Message-ID: <11512453.1075840444950.JavaMail.evans@thyme>
Date: Thu, 25 Apr 2002 06:46:00 -0700 (PDT)
From: hollis.kimbrough@enron.com
To: jeff.maurer@enron.com
Subject: Capabilities Memo
Cc: dave.schulgen@enron.com, benjamin.bell@enron.com
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Jeff,

This e-mail is intended to describe our existing and potential capabilities 
with respect to turbine performance analysis.  Using existing SCADA data we 
presently have the ability to perform both optimization and diagnostics for 
turbine performance.  In the future, we can develop our capability to move 
into preventative repairs and maintenance.  If we make changes to the type of 
SCADA data we collect we can become more aggressive in our turbine 
performance preventative modeling and characterization.

Some examples of our current capabilities include:

1.  Yaw Activity Report:  This report is prepared and sent to each of the 750 
kW sites on a monthly basis.  Although yaw activity does not affect either 
availability or power curve (contractual items), it is critical to production 
as slight variations in yaw activity can result in big production variances.  

The purpose of this report is to identify, at a glance, the turbines which 
are experiencing excessive yaw activity relative to their neighbors.  We 
present this information graphically with an average (solid green line) and 2 
standard deviations (dashed green line) to quickly identify turbines which 
are yawing more than 2 standard deviations from the average.  Any turbine 
which is either yawing zero hours, or in excess of two standard deviations, 
should be inspected by the field personnel for turbine defects or SCADA 
system defects.

This example is for LB2, March 2002 node 1. 



2.  SCADA Power Transducer Report:  This report is prepared and sent to each 
of the 750 kW sites on a quarterly basis.  This report compares the SCADA kWh 
reading to the glass meter energy reading and looks for differences of 2.5%.  
When a difference of 2.5% is detected the particular turbine is clearly 
identified in a table for additional field troubleshooting.  

Although the site gets paid based on the substation glass meter readings, the 
SCADA kWh meter readings are very important since these are what the customer 
and operators see when they pull production information into SCADA.  To 
facilitate a good basis for decision making, and to support the integrity of 
the SCADA system, it is important to ensure the meter readings are as 
accurate as possible.

This example is for SL2, Q4 2001




Please note that the decision not to put pad mounted glass meters on the 1.5 
MW WTGs makes this analysis impossible for the 1.5 MW WTG.  However, we (the 
Engineering Power Performance Group) can (and has) put a high precision 
transducer in parallel with the SCADA kWh transducer on the 1.5 MW WTG and 
discovered the SCADA transducer to be within 1%.

3.  SPC Analytic:  This report is under development but will be completed 
either this week or next week.  We are capable of generating, and 
distributing, this report as frequently as is needed.  Our intention is to 
produce this report either weekly (when the new data arrives and is uploaded) 
or monthly, whichever, is preferred.  

This analytic is written for the 750 kW WTG but we are also preparing a 1.5 
MW WTG version.  This particular report calculates an average (green solid 
line) and a 2 standard deviation line (dashed green line) for the following 
parameters: kW, nacelle mounted wind speed, generator rpm, hub rpm, blade 
pitch, ambient temperature, gearbox temperature, generator temperature, 
hydraulic oil temperature, hydraulic oil pressure #1, hydraulic pressure #2, 
AC Mains voltage, AC Mains current phase A, AC Mains current phase B, AC 
Mains phase C, AC Mains frequency, Op hours, Available hours, Line hours, EPC 
hours, Generator hours, Hydraulic hours, Yaw hours, and kW hours.  As can be 
seen here, we have the analytic working but we are completing the process so 
our clerical staff can both generate and distribute the report.

This particular example is for Cabazon for the month of February 2002.  



4.  Non-Routine report:  We provide a number of non-routine reports for both 
diagnostic and proof of concept purposes.  I have attached two examples here 
to illustrate these types of reports but basically we are capable of applying 
complex statistical and mathematical formulas to turbine performance, and 
other, data to answer very practical questions.

