Using Reliability Data to Improve Power Plant Performance

Using Reliability Data to Improve Power Plant Performance NERC-GADS Workshop presented by Robert R. (Bob) Richwine Reliability Management Consultant Richwine Consulting Group, LLC Oct 28, 2010

Workshop Agenda I. II. Background and Case Study Common Elements in Successful Programs A. B. C. D. Awareness Phase Identification Phase Evaluation Phase Implementation Phase III. Transforming to a Market-Driven Business Environment Richwine Consulting Group, LLC 2

Background • From a 2006 Wall Street Journal article – Business today is awash in data and data crunchers – Only a few companies use data as a strategic weapon – The ability to collect, analyze and act on data is the essence of a company’s competitive advantage Richwine Consulting Group, LLC 3

Survey Results in WSJ • 450 executives; 370 companies; 35 countries; 19 industries • Identified a strong link between extensive and sophisticated use of analytics and sustained high performance • Top performing companies were 5 times more likely to single out analytics as critical to their competitive edge Richwine Consulting Group, LLC 4

A substantial gap exists between actual and potential performance Potential Performance Actual Performance Richwine Consulting Group, LLC 5

The Worldwide Value of Closing the Gap (WEC estimate) • Economic – US$80 Billion per Year • Environmental – 1 Billion Tonnes of CO 2 Reduction per Year and Proportional Reductions of Other Emissions Richwine Consulting Group, LLC 6

Source of Performance Improvement • Variation of performance due to – Technology/mode of operation = 20 -25 % – Human factors/management = 75 -80 % • Confirmed by – Analytical studies – Practical experiences Richwine Consulting Group, LLC 7

Closing the Gap Better Use of Reliability Data is a Key Factor in Achieving and Sustaining Top Performance Richwine Consulting Group, LLC 8

30+ WEC Published Case Studies • www. worldenergy. org Click on “Work Programme” Click on “Performance of Generating Plant” Click on “Case Studies” • Each Case Study demonstrates actual value received by use of performance data Richwine Consulting Group, LLC 9

Case Studies Published by the WEC Objective Demonstrate that the value of performance data is far greater than the combined cost of collecting the data plus the risk of sharing the data Richwine Consulting Group, LLC 10

WEC Case Study Topics include the Use of Data in: • Benchmarking • Configuration Optimization • Generation Planning • Operations • Goal Optimization • Maintenance Planning • Risk Management • Catastrophic Event Reduction • Life Management • Equipment Design Richwine Consulting Group, LLC 11

NERC-GADS • In North America NERC has been collecting power plant reliability data in the GADS format for 28 + years • An increasing number of international companies have begun using the NERC-GADS system to collect and analyze their plant’s performance • The World Energy Council has adapted NERC-GADS for international use • Some companies have used the GADS database in innovative ways to help them achieve top performance of their generating plants Richwine Consulting Group, LLC 12

CASE STUDY Performance Improvement in Power Stations Southern Company’s Experience May 2004 WEC Case Study Richwine Consulting Group, LLC 13

Southern Company Alabama Power Georgia Power Savannah Electric Mississippi Power Gulf Power Southern Company Headquarters Atlanta, GA, USA Currently ~ 35, 000 MW 14 Richwine Consulting Group, LLC Capacity

Fossil Steam Power Stations Availability Trend 1970 -1976 Equivalent Availability Factor (EAF) Trend Richwine Consulting Group, LLC 15

Decline In Power Station Availability 1970 -1976 • Inability to provide adequate resources to power stations – High load growth – Extensive new environmental requirements (particulates) – Beginning of nuclear plant construction program • Lack of advanced decision support methods/tools to determine best use of resources that were available • Design philosophy of “lowest initial cost” • Advanced technology plants specified without adequate understanding of “learning curve” effects • Reactive maintenance philosophy instead of proactive • Lower quality fuel purchased based on “low delivered cost” instead of “lowest total cost” • Little use of performance data except for “reports” Richwine Consulting Group, LLC 16

Fossil Steam Power Stations Availability Trends 1970 -1991 Equivalent Availability Factor (EAF) Trend Richwine Consulting Group, LLC 17

Increased Power Station Availability Due To. . . • Heightened awareness of executive management of the need for availability improvement • Commitment of additional resources for availability improvement • Improved decision making addressing the “what and how” of power plant management • Many advanced programs and processes including improved reporting and analysis of plant performance data Richwine Consulting Group, LLC 18

Availability Improvement Benefit Areas • • Replacement energy Deferred construction Reduced reserve margin requirements Increased customer service reliability Richwine Consulting Group, LLC 19

Availability Improvement Benefits to Southern Company US$1, 235, 000 per year Richwine Consulting Group, LLC 20

Heat Rate Trend (Inverse of Efficiency) Richwine Consulting Group, LLC 21

Heat Rate Benefits to Southern Company US$108, 000 per year Richwine Consulting Group, LLC 22

