Process Reliability Modeling for Clean Fuels ... - Maros and Taro
Process Reliability Modeling for Clean Fuels ... - Maros and Taro
Process Reliability Modeling for Clean Fuels ... - Maros and Taro
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<strong>Process</strong> <strong>Reliability</strong> <strong>Modeling</strong><br />
<strong>for</strong><br />
<strong>Clean</strong> <strong>Fuels</strong> Projects<br />
By<br />
Chuck Treleaven<br />
Jardine <strong>and</strong> Associates, Inc.<br />
August 13, 2003<br />
www.jardinesolutions.com<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
<strong>Process</strong> <strong>Reliability</strong> <strong>Modeling</strong><br />
<strong>for</strong><br />
All Capital Projects<br />
By<br />
Chuck Treleaven<br />
Jardine <strong>and</strong> Associates, Inc.<br />
August 13, 2003<br />
www.jardinesolutions.com<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Agenda<br />
• Definitions<br />
• Approach<br />
• Applications/Case Studies<br />
• Typical Findings/conclusions<br />
• Wrap up <strong>and</strong> discussion<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Jardine <strong>and</strong> Associates<br />
• Engineering Services <strong>and</strong> Technology<br />
• <strong>Process</strong> <strong>Reliability</strong> <strong>Modeling</strong><br />
• Since 1984 services both upstream <strong>and</strong> downstream<br />
• Utilize ACE, MAROS <strong>and</strong> TARO technology in studies<br />
• Offices in Houston, London, Glasgow, Kuala Lumpur<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
What it’s not<br />
<strong>Process</strong> <strong>Reliability</strong> <strong>Modeling</strong><br />
– Not Maintenance Centered<br />
Predictive Analysis<br />
– Not <strong>Process</strong> Simulation<br />
– Not Plant Linear Program<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
<strong>Process</strong> <strong>Reliability</strong> <strong>Modeling</strong><br />
• Strategic Unit-Level view of operations<br />
• Operations Strategy, <strong>Process</strong> Flows, Maintenance<br />
Issues<br />
• Develops operating efficiency <strong>for</strong> each unit<br />
• Calculates overall efficiency based on interactions<br />
between units<br />
• Uses sensitivity analysis to optimize overall<br />
operating efficiency<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Why <strong>Process</strong> <strong>Reliability</strong><br />
<strong>Modeling</strong><br />
• Business Planning Tool<br />
• Evaluates impact of future changes to current<br />
operation<br />
• One of IPA’s Value Improving Practices<br />
• Ranks competing projects<br />
Per<strong>for</strong>mance <strong>Modeling</strong><br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
eliability<br />
quipment per<strong>for</strong>mance<br />
ata (failure frequencies)<br />
ystem configuration<br />
Maintainability<br />
Maintenance resources<br />
Shift constraints<br />
Mob delays<br />
Spares constraints<br />
Relationships in the Modelling<br />
Availability<br />
Operability<br />
�Human factors<br />
�Start-Up Issues<br />
<strong>Process</strong><br />
�Equipment/System<br />
uptime<br />
Productivity<br />
Unit Costs/Revenue<br />
�Production Efficiency<br />
�Production losses<br />
�Equipment Criticality<br />
$$$$<br />
�Venture<br />
Econom<br />
�Product price<br />
�Manhour/spares costs<br />
�Discount rates<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
FDs/P&IDs<br />
esign Basis<br />
Field Z Basecase Model<br />
