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8/7/2019 Zarnikau Price 012907

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Price Elasticity of Demand inCurrent Zonal Market

PUCT Demand Response Workshop (Project No. 32853)

Jay Zarnikau

Frontier Associates

January 2007


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Research Questions

To what degree do industrial energy consumers respond towholesale prices in the current zonal ERCOT market?

Can we quantify the average response?

Is the response to a likely 4-CP event similar to theresponse to a high balancing energy price?


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Two Papers

Zarnikau, Jay, Greg Landreth, Ian Hallett, and SubalKumbhakar, Industrial Energy Consumer Response toWholesale Prices in the Restructured Texas ElectricityMarket, forthcoming in Energy the international journal.

Zarnikau, Jay and Ian Hallett, Aggregate CustomerResponse to Wholesale Prices in the Restructured ERCOTMarket, draft January 2007. (This one is still a work inprogress.)


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What Weve Done

In our first study:

We modeled the 20 largest industrial electricity consumers inthe CenterPoint service area.

We do not know the actual identities of these consumers. All data are for 2003.

In our second study:

We modeled the entire aggregated industrial load in ERCOT(all customers with IDRs).

Data are from January 2, 2002 to April 2005.


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The Math. It gets worse!

With demand functions:

* ( ) 2 2{[ ]/( ) ( /2)[ ]/( ) } * * *ii i ii i YY i ij jy

X b b b d U F! S P 'P P'SP 'PU U

*j ij j kj ijk j k

j k j

aJ H I


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In the first study

Data were aggregated into 3-hour blocks (which may causesome endogeneity concerns if demand response changesmarket prices within the 3-hour period).

Each of the 20 energy consumers were modeled separately,

but the aggregated load of all 20 was also modeled.

It takes about an hour to estimate each model on a PC.


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In the second study

15-minute data were directly used.

Fourier series were used, so that the model could actuallybe solved.

96 demand functions are estimated (one for each 15-minuteinterval in a day).

21 MB of computer code, and another 20 MB of data.

A model run takes about 3 hours on a PC.


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So, what did we find?

Just looking at the data suggests that some customersrespond to balancing energy prices and 4 CPs. Others donot.


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Elasticities

Keep in mind that a price elasticity of demand is thepercentage change in demand associated with a 1%change in the price.

(% change in Quantity)/(% change in Price)

These are averages.

In this context:

Own-price elasticity is the change in demand in period tassociated with a change in the price in period t

Cross-price elasticity is the change in demand in one periodassociated with the change in price in another period.


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Price Elasticity of Demand Estimates forAggregated Block of Industrial Load forLargest Industrial in Houston


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Price Elasticity of Demand Estimates for

Each of the 20 Industrials in HoustonTable 3

Estimated Own-Price Elasticities

Consumer Mi

.- . . -6 . . 6-9 . . 9- - . . -6 . . 6-9 . . 9 . .-Mi

.1 -0.0052 -0.0065 -0.0043 -0.0028 -0.0035 -0.0015 -0.0112 -0.0153

2 -0.0008 -0.0010 -0.0011 -0.0014 -0.0029 -0.0022 -0.0077 -0.0106

3 -0.0032 -0.0029 -0.0002 -0.0034 -0.0094 -0.0025 -0.0143 -0.0069

4 -0.0035 -0.0047 -0.0015 -0.0015 -0.0012 -0.0012 -0.0036 -0.0016

5 -0.0017 -0.0004 -0.0033 -0.0040 -0.0047 -0.0026 -0.0102 -0.00966 -0.0050 -0.0043 -0.0071 -0.0022 -0.0215 -0.0357 -0.0248 -0.0232