Additional Cost US$325, 000 per year Richwine Consulting Group, LLC 23

Benefits versus Cost Benefits = $1, 235, 000 + 108, 000 $1, 343, 000 per year Cost = $ 325, 000 per year Net Savings= $1, 343, 000 - 325, 000 $1, 018, 000 per year Benefit/Cost= $1, 343, 000 = 4. 3 $325, 000 Richwine Consulting Group, LLC 24

Southern Company Perspective • In 1991, net savings in excess of US$1 billion per year equaled: – ~12 percent of Annual Revenue – ~100 percent of Net Income (Profit) Richwine Consulting Group, LLC 25

Environmental Benefits of Performance Improvement Annual avoided emissions included: Seven million tons of CO 2 e per year at essentially $0 cost! Richwine Consulting Group, LLC 26

Availability Improvement at Other Utilities PREPA – Puerto Rico +25% NEES – USA +13% ESB – Ireland +10% ESKOM – South Africa +20% Richwine Consulting Group, LLC 27

Observations • Each company/country faces its own set of challenges, constraints, and opportunities • No single program is optimal for every company/country • There are common elements within each successful program Richwine Consulting Group, LLC 28

Common Elements In Successful Improvement Programs January – April 2003 WEC Case Studies A n io w at ar e ic ne ss tif en Id al Ev n tio ta en em pl ua tio n Im Performance Improvement Richwine Consulting Group, LLC 29

Performance Improvement Process Phase 1 - Awareness • Benchmarking • Forecasting • Communications Richwine Consulting Group, LLC 30

Awareness January 2003 WEC Case Study • Benchmarking – April 2002 WEC Case Study – August 2002 WEC Case Study – September 2003 WEC Case Study Richwine Consulting Group, LLC 31

Reliability Benchmarking - Why? • • • Set realistic, achievable goals Identify areas for improvement Give advance warning of threats Determine appropriate incentives Trade knowledge/experience with peers Quantify and manage performance risks Richwine Consulting Group, LLC 32

Reliability Benchmarking Process • Identify reliability variables to measure and the databases required • Select peer power plants having similar design or mode of operations characteristics • Compare the candidate power plant’s reliability against these peer plants Richwine Consulting Group, LLC 33

Reliability Benchmarking Process • Identify reliability variables to measure and the databases required: Typical Reliability Variables – Equivalent Availability Factor (EAF) – Equivalent Forced Outage Rate (EFOR) – Scheduled Outage Factor (SOF) AND INCREASINGLY, EFOR(demand) Richwine Consulting Group, LLC 34

Benchmarking Process • Select peer power plants having similar design or mode of operations characteristics: – Selection Procedure (NERC/Richwine developed) • Advanced statistical methodology • Has been applied numerous times over the past 20 + years at companies and countries around the world Richwine Consulting Group, LLC 35

Peer Selection Criteria Large Population NERC-GADS Data Base 5000 + units Richwine Consulting Group, LLC 36

Peer Selection Criteria Exact Match x x x x x Number of Exact Matches Richwine Consulting Group, LLC x x x 0 37

Peer Selection Criteria Large Population Exact Matches Must Balance Criteria Richwine Consulting Group, LLC 38

Peer Selection Criteria Etc. Firing Fuel Vintage Boiler Manufacturer Criticality Etc. ASSU ME Size Etc. Draft Richwine Consulting Group, LLC Etc. Duty Age Turbine Manufacturer 39

Peer Selection Criteria Etc. Vintage Firin g Boiler ANALYSIS Manufacturer Fuel Size Etc. Duty Age Criticality Etc. Draft Richwine Consulting Group, LLC Turbine Manufacturer 40

Peer Selection Criteria Significance Testing Subcritical Supercritical Baseload Duty Cyclic Duty EFOR Richwine Consulting Group, LLC EFO R 41

Peer Groups Select Criteria Fossil Units Super All Fossil Units CRITICALI TY VINTA GE <1972 ≥ 1972 Sub MODE OF OPERATION Cycli Baseload ng Size Boiler Mfr. Draft Type Fuel Richwine Consulting Group, LLC Draft Type Size 42

Does Peer Selection Make a Difference? SUPERCRITICAL TECHNOLOGY EARLY VINTAGE RECENT VINTAGE EFOR(mean) EFOR(median) EFOR(best quartile) 15. 60% 12. 17% 8. 14% Richwine Consulting Group, LLC 9. 68% 8. 08% 5. 47% 43

Does Peer Selection Make a Difference? EFOR - PLANT A OLD CRITERIA (Coal; 100 -199 MW) mean median best quartile NEW CRITERIA % difference 6. 47% 5. 53% -14% 4. 78% 5. 07% +6% 2. 65% 3. 26% +23% Richwine Consulting Group, LLC 44

Does Peer Selection Make a Difference? EFOR - PLANT B OLD CRITERIA (Coal; 800 -1300 MW) mean Median best quartile NEW CRITERIA % difference 5. 83% 7. 63% -31% 4. 55% 5. 87% +29% 2. 70% 3. 97% +47% Richwine Consulting Group, LLC 45

