.20

29.30

89.27

28.36

61.36

1.84

0.99

0.85

475.04

Distribution Costs 11KV LT network Retail supply 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

Distribution 11KV Demand Energy Distribution LT network Customer Demand Energy Retail supply Customer Demand Energy 31.95

45.89

2.93

38.95

26.78

26.78

0.00

0.43

0.37

174.08

3.94

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

3.94

3.52

19.67

2.93

9.80

6.74

6.74

0.00

0.11

0.09

49.59

15.74

45.89

5.86

28.85

6.39

19.83

1.08

0.32

0.27

124.23

3.00

0.00

0.00

0.00

5.10

0.00

0.00

0.00

0.00

8.10

11.28

19.67

5.86

7.30

0.00

5.02

0.00

0.08

0.07

49.28

1.28

39.33

5.86

3.14

0.15

2.16

0.75

0.04

0.02

52.73

0.00

0.00

0.00

0.00

0.72

0.00

0.00

0.00

0.00

0.72

Distribution Total Customer Demand Energy Customer 5.14

16.86

5.86

1.22

0.52

0.84

0.00

0.01

0.01

30.46

48.98

131.11

14.65

70.95

17.64

48.77

1.84

0.79

0.67

335.40

6.94

0.00

0.00

0.00

7.71

0.00

0.00

0.00

0.00

14.66

19.94

56.19

14.65

18.32

3.00

12.59

0.00

0.20

0.17

125.08

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

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 Sample Feeder Data for 24 Hours of a day

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

0100

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

0200

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

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

0700

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

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

0900

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

1000

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

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

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

1400

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

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

1700

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

Months Apr May Jun Jul Aug Sep Peak Timings

8:00 AM 6:00 AM 7:00 AM 8:00 AM 8:00 AM 9:00 AM

Correspon ding Feeder data

3.62

5.33

3.34

2.25

0.89

1.72

Months Oct Nov Dec Jan Peak Timings

12:00 PM 9:00 AM 11:00 AM 5:00 AM

Feb

2:00 PM

Mar

12:00 AM

Average Corresp onding Feeder data

5.19

3.60

4.81

4.47

4.98

1.93

3.51

Max feeder load = 9.25 MW CF= Agri demand during system peak/ Max peak = 3.51/9.25 = 37.97%

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

Agricultural Consumption As per annual accounts Losses attributable to agriculture Estimated to match annual accounts Energy Input to agri Sum of above two

Calculations

5837 MU 1900MU 7737 MU Load factor (LF) Coincident Factor (CF) Non Coincident Peak (NCP) Coincident Peak (CP) Ratio of CP Derived from Sample Feeder Data Derived from Sample Feeder Data Energy input/ (8.76* LF) NCP * CF CP/System peak 41.97% 37.37% 2104 MW 799 MW 37.09%

A D C B

Step 6 - Block approach to asses energy component of power purchase cost

Merit Order Stack for 2007/08 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

Growth Block

Power purchase over and above the base block

Base Block

Power Purchase for 2005/06 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 12000 10000 8000 6000 4000 2000 0

“Growth Block” “Base Block” Y million kWh X million kWh

Base Year Relevant Year Agriculture 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

Functionalised & Classified Cost of UGVCL( Rs Cr) Allocation of Cost to Agricultural Category (Rs Cr) Per unit Cost to agriconsumers (Rs /Kwh)

Demand

887.63

0.56

Energy

1811.73

329.21

1073.93

1.84

Customer Transmission charges Distribution Total Total Cost Demand

231.50

Energy Customer Demand

296.96

Energy

19.41

Customer

114.66

3361.88

85.86

0.15

110.14

0.19

11.55

0.02

27.86

0.05

1638.55

2.81

Block approach On basis of Coincident peak 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

Illustrative Example UGVCL

Particulars

Energy Sold to agri Revenue from sale to agriculture Total Cost of Supply to agri Subsidy from govt Cross Subsidy

Units

MU Rs Cr Rs Cr Rs Cr Rs Cr 5837 658 1638 577 404

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