using economic costs to design time-of-use prices: a case study american public power association...

Using Economic Costs to Design Time-of-Use Prices: A Case Study

American Public Power Association

Business & Financial Conference

Hyatt Regency

Savannah, Georgia

September 13-16, 2009

Presentation by:

John M. KellyDirector of Economics and ResearchAmerican Public Power AssociationWashington, D.C.

2

Largely a “How to” Presentation …

Rather than “Why?”

But …

3

Why Economic Costs?

Should Rate Patterns be Based on:

Tradition … inertia … and happenstance;

OR

A careful weighing of the relevant factors [costs] with a view of guiding consumers to make efficient use of the facilities that are available?

— William Vickrey, 1955

4

Why Economic Costs?

1. We are bombarded with information;

2. We have to sort the trivial from the important/relevant;

3. If we do not, we are lost in terminal overload;

4. The criteria for sorting must involve context and theory-- the larger perspective.

[For example, “What does the term cost mean, what is relevant and what is not?”].

Stephen Jay Gould

5

Why Economic Costs?

Generally, Pragmatically …

When prices reflect costs, good economic things

happen when they don’t, bad things

happen

Intuitively what competitive business do

They Work

6

Why Economic Costs?

Relevancy – Focuses on relevant cost of business decisions (how “bottom line” affected)

Efficiency Efficient use of current

facilities (lowers average Cost/price of Electricity Service

Efficient consumption (residential & business)

Sustainability -- Reflects prices in competitive market

7

Why Economic Costs?

Equity – Eliminates cross-class subsidies

Transparency (v. traditional cost of service)

8

Efficiency and the Structure of Electricity Prices

Rate Structure Capacity Utilization?

Flat Rate ? ? ? ? ?

? ?

? ?

? ?

Time-Varying

Rate ? ? ? ? ?

9

Efficiency and the Structure of Electricity Prices

Rate Structure Capacity Utilization?

Flat Rate 45% --55%

Time-Varying

Rate 65% -- 75%

10

APPA DEED Project

Sponsored by APPA Demonstration of Energy-Efficient Developments

Practical and Useful TOU Pricing Methodology

Grand Haven (MI) Board of Light & Power 13,000 customers $26 million revenues

11

Task Essentially is to …

1. Forecast structure of wholesale power prices based on past prices and utility budget information …

2. Adjusting for market power and price anomalies so to reflect economic costs

3. Determine seasons and daily time periods

12

APPA DEED Project (continued)

Commons costs of power supply (generation plants/wholesale purchases) not allocated

Wholesale Prices used to design structure of retail prices

Quantitative methods used to determine seasons and time periods (versus visual inspection of graphs)

13

Steps for Developing TOU Prices Based on Economic Costs

(Short-Run Marginal Costs)

Collect and Review 4-5 years of data on: -- Hourly Wholesale Market Prices -- Utility Sales and Revenues

Determine Seasons

Determine Daily Cost/Price Periods for Each Season

Calculate Average Period Costs

Estimate Revenue Impacts

Adjust TOU Price Structure to Recover All Power Supply Costs

14

Basic Data

Four-Five Years of Data

Wholesale Prices – MPPA (project) node prices in MISO wholesale market;

Utility Sales and Revenue

Budgets

15

Organization & Preliminary Analysis of

Data

1. Review 4-5 years of monthly hourly data, first graphically to identify and appropriately adjust for excessive prices and anomalies.

2. Compute average hourly prices for week day and weekend (plus holiday) hours.

3. Adjust increased hourly price by appropriate amounts based on future year budget estimates.

16

Mean Hourly Costs (May-Sept)

2040

6080

100

LMP

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour

May JuneJuly AugustSeptember

Mean LMP by Hour of Day (2007)

17

Precision/Accuracy

Objection: Forecasts are not precise

But … relative to what?

Essentially flat prices (or some related standard);

or

Time-varying costs of electricity power supply?

18

Costs: Traditional, Economic, Competitive,

and Wholesale2

46

810

1214

16Ce

nts

per K

Wh

0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

SR Marginal Social Cost

Competitive Cost

Traditional Cost

a

24

68

1012

1416

Cent

s pe

r KW

h

0 2 4 6 8 10 12 14 16 18 20 22 24

Hour

Traditional Cost

SR Marginal Social Cost

Wholesale Market Cost

b

19

Precision/Accuracy

“One puts more food on the table by shooting at flying ducks than at floating decoys.”

William Vickrey

20

Methods for Identifying Seasons and Daily Time

Periods

1. Visual Inspection of Graphs

2. Visual Inspection of Graphs

- aided by “data mining,”

ANOVA, standard

deviations, pivot tables, etc.