Performance Benchmarking Results -30 Peer Units • Peer unit selection criteria – Subcritical – Reserve shutdown hours less than 963 hours per year – Natural boiler circulation – Primary fuel = coal – Single reheat – Net output factor greater than 85. 6% Richwine Consulting Group, LLC 46

Peer Unit EFOR Distribution Richwine Consulting Group, LLC 47

Peer Unit SOF Distribution Richwine Consulting Group, LLC 48

Peer Unit EAF Distribution Richwine Consulting Group, LLC 49

Conclusions • Benchmarking is helping utilities – – Set goals Develop incentives Identify improvement opportunities Quantify and manage risks • Proper peer group selection is essential Richwine Consulting Group, LLC 50

Forecasting Statistics Versus Probability • Statistics – Yesterday’s actual results • Probability – Tomorrow’s predicted results Richwine Consulting Group, LLC 51

Forecasting Performance • An embarrassing personal example – September 2002 WEC Case Study Richwine Consulting Group, LLC 52

EFORACTUAL - EFORPREDICTED Richwine Consulting Group, LLC 53

Basic Principle ~ Past Conditions Future Conditions Past Results Future Results Richwine Consulting Group, LLC 54

Predicting EFOR Most Important Parameters • Lagging Equivalent Forced Outage Hours • Lagging Service Factor • Current Year Planned Outage Hours • Lagging O&M Spending • Current Year O&M Spending • Fuel Type Richwine Consulting Group, LLC 55

EFORACTUAL - EFORPREDICTED Richwine Consulting Group, LLC 56

Forecasting Examples • New Technology “learning curve” – Supercritical • November 2002 WEC Case Study Richwine Consulting Group, LLC 57

Outage Rates versus Year of Initial Operation Richwine Consulting Group, LLC 58

Communications to all stakeholders, especially employees, is vital to clearly show the “GAP” between your plant’s reliability compared to the best performers in their peer group Richwine Consulting Group, LLC 59

Phase 2 - Identification February 2003 Case Study en es s ar w A n io at ic tif en Id Richwine Consulting Group, LLC 60

Identification February 2003 Case Study Identifying problem areas with best payback potential – Component Benchmarking – High Impact – Low Probability Event Reduction – February 2002 Case Study – Trend Analysis Case Studies: • March 2002 – Peak Season Reliability • June 2002 – Availability Following Planned Outages • December 2002 – Reliability Versus Demand Richwine Consulting Group, LLC 61

Component Benchmarking • Two options – #1 - Components from all groups but using component design and operational data for selecting peer groups – # 2 - Components in peer group of unit-level benchmarking Richwine Consulting Group, LLC 62

Component Benchmarking • Compare the performance of each system/equipment to its peer distribution • The system/equipment with the largest “percentile gap” between its performance and the “best in class” in its peer group should be a high priority system to study Richwine Consulting Group, LLC 63

Is Your Power Plant Headed for a HILP? ? How to Avoid, Detect or Mitigate High Impact – Low Probability (HILP) Events Robert Richwine – Richwine Consulting Michael Curley – NERC G. Scott Stallard – Black & Veatch Richwine Consulting Group, LLC 64

What is a HILP? • High Impact – Low Probability Event • Happens infrequently but results in extended unplanned outages • Sometimes called “First Time Event” (at least the first time it has happened at your plant) Richwine Consulting Group, LLC 65

Typical HILPs • • Turbine Water Induction Boiler Explosions Generator Winding Failures Many, many others Richwine Consulting Group, LLC 66

HILP Reduction Programs • Some companies have successfully reduced their HILP frequencies or magnitudes with a formal HILP Reduction Program using the North American Electric Reliability Corporation’s (NERC) GADS data. • NERC-GADS database contains 25+ years of detailed design and reliability data from over 5, 100 generating units with a wide variety of technologies. Richwine Consulting Group, LLC 67

HILP Effect on Forced Outage Rate (FOR) • FOR made up of two major elements – Routine expected events with small/medium outage consequences – Unexpected major events with large outage consequences • Should separate these two elements of FOR when benchmarking reliability and establishing reliability improvement programs Richwine Consulting Group, LLC 68

Benchmarking two units’ Forced Outage Rate (FOR) - Example FOR Unit A 10% Many small Type of Outages events "Normal" FOR 10% Richwine Consulting Group, LLC Unit B 10% Fewer, smaller events but 1 major event of 3 weeks length ~4% 69

Benchmarking two units’ Forced Outage Rate (FOR) Implications 1) The two units have had very different failure modes 2) We should adapt our benchmarking analysis and improvements efforts to account for these differences. Richwine Consulting Group, LLC 70

