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 Mime-Version: 1.0 Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit Bcc: dave.schulgen@enron.com, benjamin.bell@enron.com X-From: Hollis Kimbrough X-To: Jeff Maurer X-cc: Dave Schulgen, Benjamin Bell X-bcc: X-Folder: \mark fischer 7-12-02\Notes Folders\All documents X-Origin: FISCHER-M X-FileName: mark fischer 7-12-02 LNotes.nsf 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