Transcript of Natural Gas Demand for Power Generation in the US
PESA Foreign SvcNatural Gas Demand for Power Generation in the US
Cointegration
and Fuel Switching
Kenneth B. Medlock III
James A. Baker III Institute for Public Policy RICE
UNIVERSITY
Motivation In a previous study we did we examined the claim that
there has been a decoupling of natural gas and crude oil
price.
We found that there is still a long run relationship between
petroleum product prices and natural gas when we account for
increases in the energy efficiency of electricity generators –
introduction of natural gas combined cycle.
How do electricity markets respond to deviations in the long run
price relationship between natural gas and petroleum product
prices?
Macro-level response Micro-level response
Plant-level Fuel Switching
Data Price Data – EIA
City gate natural gas prices, PADD residual fuel oil and distillate
fuel oil prices
Electricity Generator Efficiency Measures – EIA and EPA Capacity
weighted national average heat rates
Degree Days Population weighted average heating and cooling degree
days - NOAA
Storage Inventories End of month working gas inventories relative
to their five-year average
The cost of electricity generation ($/kWh) is calculated:
=
2 2ln ln ln ln ln
1 1ln ln ln ln 2 2 1 1ln ln ln ln 2 2
i i i i i i i
ij i j ij i j j i j i j
i i i i i i i
C K HR Q Q
K HR
λ η
ξ
i i i i
∂ Ψ Ψ Ψ∂ ∂
7 , 8 9 10 ,
ln ln
ln ln
NG NG NG Oil Coal NG Oil i t i t i t i t i t i t i t
Coal i t j i t
j
α α α α α α α
α α α α β −= + + Ψ + Ψ + Ψ + +
+ + + + +∑ Dependent
ln Q i,t 0.0133***
Translog
with Cointegration But, our previous study showed that natural gas
and petroleum product prices are cointegrated.
Therefore, we replace the prices of natural gas, and petroleum
products with the error term from the cointegrating equation.
The cointegrating relationship varies by region and is
estimated:
We can plug in place of the oil and gas prices.
0 1ln lnNG Oil t t tβ β ωΨ = + Ψ +
0 1ln lnNG Oil t t tω β β= Ψ − − Ψ
Translog
6 , 7 8 9 ,
ln ln
ln ln
NG NG Coal NG Oil i t i t i t i t i t i t
Coal i t j i t
j
γ γ γ ω γ γ γ
γ γ γ γ β −= + + + Ψ + +
+ + + + +∑
ln Q i,t 0.0123***
[ ]
ω
Interpretation of Results Elasticities:
Then, α<0 indicates a positive response in NGConFrac that is
decreasing as x increases.
In the second case, α<0 indicates a positive effect when x is
positive.
1 1
y e x y xe x e x y x
y x
α
Double Log Results
Plant Level Fuel Substitution 136,000 MW of capacity - 18% of
electricity generation capacity in the United States is dual-fueled
and approximately 13% of that capacity is industrial cogen.
0
5,000
10,000
15,000
20,000
25,000
C O C T
D E FL G A IA IL IN KS KY LA M A
M D
VA VT W W I
W
NG Consumption NG Consumption NG + Oil Consumption NG + Oil
Consumption
NG Price NG Price DFO Price RFO Price
i t i t
Month
−
= +
+ + + +
∑
Where fuel consumption is measured in MMBtu and prices are measured
in $/MMBtu Monthly dummy variables to account for systematic
seasonal outages
Plant Level Model
Random effects model
∈
, , ,
, , , , , ,
, , ,
o i t i t i i t
o i t i t i i t i t i t i i t
o i t i t i i t
y x v
β ε
Panel Tobit
Specification Tobit model allows for estimation of a relationship
between a censored dependent variable and its explanatory
variables.
The model assumes that the random effects, , are normally
distributed and thus we have a joint distribution of the observed
data:
where:
,..., | ,..., , 2
i vv T o o o i i T i i T i t i t i i
t
ef y y x x F y x v dv σ
β πσ
i t
i t
e y
Fired Distillate Fuel
P NG i,t /P
DFO i,t -0.0395*** -- -0.0489***
P NG i,t /P
Feb 0.0208** 0.006 0.0344**
Mar 0.0849*** 0.0708*** 0.0972***
Apr 0.0965*** 0.0439*** 0.1172***
May 0.1054*** 0.0333** 0.1558***
June 0.0560*** -0.0404*** 0.1176***
July 0.0988*** 0.0294** 0.2368***
Aug 0.0568*** -0.0277* 0.0954***
Sept 0.0544*** 0.0192 0.0607***
Oct 0.0377*** 0.0027 0.0569***
Nov 0.0159*** -0.0496*** 0.0393***
Dec -0.1638*** -0.1209*** -0.1884***
Constant 0.2822*** 0.3266*** 0.2541***
Conclusions There is significant flexibility in the electricity
markets through macro and micro level switching. At the grid level,
we see a response to the long run deviations in price, adjusted for
technological changes. Decision makers at the plant-level are
responsive to the price ratio more than the deviations from the
long run price relationship. Overall, plant level switching occurs
more often as a result of changes in the relationship between
natural gas and distillate than changes in the relationship between
natural gas and residual fuel oil.
Next Steps
Grid Level Examine time series aspects of the translog formulation
in more depth
Plant level Plant outage data Contracting behavior data
Industrial fuel switching
Natural Gas Demand for Power Generation in the US Cointegration and
Fuel Switching
Motivation
Outline
Data