HILP Reduction Program • Step 1 – Select the best peer group for benchmarking against your unit • Step 2 – Find the peer group’s HILP contribution to EFOR and compare to your unit’s HILP contribution • Step 3 – Prioritize the peer group’s HILP problem areas • Step 4 – Review GADS root cause information • Step 5 – Assess your plant’s susceptibility to HILPs • Step 6 – Identify options to address HILPS • Step 7 – Evaluate and select HILP reduction options • Step 8 – Track results of implemented options, compare to expectations and feedback into program to improve the process Richwine Consulting Group, LLC 71

Step 1 – Select Peer Group • It is vital to select the best peer group • You don’t want to be comparing apples to oranges • Actually, the best we can usually do is compare apples to oranges – at least they are both fruit • If you don’t go through an analytical selection process you might be comparing apples to zebras Richwine Consulting Group, LLC 72

Step 2 – Compare Unit to Peer Group’s HILP Contribution to FOR • Using NERC’s pc-GAR software calculate FOR • Using NERC’s pc-GAR-MT software determine the number of full forced outage hours with outage durations greater that the value “you” define as a HILP (typically greater than 1 week or longer) • Using the HILP full forced outage hours calculate the FOR due to HILPs • Compare the unit’s HILP contribution to FOR to its peer groups 73 • Repeat for your. Richwine Consulting Group, LLC company’s fleet

Step 3 – Prioritize the Peer Group’s HILP Problem Areas • Using pc-GAR-MT and excluding non-HILP events (an option of the software) compile a frequency chart of HILP cause codes that the peer group has experienced • Use the frequency chart to focus on the most likely HILP areas for your unit • Consider exporting the files from pc-GARMT to a spreadsheet for easier manipulation and more detailed analysis as well as graphical reports Richwine Consulting Group, LLC 74

Step 4 – Review GADS Root Cause Data • GADS input contains an optional 80 character freeformat data field, often containing valuable data regarding the outages. • Although not currently available in pc-GAR or pc. GAR-MT, Mike Curley, Manger of NERC-GADS Services, can advise you on how to retrieve this information. • Reviewing this data for HILP events can indicate the root causes of events that your unit’s peer group has experienced and can point you in directions for assessing your unit’s susceptibility 75 to those HILPs. Richwine Consulting Group, LLC

Step 5 – Assess Your Unit’s Susceptibility to HILPs • HILP susceptibility is usually the result of several factors occurring together • Assessing HILP risk must rely on a structured process focusing on if these factors could exist • Catalogue key HILP events and the circumstances that could induce the HILP • Evaluate your unit to determine if these circumstances are present such as equipment condition, O&M experiences & practices, QA, etc. • Create a scorecard to quantify the level of HILP risk Richwine Consulting Group, LLC 76

Step 6 – Identify Options to Address HILPs • HILP reduction options are usually very specific to the issue • HILP reduction options should consider ways to: – Prevent the HILP – Detect the HILP event early so as to minimize downstream damage – Mitigate the impact of an undetected HILP Richwine Consulting Group, LLC 77

Step 7 – Evaluate and Select HILP Reduction Options • Sufficient information should be gathered to be able to forecast the effect of each option • An economic analysis for each option should be done to: – Justify – Time – Prioritize • Using the option evaluations and considering the fact of limited company resources (time, money, manpower) the best set of options should be chosen for implementation Richwine Consulting Group, LLC 78

Step 8 – Track Results, Compare to Expectations & Feedback • Monitor the actual results of each implemented HILP improvement option and compare to expected results • Compare the fleet’s FOR trend due to HILPs over time • Feedback successes and failures into the HILP reduction program to improve the process Richwine Consulting Group, LLC 79

Conclusions & Recommendations HILPs Happen!! • No power plant in immune to HILPs • While your staff must react to the “problems of the day” some resources should be devoted to searching for cost-effective ways to prevent, detect or mitigate HILPs • Addressing HILP causes and seeking solutions “before a HILP occurs” is a proven way to move from a fire-fighting to pro-active style of management Richwine Consulting Group, LLC 80

Conclusions & Recommendations The Future • Competition is here (or just around the corner) • Market-based business environments using terms like Commercial Availability to indicate the effects of your plant’s outages on the company’s profitability makes it crucial to better manage your plant’s reliability to be available when its value is greatest • A good HILP reduction program can help move you to becoming one of the industry leaders (or if already a leader to staying there) Richwine Consulting Group, LLC 81

EFOR After Scheduled Outages Week Following Schedule Outage Richwine Consulting Group, LLC 82

EFOR After Scheduled Outage Trend • If your plants exhibit this trend you can seek cost-effective ways to reduce this unreliability • If you cannot find ways to reduce the problem, you can incorporate this tendency into the dispatch optimization process (perhaps by not scheduling outages at two major units back-to-back or some other planning/scheduling method) Richwine Consulting Group, LLC 83

Forced Outage Rate Versus Demand Trend Richwine Consulting Group, LLC 84

Forced Outage Rate Versus Demand Trend • High Output Factor (maximum generation most of the time) units have fewer failures but take more time to repair • Low Output Factor (often generating at minimum and load-following) units have more failures but take less time to repair Richwine Consulting Group, LLC 85

tio n ua Ev al en ar w A n io at ic tif en Id es s Common Elements Phase 3 - Evaluation March 2003 Case Study Richwine Consulting Group, LLC 86