7 -0.0024 -0.0004 -0.0002 -0.0026 -0.0147 -0.0074 -0.0167 -0.0223

8 -0.0024 -0.0012 -0.0007 -0.0012 -0.0034 -0.0020 -0.0037 -0.0037

9 -0.0031 -0.0019 -0.0009 -0.0040 -0.0063 -0.0020 -0.0069 -0.0068

10 -0.0007 -0.0003 -0.0006 -0.0015 -0.0008 -0.0007 -0.0058 -0.0041

11 -0.0003 -0.0007 -0.0026 -0.0067 -0.0022 -0.0027 -0.0064 -0.0074

12 -0.0002 -0.0058 -0.0003 -0.0052 -0.0028 -0.0010 -0.0152 -0.0099

13 -0.0003 -0.0004 -0.0012 -0.0004 -0.0002 -0.0003 -0.0019 -0.0004

14 -0.0019 -0.0019 -0.0008 -0.0014 -0.0009 -0.0007 -0.0023 -0.0016

15 -0.0008 -0.0032 -0.0005 -0.0005 -0.0016 -0.0022 -0.0038 -0.0036

16 -0.0001 -0.0003 -0.0001 -0.0041 -0.0030 -0.0019 -0.0075 -0.0088

1

7-

0.0004-

0.001

9-

0.0004-

0.001

6-

0.0008-

0.0005-

0.0025-

0.002718 -0.0064 -0.0029 -0.0027 -0.0017 -0.0068 -0.0049 -0.0145 -0.0130

19 -0.0002 -0.0001 -0.0004 -0.0004 -0.0012 -0.0004 -0.0026 -0.0017

20 -0.0045 -0.0054 -0.0015 -0.0015 -0.0027 -0.0025 -0.0052 -0.0034

AverageValue -0.0022 -0.0023 -0.0015 -0.0024 -0.0045 -0.0037 -0.0083 -0.0078

Highest Value -0.0001 -0.0001 -0.0001 -0.0004 -0.0002 -0.0003 -0.0019 -0.0004

Lowest Value -0.0064 -0.0065 -0.0071 -0.0067 -0.0215 -0.0357 -0.0248 -0.0232


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Price Elasticity of Demand Estimates for

Each of the 20 Industrials in HoustonFigure 3

Average Elasticities for the Six Most Responsive Energy Consumers

-0.0400

-0.0350

-0.0300

-0.0250

-0.0200

-0.0150

-0.0100

-0.0050

0.0000

id.-3a.m.

3-a.m.

-a.m.

-Noo

n

Noon-3p.m

.

3-p.m.

-p.m.

p.m.-

id.

Period Within a Day

OwnPriceElasticit

Cust 1

Cust 3

Cust

Cust 7

Cust 12

Cust 18


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Sanity Check on Results

Based on some simple comparisons of the aggregate loadlevels of transmission voltage (large industrial) energyconsumers between days of likely 4 CP charges andadjacent days, the ERCOT staff has identified about 600MW of aggregate demand response or about a 1%

reduction in demand. A back of the envelope calculation using the price

increase associated with a 4 CP hour, a normal aggregateload level for these twenty energy consumers, and theestimated own-price elasticity for the 3 p.m. to 6 p.m. period

would suggest a demand response of nearly 100 MW. It seems plausible that these 20 industrials might account

for about one-sixth of the total demand response in ERCOTto a 4 CP event.


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What ifwe take out the 4 CPs?

In the results presented above, the price signal to theenergy consumers contains two components:

the wholesale balancing energy price

and the transmission price (based on the 4 CP formula).

When the transmission price signals were removed from theprice series, the own-price elasticities increased for the timeperiods of midnight to 3 a.m., 3 a.m. to 6 a.m., 6 p.m. to 9p.m., and 9 p.m. to midnight, but were lower for the other(late morning and afternoon) hours.


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Results for Aggregate Market-WideR

esponse of Industrials Average own-price elasticity is -.00004.

Not surprisingly, the average market-wide estimates aremuch smaller than the elasticity estimates for the 20 largestindustrials in the Houston area.


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Results for Aggregate Market-WideR

esponse of IndustrialsComplete matrix of elasticities

1

1 1

1

1

11

1 1

1

1 1

1


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Impediments to Price Response

Many large industrials are self-scheduled LaaRs, and areconstrained in their ability to respond to prices.

Many energy consumers prefer a predictable flat price.

Advance notice of prices is limited.

4 CPs cannot be predicted with perfect accuracy.

The $1000/MWh wholesale price cap was in place duringthe periods studied.


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Implications

It might be difficult to rely upon price response to balancesupply and demand in an energy-only market, unless moreis done to facilitate demand response.

While it might be useful for ERCOTs short-term load

forecasts to take demand response into account when highprices are expected, the adjustments will likely to small.

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