3. Economic Estimates of Welfare Losses

21

Methods for Identifying Seasons and Daily Time

Periods

4. *Cluster Analysis

5. *Regression Trees

22

Mean Hourly Costs (May-Sept)

2040

6080

100

LMP

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour

May JuneJuly AugustSeptember

Mean LMP by Hour of Day (2007)

23

Determining Seasons (Step 1): Correlation

Matrix

  May June July August September

May 1        

June 0.9569 1      

July 0.9361 0.996 1    

August 0.9454 0.988 0.989 1  

September 0.9218 0.92 0.901 0.9053 1

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Determining Seasons (2): Sums of Absolute Differences of Hourly Costs (mill/kWh)

Year 2007

May – June = 297

June – July = 267

Average of 2005 and 2006 July Costs

May – June = 297

June – July = 159

25

Mean Hourly Costs (January-May and

September-December)20

4060

8010

0LM

P

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour

Jan FebMar Apr

May SepOct NovDec

(Weekdays, 2007)Mean Hourly LMP

26

Determining Hourly Cost Periods(Step 1): Cluster Analysis

Dendrogram (Summer Weekdays)0

5010

015

0L2

diss

imila

rity m

easu

re

1 6 7 2 3 4 5 8 24 9 23 10 22 11 12 19 20 21 13 18 14 15 17 16

(Weekdays, 2007)Dendrogram for Summer Cluster Analysis (June, July, August)

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Determining Hourly Cost Periods (Step 2): Duda &

Hart Stopping Rule

Clusters Je(2)/Je(1) Pseudo T-squared

1 0.2113 82.12

2 0.2927 26.58

3 0.2618 25.38

4 0.4515 4.86

5 0.303 11.5

6 0.1772 13.93

7 0.239 6.37

8 0.3233 6.28

9 0.2383 15.98

10 0.0912 9.97

11 0.2526 2.96

12 0 .

13 0 .

14 0 .

15 0.1229 7.13

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Determining Hourly Cost Periods (Step 3) Reviewing Resulting Hourly Clusters/Deciding on

Number of Periods

1st Cluster: 1 – 7

2nd Cluster: 8 – 9 and 23 – 24

3rd Cluster: 13 – 18

4th Cluster: 10 – 12 and 19 – 22

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Hour Mon Tue Wed Thu

FriHour Mon Tue Wed Thu Fri

1           1          

2           2          

3           3          

4     27     4     27    

5           5          

6           6          

7           7          

8     46     8          

9           9          

10           10     62    

11     73     11          

12           12          

13           13          

14           14          

15     97     15     97    

16           16          

17           17          

18           18          

19           19          

20     71     20          

21           21     61    

22           22          

23     41     23          

24           24          

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Revenue by Season and Time Period -- Hourly

(LMP) Cost

Season

Winter Middle Summer Total

Weekday 1 595,050 447,902 480,594 1,523,546

2 1,699,176 4,615,539 959,737 7,274,452

3 409,970 402,696 1,828,104 2,640,770

4 1,331,961 . 1,108,097 2,440,058

Weekend 1 208,561 326,723 209,184 744,468

2 522,091 702,699 387,931 1,612,721

3 213,315 . 271,325 484,640

Total 4,980,124 6,495,560 5,244,792 16,720,655

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Revenue by Season and Time Period (Mean Cost)

Season

Winter Middle Summer Total

Weekday 1 546,847 485,891 493,896 1,526,634

2 1,715,492 4,319,627 979,230 7,014,349

3 410,311 426,118 1,828,664 2,665,092

4 1,411,395 . 1,149,352 2,560,747

Weekend 1 198,711 347,215 173,016 718,942

2 507,990 774,611 352,574 1,635,175

3 224,944 . 251,704 476,648

Total 5,015,689 6,353,462 5,228,436 16,597,587

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Revenue Adjusted for Price Elasticity of

Demand

Summer Middle Winter Total

Weekday 1 530,340 507,701 559,514 1,597,555

2 962,622 4,836,860 1,695,001 7,494,483

3 1,826,963 426,415 412,776 2,666,154

4 1,097,885 . 1,381,278 2,479,163

Weekend 1 178,786 361,239 199,170 739,195

2 354,700 789,834 520,240 1,664,774

3 245,793 . 220,664 466,457

TOTAL 5,197,089 6,922,050 4,988,646 17,107,785

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Recovery of Power Supply Costs

Determine Non-Power Supply Costs for Utility

Determine Non-Power Supply Costs by Customer Class

No Readily Accessible Estimates for GHBLP Estimated 70-75 percent 10-15 Percent Increase above

wholesale-cost based price structure (Lincoln Electric System estimates

about 10 percent)

Mark up Price Structure Uniformly

Mark up Price Structure Selectively

34

DEED Methodology versus Traditional (FAC)

Ratemaking

1. Standard/Core Methodology for Determining Costs and Prices (not secondary or option)

2. Power Supply Costs (generation and purchased power) not allocated

3. Rate Structure Based on Wholesale Power Market Prices

35

DEED Methodology versus Typical TOU

Pricing

SRMC instead of LMRC

More Pricing Periods

Wider Price Range (Highs and Lows)

More Reliance on Quantitative Methods for Determining Pricing Periods

36

DEED Methodology versus Real-Time Pricing

Real-Time Pricing -- Ideal or Goal but:

Complexity

Cost

Customer: Understanding and Convenience

37

Again … Accuracy/Precision

versus Relevance

“One puts more food on the table by shooting at flying ducks than at floating decoys.”

William Vickrey