Capital Project Evaluation Process • Elements of an Evaluation Analysis – 1) IMPACT – A prediction of difference in future plant performance if the project is implemented versus if it is not implemented. – 2) WORTH of PERFORMANCE IMPROVEMENT – 3) COST – The total budget cost including equipment procurement and installation costs Richwine Consulting Group, LLC 87

Capital Project Evaluation Process - Impacts • Future with/without the project (positive/negative) – – – – Availability Efficiency O & M Savings (or increased cost) Auxiliary Power Requirements Maximum or Minimum Capacity Environmental Other quantifiable impacts Intangibles Richwine Consulting Group, LLC 88

Impact Data Sources • • Knowledgeable plant and support staff Engineering staff Plant data !!! Industry data !!! Manufacturers and consultants Other projects results Test Results Other Richwine Consulting Group, LLC 89

Capital Project Evaluation Process Part 2 • Timing – The second obstacle a project must overcome – Addresses the question “If a project is justified, when should it be implemented”. – Many “wear-out” project need to have this analysis performed based on their technical risk profile – All projects should be timed based on their economic risk profile Richwine Consulting Group, LLC 90

Capital Project Evaluation Process Part 3 • Prioritization - The third (and hardest) obstacle a project must overcome – Addresses the question “ If the company does not have all of the resources (money, time, manpower) necessary to implement all of the justified projects that should be done this year, which projects will hurt the least to delay? ” Richwine Consulting Group, LLC 91

Operations & Maintenance Economic Decision Analysis • Company’s business economics applied to day-to-day O&M decisions • Helps identify the best economic option for recovering from abnormal conditions • Helps identify the best economic option for establishing normal O&M programs Richwine Consulting Group, LLC 92

O&M Decision Analysis • Problem solution steps – Define problem and identify viable options – Quantify technical consequences of options – Combine technical consequences with company economics – Evaluate results and incorporate into decision Richwine Consulting Group, LLC 93

O&M Decision Example Leaking Feedwater Heater Problem Tube failure in 7 A feedwater heater Requires isolation of 6 A & 7 A heaters 1% efficiency loss during isolation Richwine Consulting Group, LLC 94

O&M Decision Example Leaking Feedwater Heater • Solution Options 1) Remove unit from service immediately, locate and plug leaking tube 2) Wait until weekend to repair 3) Wait until next planned outage and imbed repair 4) Wait until next forced outage of sufficient duration to imbed repair Richwine Consulting Group, LLC 95

O&M Decision Example Leaking Feedwater Heater • Consequences – Option 1 - repair immediately • • 48 hour outage during high demand period Overtime labor cost of $1000 Start-up cost of $20, 000 Total cost = $217, 000 Richwine Consulting Group, LLC 96

O&M Decision Example Leaking Feedwater Heater • Consequences – Option 2 - repair during weekend • • • 48 hour outage during lower demand period Overtime labor cost of $1000 Start-up cost of $20, 000 1% efficiency penalty until weekend Total cost = $137, 000 Richwine Consulting Group, LLC 97

O&M Decision Example Leaking Feedwater Heater • Consequences – Option 3 -repair during next planned outage • 1% efficiency penalty until next planned outage • Total cost = $202, 000 Richwine Consulting Group, LLC 98

O&M Decision Example Leaking Feedwater Heater • Consequences – Option 4 - repair during next forced outage • 1% efficiency penalty until next 48 hour outage – uncertain when next 48 hour outage will occur • Total cost range = $0 - $202, 000 – maximum cost of $202, 000 – “break even” point in 8 weeks Richwine Consulting Group, LLC 99

O&M Decision Example Leaking Feedwater Heater • What would YOU decide? – – Option 1 (repair now) Option 2 (repair during weekend) Option 3 (repair during P. O. ) Option 4 (repair during F. O. ) Richwine Consulting Group, LLC - $217, 000 - $137, 000 - $202, 000 - $0 -$202, 000 100

O&M Decision Example Leaking Feedwater Heater • If the same event happened at a different time the following economic results could happen: – – Option 1 - repair now Option 2 - repair during weekend Option 3 - repair during next PO Option 4 - repair during next FO $ 75, 000 $ 50, 000 $450, 000 $0 -$450, 000 Now what would you decide? ? ? Richwine Consulting Group, LLC 101

Planned versus Unplanned Outages • For every extra day of planned outage, unplanned outages only were reduced by 0. 6 of a day • This suggests that planned outages should be minimized in order to maximize availability • However, planned outages almost always occur during the non-peak season, when financial consequences are much lower by as much as ¼ • Therefore, the strategy that will result in the lowest cost of electricity is to maximize planned outages (within reason) so as to minimize the expensive forced outages Richwine Consulting Group, LLC 102