Gas Production Field Z <strong>and</strong> Basecase Production Model Efficiency<br />
Gas Production <strong>and</strong> Production Efficiency<br />
Summary - Per<strong>for</strong>mance<br />
F6 Vent System<br />
Atmos F6 Vent System Stack<br />
Atmos Vent Stack<br />
VS430 Vent<br />
VS430 Vent<br />
TT430 Tempx<br />
TT430 Tempx<br />
LP Vent System<br />
LP Vent System<br />
VS-425 Vent<br />
VS-425 Vent<br />
TT425 Tempx V415 scrubb<br />
TT425 Tempx V415 scrubb<br />
Atmos Vent Stack<br />
Atmos Vent Stack<br />
F6 Vent System<br />
Atmos F6 Vent System Stack<br />
LP Vent System<br />
Atmos Vent Stack<br />
LP Vent System<br />
P420A Vent<br />
Level control<br />
100.0<br />
P420A Vent<br />
VS430 Vent<br />
TT430 Tempx<br />
VS-425 Vent<br />
TT425 Tempx V415 scrubb<br />
Level control<br />
100.0<br />
VS430 Vent<br />
TT430 Tempx<br />
VS-425 Vent<br />
TT425 Tempx V415 scrubb<br />
Cond Pumps 420A/B<br />
V415 level<br />
V415 Lvlxdc V415 Lvlwrn<br />
Cond Pumps 420A/B<br />
Atmos Vent Stack V415 level<br />
V415 Lvlxdc V415 Lvlwrn<br />
Atmos Vent Stack<br />
P420B Vent Start Prob<br />
Level control<br />
100.0<br />
P420B Vent Start Prob<br />
Level control<br />
100.0<br />
P420A Vent<br />
Level control<br />
100.0<br />
P420A Vent<br />
Level control<br />
100.0<br />
Cond Pumps 420A/B<br />
VS Fan A<br />
Cond Pumps 420A/B<br />
100.0<br />
VS Fan A<br />
100.0 P420B Vent Start Prob<br />
VS Cndsr<br />
100.0<br />
VS Fans P420B A&B Vent Start Prob<br />
VS Cndsr<br />
100.0<br />
VS Fans A&B<br />
3<br />
20032004<br />
20042005<br />
20052006<br />
20062007<br />
20072008<br />
20082009<br />
20092010<br />
20102011<br />
20112012<br />
20122013<br />
20132014<br />
20142015<br />
20152016<br />
20162017<br />
20172018<br />
20182019<br />
20192020<br />
20202021<br />
20212022<br />
20222023<br />
2023<br />
Year<br />
Year<br />
Total production (mmbbl)<br />
Production Total production Efficiency (mmbbl) (%)<br />
Production Efficiency (%)<br />
VS Fan B<br />
100.0<br />
VS Fan B<br />
100.0<br />
VS Fan A<br />
LP Vent 100.0 System<br />
VS Fan A<br />
Plat A LP Vent Vent System 100.0 System<br />
VS Cndsr Plat A Vent System<br />
VS Fans A&B<br />
VS Cndsr<br />
VS Fans A&B<br />
VS Fan B<br />
100.0<br />
VS Fan B<br />
100.0<br />
LP Vent System<br />
Plat A LP Vent Vent System<br />
System<br />
Plat A Vent System<br />
V415 level<br />
V415 level<br />
V415 Lvlxdc V415 Lvlwrn<br />
V415 Lvlxdc V415 Lvlwrn<br />
Plat<strong>for</strong>m A<br />
<strong>Reliability</strong> Block Diagram Plat<strong>for</strong>m A 67 of 155<br />
<strong>Reliability</strong> Block Diagram 67 of 155<br />
Vent System<br />
Vent System<br />
Level control<br />
Level control<br />
Rev 16.03.00 By: DPCHK: FK<br />
Rev 16.03.00 By: DPCHK: FK<br />
Plat<strong>for</strong>m A<br />
<strong>Reliability</strong> Block Diagram Plat<strong>for</strong>m A 67 of 155<br />
<strong>Reliability</strong> Block Diagram 67 of 155<br />
Vent System<br />
Vent System<br />
Rev 16.03.00 By: DPCHK: FK<br />
Rev 16.03.00 By: DPCHK: FK<br />
Modelling<br />
RBDs <strong>Reliability</strong> Data<br />
100<br />
100<br />
90<br />
90<br />
80<br />
80<br />
Gas Production Efficiency (%)<br />
Gas Production Efficiency (%)<br />
70<br />
70<br />
60<br />
60<br />
50<br />
50<br />
40<br />
40<br />
30<br />
30<br />
20<br />
20<br />
10<br />
10<br />
0<br />
0<br />
Production<br />
Efficiency<br />
Lifecycle<br />
Simulation<br />
Model<br />
OPEX<br />
NPV<br />
Tank/Storage<br />
Strategy<br />
Equipment<br />
Criticality<br />
Maintenance<br />
Strategy<br />
