---------------------- Forwarded by Vince J Kaminski/HOU/ECT on 04/19/2001 
04:28 PM ---------------------------


Jeff Gray@EES
04/17/2001 12:30 PM
To: Vince J Kaminski/HOU/ECT@ECT
cc: Michael Moore/HOU/EES@EES 
Subject: EES revenue through customer DSM projects

Vince:

Have you or a member of your group had a chance to look over the forwarded 
e-mail yet?  We have a meeting on Thursday with another potential client who 
plans to use his own capital.  His capital budgeting issues are similar to 
those of the client who prompted my original e-mail.

The more DSM projects that we can help the client get approved, the more DSM 
savings we can share with the client.  These DSM projects can turn a retail 
commodity contract with low profitability into a substantially more 
profitable contract for us.

Would one of your GARCH analyses provide us with a quantitative solution?  
One of your experts in differential equations might have devised something.  
We'd really like to have something quantitative if you think it's at all 
possible.

Thanks,

Jeff

---------------------- Forwarded by Jeff Gray/HOU/EES on 04/17/2001 12:16 PM 
---------------------------


Jeff Gray
04/09/2001 04:41 PM
To: Vince J Kaminski/HOU/ECT@ECT
cc: Michael Moore/HOU/EES@EES, Jay Sparling/HOU/EES@EES 
Subject: DSM projects as real options  

Vince:

Could you spare a few moments to look over the attached three-page Power 
Point presentation?  At a minimum, we're trying to demonstrate the 
following:  In high-volatility electricity environments, for those EES 
customers who employ their own capital, their usual capital-project IRR 
hurdles may be lowered slightly in the special case of DSM projects, to allow 
for the extra value derived from reduced risk exposure stemming from reduced 
power consumption/dependence.

I'm pushing the boundaries of real-option theory (and good sense) and viewing 
a DSM project as a series of options, the values of which are additive.  
First is the option to engage in the DSM project itself; which, if we 
exercise the option immediately, can be valued intrinsically through a simple 
NPV analysis.  Second is a strip of put options to generate "negawatts," 
extending over the useful life of a DSM installation, the cumulative value of 
which is an extrinsic value associated with the DSM project.  These options 
are exercised sequentially--over the life of the DSM installation--whenever 
the customer experiences a dramatic, stochastic spike in electricity price, 
associated with a lognormal price distribution.  I'm calling the value of 
this strip a "residual time value" associated with the original DSM option.  
If we can add this residual time value to the NPV and derive a total value 
that is quantitatively higher than a simple NPV alone,  we may be able to 
help the customer get more projects approved, even at the original high IRR 
hurdle.

Alternatively, and more feasibly, we'd like to give these same customers a 
"qualitative" tool with which they can convince their finance gatekeepers to 
lower--for DSM projects--their standard capital-project IRR hurdle .  The 
attached presentation is a first attempt at this qualitative argument.

We intend to use this only as a sales and marketing tool, to allow at least 
one of our customers who has an onerously high hurdle rate to manage around 
his company's internal capital-budgeting requirements.  He has set aside a 
large sum of money for DSM projects, but will only be able to spend a small 
portion of it under his company's current capital budgeting methodology, 
which does not take into account forward commodity price volatility.

In your opinion, is there any hope in devising a quantitative justification, 
or will we have to stick with the qualitative argument as described in the 
attached presentation?  In other words, is it possible to quantify "residual 
time value" as I've defined it above? Or, even better, are you aware of a 
more practical way of conceptualizing this problem?

Thanks,

Jeff Gray



 



Vince J Kaminski@ECT
01/05/2001 03:26 PM
To: Jeff M Gray/NA/Enron@ENRON
cc: Vince J Kaminski/HOU/ECT@ECT, Stinson Gibner/HOU/ECT@ECT, Alex 
Huang/Corp/Enron@ENRON, Gary Hickerson/HOU/ECT@ECT, Michelle D 
Cisneros/HOU/ECT@ECT 
Subject: Power Plant Model

Jeff,

A few comments on the model:

1. We have a few reservations about some features of the model but would like 
to
discuss it internally and make the improvements without giving the benefit of 
our insights to the consultant.
In general, the model is not unreasonable but the devil is always in the 
details and in the inputs and
calibration. The same model may produce drastically different results 
depending
on the quality of inputs. 

2. We don't have a separate pool of programmers in the Research  Group. We 
were told that you
would provide an IT resource. Alex would supervise this person.


Vince