Operations & Maintenance Economic Decision Analysis • Applications – Maintenance • Reactive (e. g. planned outage extension) • Proactive (e. g. condition directed maintenance) – Operations • Reactive (e. g. tube leaks) • Proactive (e. g. pump operations) Richwine Consulting Group, LLC 103

Common Elements Phase 4 Implementation April 2003 Case Study A n io w at ar ic tif en es s en Id Ev n io at t en al em pl ua tio n Im Richwine Consulting Group, LLC 104

Implementation • • Project choice (economic plus intangibles) Financing Goal selection Monitor actual results and compare against expected results Awareness Richwine Consulting Group, LLC 105

Implementation • Goal Setting Case Studies – May & June 2003 – Are Reliability Measures Unreliable? ? – July 2003 – Planned vs. Unplanned Outages Effects on Goals Richwine Consulting Group, LLC 106

Problems with Current Indices • Factors – EAF, FOF, UCLF, etc. Factors use the entire time period as the denominator without regard to unit demand EXAMPLE: Peaking Gas Turbine 100 hrs/year demand 25 forced hours during demand EAF = 99. 71% FOF = 00. 29% Richwine Consulting Group, LLC 107

Problems with current indices • FOR, EFOR In Example FOR = EFOR = 25% In reality the GT is likely to have had many more FOH reported since GADS counts all forced outage hours, not just ones during demand periods. Therefore, actual EFOR statistics are much higher, often 60% +. Richwine Consulting Group, LLC 108

Equivalent Forced Outage Rate – Demand (EFORd) • Markov equation developed in 1970’s • Used by the industry for many years – PJM Interconnection (20 years) – Similar to that used by the Canadian Electricity Association (20 years) – Being use by the New York ISO, ISO New England, and California ISO. – Now a part of IEEE standard 762 & NERC-GADS Richwine Consulting Group, LLC 109

EFORd Equation: EFORd= [f(FOH) + fp(EFDH)] * 100% [SH + f(FOH)] Where: f = (1/r)+(1/T) (1/r)+(1/T)+(1/D) fp = SH/AH r= FOH/(# of FOH occur. ) T= RSH/(# of attempted Starts) D= SH/(# of actual starts) Richwine Consulting Group, LLC 110

EFORd Concept • Equation is complex, but concept is simple • Reported Forced Outage Hours are “reduced” • Reduction % is the ratio of Reserve Shutdown Hours to the Service Hours in the time period • This is an approximation (since actual demand hours are not collected by NERC) that estimates the hours on forced outage during demand • Advantage – We can calculate historic EFORd without collecting new data!!! Richwine Consulting Group, LLC 111

Example of EFORd EFOR, range from 3. 9 to 42. 4% EFORd, range from 3. 9 to 10. 6% Richwine Consulting Group, LLC 112

Implementation • Monitor Actual Results and Compare Against Expected Results – September 2002 Case Study – Predicting Unit Reliability • Feedback Into Awareness, Identification & Evaluation Phases Richwine Consulting Group, LLC 113

Common Elements January–April 2003 Case Studies A n io w at ar ic tif en es s en Id Ev n io at t en al em pl ua tio n Im Performance Improvement Richwine Consulting Group, LLC 114

The Future Transforming to a Market-Driven Business Environment Richwine Consulting Group, LLC 115

The Future Is Not What It Used To Be

Increasing Competition Is The Future Of Our Industry

Past Business Environment • Regulated – Suppressed Competition Cost (Prudent) + Profit (Mandated) = Price Avoid Risk Richwine Consulting Group, LLC 118

Evolving Business Environment • Market Driven – Increased Competition Price (Market) – Cost (Total) = Profit Identify, Quantify, and Manage Risk Richwine Consulting Group, LLC 119

Example of Risk/Reward Decisions • You are playing a video poker “jacks or better” game • You bet $5 • You are dealt the 10, jack, king and ace of hearts and the queen of spades • The reward for a straight is $20 • The reward for a royal flush is $2000 • Should you – 1) keep the five cards you are dealt for a sure $20 payoff? – 2) discard the queen of spades, hoping for the queen of hearts for a possible $2000 payoff? Richwine Consulting Group, LLC 120

Example of Risk/Reward Decisions Video poker example analysis Risk = $5 Reward Option 1 - $20 @ 100% probability = $20. 00 Option 2 - $2000 @ 1/47 probability = $42. 55 Reward/Risk Option 1 - $20/$5 =4 Option 2 - $42. 55/ $5 = 8. 51 (Actually better since other winning cards could be drawn; i. e. a different heart for a flush or a different queen for a straight) Richwine Consulting Group, LLC 121

Low Cost Producer • To be successful in a competitive business environment a company must become the Low Cost Producer • Becoming the Low Cost Producer will only be achieved when all employees are making better day-to-day decisions Richwine Consulting Group, LLC 122

Need Better • Resource Management – – People Plants Money Time Richwine Consulting Group, LLC 123

Transform People from Risk Avoidance to Risk Management Mindset • Any company’s only long-term sustainable competitive advantage is the quality of it’s people and the quality of it’s leadership Richwine Consulting Group, LLC 124