This example is a request that came from Engineering and Asset Management to 
determine the suitability for installation of Ride Through kits.  This 
example demonstrates some of the advanced statistical methodologies we have 
available for application to employ on behalf of other EWC, or customer, 
organizations. 

 

This next example was prepared for the Engineering Department in their 
efforts to understand the blade pitch problem.  Engineering suspected a 
correlation between vibration faults and improper blade pitch so we prepared 
a graph which displayed the total number of vibration and blade asymmetry 
faults.  The results were provided to Engineering within 24 hours of the 
request.



5.  Owner Reports:  We prepare performance reports for each of our sites on a 
monthly basis.  These reports supply the turbine performance information 
needed to fulfill contractual obligations for performance reporting.  
Included here are examples for both a 1.5 MW WTG site (Trent) and a 750 kW 
site (SL2).



6.  Future Report:  As we complete the SPC analytic we will turn our 
attention to development of a power curve report.  This report will be 
produced on a quarterly basis and will detect degradation in the power curve 
over time.  The specification for this report has been developed and will 
compare relative power curves for both the 750 and 1.5 turbines.  The basis 
for the report will be a power curve which is displayed graphically, on a 
turbine by turbine basis, for the same quarter from previous years.  In other 
words, for the first quarter in 2002 the graph will include Q1 from 1999, 
2000, 2001 and 2002.  The second quarter graph will include Q2 from 1999, 
2000, 2001 and 2002.  

The reason for assigning the Quarters this way is to control for changes in 
atmospheric conditions (i.e. density, relative humidity, wind, etc) and 
isolate long term turbine performance.   With this report we should be able 
to identify problem turbines and take remedial action resulting in increased 
production. 




The report examples so far have all been illustrative of our ability to 
provide diagnostic and optimization information to the field, customers and 
other internal organizations.  We have a great potential to move beyond these 
levels of reporting into predictive and preventative maintenance situations.  
Here are several examples of what might be possible if we changed some of our 
processes or strategies:

1.  Without modifying the existing SCADA system we currently have the ability 
to evaluate numbers of cycles of various pieces of equipment and compare that 
to failure data to predict component failure.  However, our current 
development/construction/operations process resulted in incomplete data sets 
for the 1.5 MW WTG so we cannot fully bring this ability to bear.  A great 
example of this is the blade failures at Trent Mesa where some of the blades 
seem to be cracking and failing prematurely.  If the presumption is made that 
the failure is related to load cycles (reasonable), and those load cycles are 
not thermally based (also reasonable), then we could have compared the cycles 
and predicted which blade set was at the highest risk of failing next.  Armed 
with this information, we could direct our field crews straight to the 
pertinent turbines to conduct inspections and possibly do repairs before a 
failure occurred.

If we want to have this capability in the future, we must ensure that SCADA 
is operational when the WTG is operational and that we collect, and store, 
the data from the time the turbine commences operation.

2.  If we are willing to add vibration monitoring equipment, such as 
accelerometers, to critical bearings and rotating equipment we should be able 
to predict the time to failure for these components.  Having this ability 
would enable us to avoid consequential damage to other components and also 
allow us to pick a convenient time for a scheduled outage to conduct 
repairs.  Having a methodology such as this would also enable us to service, 
or replace, components as the component came to the end of life versus 
maintaining a maintenance schedule which replaces components on a calendar 
schedule (i.e not the actual end of component life). 

This would require both a modification to the turbine (additional 
transducers) and to the SCADA system.

3.  If we were to engage a Reliability Engineering function in our company we 
would be able to develop a much more advanced ability to engage in predictive 
and preventative maintenance.  To the best of my knowledge we do not have 
anyone within EWC performing this role.

I have not provided an exhaustive list of our capabilities.  Rather my 
intention has been to equip you with knowledge and understanding of what we 
are capable of today, and some of the possibilities for tomorrow.  Please let 
me know if you would like additional information or examples or whether you 
have any questions.

Best Regards,
Hollis