Shirley: 
As requested, herein is information regarding the meeting with Vince Kaminski.  
The presentation on the EGE tool's applications and the Allegheny Energy case study is timed to take an hour.  If the meeting is most conveniently scheduled for Tuesday, May 29, might I request it be set for late afternoon (as my other appointments are the next day).  
And, as Vince will recall, I was Co-Leader of the energy consulting business of PHB Hagler Bailly, and developer of the Ramp Up, Real Time, 75check and Electric Strategy tools.  Presently, I am CEO of Energy Leader Consulting (ELC).
    Background
The U.S. power generation industry has become increasingly efficient in recent years.  Rapidly growing new entrants seek profit maximization aggressively.  Utilities, who still control most power plants, endeavor to adopt the entrants' methods.  Yet, inefficiency among many utilities remains widespread.
Utility inefficiency arises from adherence to decades-old habits and in unit commitment and dispatch and planned maintenance scheduling.  Many utilities, notwithstanding the industry-wide trend towards profit maximization, cling to ingrained routines.
Inefficiency can also arise from the diseconomies of small scale.  A utility may operate a relatively small system (fewer than a dozen plants).  A small system lacks portfolio diversification and perspective in its focus on its regulated customers, playing the wholesale market at the margin.
For a variety of reasons, utilities are reluctant to cut back the starts of their generating units, let alone shut down any (even temporarily or seasonally).  Economically inefficient units continue to be committed, week after week, and run in the half-load range.
    EGE Objectives
EGE identifies and assesses generating units of a utility with questionable commitment routines.  Taking into account transmission and reliability factors, the procedure points towards profit opportunities that may be exploited by another industry participant.
    I. An industry participant can use EGE as a basis for a medium or long-term wholesale power transaction with a utility; or to price wholesale power more aggressively, to take market share from the utility (i.e., compel changes in unit commitment habits).  
    II. An industry participant can use EGE to spot and quantify efficiencies that would come from a merger or acquisition.  
    III. A power plant developer can use EGE to estimate the incremental value a new plant will enjoy when the target utility's unit commitment routines inevitably become rationalized.
    Specific EGE Concepts
EGE reduces and analyses the extraordinary but unwieldy continuous emission monitoring data base intelligently focusing on profit opportunities.  
It produces indicative statistics such as:
    a. the frequency distribution of starts per week;
    b. the frequency distribution of starts by day/15-minute segment during the week;
    c. the frequency distribution of load level;
    d. the frequency distribution of hours of operation per start;
    e. average heat rate and approximate fully-allocated cost in the half-load range;
    f. average ramp rate from the half-load range;
    g. the frequency distribution of unused connected capacity during the highest demand hours; and
    h. forced-off maintenance outage rate (where indicated).
Indicative statistics are generally aggregated by month/year; in some cases, by temperature range.  (They can be by regional wholesale prices as well.)  EGE establishes if the target utility has changed unit commitment routines significantly in recent years.
EGE is based upon uniquely timely actual hourly operating data.  EGE is now updated for the 4th quarter 2000 (through December 31, 2000).  EGE 1st quarter 2000 (through March 31, 2001) will be available approximately June 15, 2001.
EGE also compares and ranks generating units' commitment and dispatch with that of similar units operated by the target utility (as well as other regional generators).  Some utilities operate a group of economically marginal units at the half-load level for lengthy time periods (without an apparent reliability basis), splitting the limited economic demand for power among the units.
Other EGE supporting data:
    i. planned maintenance schedule (where indicated);
    j. actual maximum generating capacity;
    k. actual minimum generating capacity (actual maximums and minimums can differ significantly from government-reported values);
    l. average heat rate in the full-load range; and
    m. average heat rate in the three-quarter-load range.
With respect to a generating units' average heat rate in the half-load, three-quarter-load and full-load ranges, it can be instructive to rank these relative to similar generating units within a region.  It can also be of interest to identify significant seasonal variations in average heat rates and maximum capacities, and changes in recent years in these parameters.
    The Real-World Example of Allegheny Energy
Allegheny Energy can serve as a case study to illustrate the application of EGE.  In the 4th quarter 2000, for instance, one high-cost generating unit was started virtually every weekday morning (52 times) and committed for the whole day (in all but two cases).  Arguably, there are power products that could substitute for this routine (in part at least) at a profit to the seller of the product and Allegheny Energy.
Another high-cost Allegheny Energy generating unit was started virtually every weekend during the autumn (nine times) and committed for most of the coming week.  At another plant, two high-cost units were operated too often in the expensive half-load range (some 550 hours) and three-quarter-load range (another 400 to 600 hours); they were seldom called upon to run at higher levels.  Again, there are power products that that address these practices and might appeal to Allegheny Energy.
    Offering of Energy Leader Consulting (ELC)
EGE is a procedure, not a software package or data base.  ELC believes this format is more effective in arming clients with the information they need to act upon profit opportunities.
ELC transfers its "knowledge" about the EGE procedure and the supporting data methods in a straight-forward four-step process:
    1. Enron would select one to three target utilities.
    2. ELC would perform the EGE procedure on the target utilities.
    3. Employing this real-world analysis as a pedagogic tool, ELC, in a one-day seminar with Enron personnel, would instruct how to perform the procedure in the future (without the assistance of ELC).
    4.  Optionally, ELC would provide EGE supporting data, quarterly, to Enron.
The basic EGE supporting data set is national including all generating units under the continuous emission monitoring program (virtually all fossil fuel units).  Parameters that are incorporated, and the data set format, will be specified upon request.  Custom modifications will be considered.
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Steven A. Mitnick
Chief Executive Officer
Energy Leader Consulting
4807 41st Street, NW
Washington, DC 20016
(202) 997-0924 voice
(202) 537-0906 fax
SMitnick@EnergyLeader.com