Management Impact • Only 20 - 25 percent of the variation in reliability can be explained due to design/mode of operation differences • The remaining 75 - 80 percent of the variation in reliability is due to differences in management Richwine Consulting Group, LLC 125

4 Pillars Of Change Leadership Climate & Culture Selection Richwine Consulting Group, LLC Training 126

Decision Making • Push decision making authority and responsibility down to the lowest appropriate level (decisions must be made quickly) Executive Management Plant Supervisor Individuals Richwine Consulting Group, LLC 127

Need Better • Decision Tools – Identify viable decision options – Combine technical consequences with economics – Evaluate options based on financials results – Monitor results and refine process Richwine Consulting Group, LLC 128

Need Better • Key Performance Indicators – EFOR (demand) – Commercial Availability • Un-weighted • weighted Richwine Consulting Group, LLC 129

Market-Based KPI’s May & June 2003 Case Studies • Demand EFOR – EFOR (demand) – Developed for non-base loaded units – Approximates the reliability of a unit during demand periods • Commercial Availability – Un-weighted – measures a unit’s availability only during demand periods – Weighted – measures a unit’s availability only during demand periods and “weights” each hour’s impact by the unit’s gross margin during that hour Richwine Consulting Group, LLC 130

Commercial Availability • Cannot benchmark directly except against your own units and their trends • Can benchmark indirectly using conditional probabilities plus plant’s actual economics Richwine Consulting Group, LLC 131

Conditional Probability When required (conditional) what is the likelihood (probability) that the unit will be able to generate at its rated capacity? Richwine Consulting Group, LLC 132

Conditional Probability. . . …has been shown to vary depending upon the plant’s economic necessity Richwine Consulting Group, LLC 133

Conditional Probability • Using NERC-GADS data we can determine probability distributions of Conditional Probability (C. P. ) for the peer group of each individual unit • There will be different probability distributions during different demand periods (peak season, day/night, weekday/weekend day, etc. • Selecting your unit’s optimum goal will start with these C. P. distributions Richwine Consulting Group, LLC 134

Commercial Availability Benchmarking • Example using Conditional Probabilities Hour G. M. potent Avail G. M. actual 1 2 3 4 5 6 7 8 9 10 Total $ 3000 $ 1500 $ 6000 $12000 $24000 $18000 $ 9000 $ 0 $73500 y y n n $ 3000 $0 $12000 $24000 $18000 $ 9000 $ 0 $66000 C. P. . 92. 92. 98. 98. 90 Richwine Consulting Group, LLC G. M. goal $ 2760 $ 1380 $ 5520 $11760 $23520 $17640 $ 8820 $ 0 $71400 135

Commercial Availability Benchmarking From Example Potential Gross Margin Actual Gross Margin Goal Gross Margin G. M. achieved above goal Traditional Availability Forced Outage Rate (d) Commercial Availability Goal C. A. Richwine Consulting Group, LLC = $73500 = $66000 = $71400 =($5400) = 60. 0% = 28. 6% = 89. 8% = 97. 1% 136

Commercial Availability Benchmarking From Example but available in hour 4 Potential Gross Margin = $73500 Actual Gross Margin = $72000 Goal Gross Margin = $71400 G. M. achieved above goal = $ 600 Traditional Availability = 70. 0% Forced Outage Rate (d) = 14. 3% Commercial Availability = 98. 0% Goal C. A. = 97. 1% Richwine Consulting Group, LLC 137

Commercial Availability Benchmarking From Example but available in all hours except 6 Potential Gross Margin = $73500 Actual Gross Margin = $49500 Goal Gross Margin = $71400 G. M. achieved above goal = ($21900) Traditional Availability = 90. 0% Forced Outage Rate (d) = 14. 3% Commercial Availability = 67. 3% Goal C. A. = 97. 1% Richwine Consulting Group, LLC 138

Commercial Availability Benchmarking 1) Identify your unit’s design & operational peers 2) Calculate the probability distribution of these unit’s Conditional Probabilities during their demand periods that are similar to yours. 3) Estimate your unit’s Optimum Economic Conditional Probabilities during each demand period (often the top quartile or top decile C. P. of your peers). 4) Apply those Conditional Probability goals to your unit’s economics (forecast or actual) using whatever definition of Commercial Availability you choose Richwine Consulting Group, LLC 139

Commercial Availability Benchmarking • Although this process might seem complicated remember the following adage: For every complex, difficult to understand, hard problem, there is a simple, easy to understand, WRONG solution!! Richwine Consulting Group, LLC 140

Commercial Availability Implications • Benchmarking – Selection – Comparisons Richwine Consulting Group, LLC 141

Commercial Availability Implications • Design Impacts – More or less redundancy? – More or less Condition Monitoring Systems? – More or less flexibility to respond to changing economic conditions in the future? Richwine Consulting Group, LLC 142

