Working with Power Model Forecasts

 

Recently we have been spending quite a bit of time working with
companies who are using both a power model such as Prosym, GE Maps, or
IREMM, and GPCM.  These power models compute, among other things, the
amount of gas burned at gas-fired or dual-fired generation plants.
These values are frequently then fed back to GPCM as electric generation
gas demands.  The idea was that GPCM would produce the prices for the
various power demand locations which could then be fed back to the power
model for re-calculation of demands.  This iterative process would
produce eventually a solution which was consistent between the power
model and GPCM.  The difficulty with this idea is that the power model
takes too much time to solve to make it practical.  

 

After a lot of thought, I have come up with a different idea which has
greater workability.  I would recommend the following:  instead of
running a single power model case with an expected set of gas prices for
each area, run 3 cases:  essentially a high, medium and low Henry Hub
Price forward price trajectory plus best estimates of future basis to
each power generation gas demand area.  The results will then be three
gas burns at three prices at each location.  We can then construct a
demand curve for each demand location based on those three points.  With
those demand curves, GPCM can solve for an expected price - gas burn
combination which will be an appropriately interpolated value between
the 3 points computed by the power model.  

 

When this is done, one final run could be made using the power model and
the resulting GPCM prices.  It should produce gas burns very close to
the value computed by GPCM and will contain all the information needed
by the power modeling team.

 

From Enerfax on Thursday (http://www.enerfax.com
<http://www.enerfax.com/> )

 

AGA Natural Gas Storage Report

 

            Week                                    Prev      

           Ending    Prev                   Prev    Year    

| Region | 1/18/02 | Week | Diff | % Full | Year | % Full| 

| Prod   |  707    |  733 | -26  |  74%   |  312 |  33%  |      

| East   | 1319    | 1396 | -77  |  72%   |  816 |  44%  |  

| West   |  379    |  400 | -21  |  75%   |  241 |  47%  |   

       

| Total  | 2405    | 2529 |-124  |  73%   | 1369 |  42%  

 

Bob Brooks

GPCM Natural Gas Market Forecasting System

http://gpcm.rbac.com <http://gpcm.rbac.com/>