Commercial Availability Implications • Goals Systems – Commercial Availability helps provide a direct linkage between a plant’s performance results and its company’s financial results • Human Factors – it has been proven that only 20%25% of the variation in a plant’s performance is due to technical factors, while the remaining 75%-80% is due to human factors (May 2002 WEC case study) Richwine Consulting Group, LLC 143

Commercial Availability Implications • Maximizing Commercial Availability – How decisions are affected–plant & executive – Impact on current indices- most will look worse Richwine Consulting Group, LLC 144

Commercial Availability Implications • Perception by other stakeholders – – – – Company executives and board members Regulatory agencies Insurance Companies Bank Engineers Wall Street Stockholders Customers Richwine Consulting Group, LLC 145

Need Better • Goals Systems – Direct linkage between • Plant results • Corporate objectives Plant Goals Corporate Goals Richwine Consulting Group, LLC 146

#1 Problem Worldwide Goals Conflict Corporate Goals Plant Goals Richwine Consulting Group, LLC 147

Optimum Economic Availability October 2004 Case Study Richwine Consulting Group, LLC 148

Optimum Economic Availability O&M Costs Availability Richwine Consulting Group, LLC 100% 149

Optimum Economic Availability Top Quartile Frontier O&M Costs Availability Richwine Consulting Group, LLC 100% 150

Optimum Economic Availability Top Quartile Frontier Total O&M Costs Availability Richwine Consulting Group, LLC 100% 151

Optimum Economic Availability O&M Costs Total O&M Cost $ Cost of Unavailability $ Cost Of Unavailability Availability 100% Richwine Consulting Group, LLC 152

Optimum Economic Availability Total O&M Cost + Unavailability Cost O&M Costs Total O&M Cost $ Cost of Unavailability $ Cost Of Unavailability Availability 100% Richwine Consulting Group, LLC 153

Optimum Economic Availability Total O&M Cost + Unavailability Cost O&M Costs Total O&M Cost $ Cost of Unavailability $ Cost Of Unavailability Optimum Economic Availability 100% Richwine Consulting Group, LLC 154

Optimum Economic Availability Total O&M Cost + Unavailability Cost O&M Costs Total O&M Cost $ Cost Of Unavailability $ Cost of Unavailability Total O&M Cost Target Optimum Economic Availability 100% Richwine Consulting Group, LLC 155

Optimum Economic Availability Top Quartile Frontier O&M Costs Proactive Reactive Availability Richwine Consulting Group, LLC 100% 156

Optimum Economic Availability Total O&M Cost + Unavailability Cost O&M Costs Total O&M Cost $ Cost of Unavailability Proactive Cost Target Proactive Reactive Optimum Economic Availability 100% Richwine Consulting Group, LLC Reactive Cost Target 157

Need Better • Goals Systems – Direct linkage between • Plant results • Corporate objectives Plant Goals Corporate Goals Richwine Consulting Group, LLC 158

Traditional Plant Goals System • Goal Area – – – Weighting Availability Efficiency O&M Budget Control Safety Other Richwine Consulting Group, LLC 25% 15% 30% 10% 20% 100% 159

Market-Based Goals System • Objective – – Minimize a plant’s total controllable production cost (or maximize its contribution to corporate profitability) Richwine Consulting Group, LLC 160

Market-Based Goals System • Method – Convert a plant’s technical goals (availability, efficiency, etc. ) to the company’s economic goals – Develop economic forecasts of the worth of performance improvement and incorporate them into decision tools provided to production staff – Train production employees in the use of these tools, integrating their local “technical” knowledge with corporate economics – Give production management the flexibility to make tradeoffs between individual performance/spending goals in order to minimize the cost of electricity and/or maximize the corporate profitability Richwine Consulting Group, LLC 161

Market-Based Goals System • Goal Area – – Expectation EFOR deviation SOF deviation Efficiency Deviation Other performance areas 5% 7% 2% Cost $500, 000 $140, 000 $400, 000 Total Performance Deviation Cost $1, 040, 000 Operations & Maintenance Budget $5, 000 Total Controllable Production Cost $6, 040, 000 Richwine Consulting Group, LLC 162

Future - Market Oriented System • Consequences – – More revenue uncertainties More cost uncertainties More risk More opportunities Richwine Consulting Group, LLC 163

Summary • Change is occurring everywhere • Changes are not the same everywhere • Company specific programs should be developed and implemented that will allow each company to anticipate and respond quickly to its unique set of changes • The companies that are best able to respond to market-induced pressures will be the survivors Richwine Consulting Group, LLC 164

Performance Improvement Better Use of Reliability Data will be a Key Factor in Achieving and Sustaining Top Performance Richwine Consulting Group, LLC 165

Using Reliability Data to Improve Power Plant Performance Presented by Robert R. (Bob) Richwine Reliability Management Consultant Richwine Consulting Group, LLC RRR 2@bellsouth. net +1 -678 -231 -3606 Atlanta, Georgia, USA 30076 Richwine Consulting Group, LLC 166