Others<br />
Others<br />
19%<br />
19%<br />
Field<br />
Field<br />
Z<br />
Z<br />
Basecase<br />
Basecase<br />
Model<br />
Model<br />
Subsystem Criticality<br />
Subsystem Criticality<br />
LP Separation<br />
LP Separation<br />
4%<br />
4%<br />
Relief Valve<br />
Relief Valve<br />
Inspection<br />
Inspection<br />
6%<br />
6%<br />
Oil Treating<br />
Oil Treating<br />
7%<br />
7%<br />
Facilities Inspection<br />
Facilities Inspection<br />
7%<br />
7% Field Gas<br />
Field Gas<br />
Compression<br />
Compression<br />
9%<br />
9%<br />
Absolute production losses = 7.22%<br />
Absolute production losses = 7.22%<br />
Power Generation<br />
Power Generation<br />
26%<br />
26%<br />
LP Gas Sweetening<br />
LP Gas Sweetening<br />
22%<br />
22%<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
‘Traditional’ Refinery Unit<br />
Analysis<br />
• Models defined at equipment level<br />
• Detailed definition of maintenance /operations<br />
• Focus on equipment reliability/configuration<br />
• Key output is expected unit uptime/availability<br />
• Typically considering average annual<br />
per<strong>for</strong>mance<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Plant-wide<br />
<strong>Reliability</strong><br />
MTTR<br />
Unit<br />
Unit<br />
Configuration<br />
Configuration<br />
Traditional<br />
RAM Modelling<br />
Unit Interdependency<br />
Equipment Availability<br />
Component <strong>Reliability</strong><br />
•MTTF<br />
•RCA<br />
•FMEA<br />
Sales Strategy<br />
Unit Availability<br />
Maintenance<br />
Strategy<br />
• Overall Gasoline Production Efficiency<br />
• Individual Product Efficiency<br />
• Individual Product Volumes<br />
Plant-Wide <strong>Reliability</strong><br />
Unit Utilisation<br />
Storage<br />
Multi-stream<br />
(feed, intermediate & product)<br />
Operational Operational Flexibility<br />
Flexibility<br />
e.g. e.g. • Revised Slate<br />
• Slowdowns<br />
• Back-up Routes<br />
JARDINE<br />
TARO Modelling<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Refinery Wide Analysis<br />
• Strategic view of operations<br />
• Unit, not equipment level<br />
• 10 years, not 6 months<br />
• Relationships with surrounding units<br />
• Tankage <strong>and</strong> shipment<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Agenda<br />
• Definitions<br />
• Approach<br />
• Applications/Case Studies<br />
• Typical Findings/conclusions<br />
• Wrap up <strong>and</strong> discussion<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Refinery Unit Analysis<br />
• Model in detail reliability / availability per<strong>for</strong>mance:<br />
– Indenture level – equipment items<br />
– Failure <strong>and</strong> Repair Data (MTTF etc.)<br />
– Maintenance response times<br />
– Restart times<br />
• Equipment based reliability software-(Jardine’s ACE)<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
• What is objective of analysis?<br />
– Uptime/availability<br />
– Identify system modifications to improve per<strong>for</strong>mance<br />
(redundancy)<br />
– Maintenance workload<br />
– Spares optimization<br />
• Input data:<br />
– Equipment per<strong>for</strong>mance data<br />
– Level of analysis (equipment level, component level) – is<br />
determined by availability of data/in<strong>for</strong>mation<br />
– Scheduled Maintenance (Renewals)<br />
– Resource constraints<br />
Unit Analysis<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
• Objectives?<br />
Refinery Wide Analysis<br />
– Predict utilization factors<br />
– Identify refinery bottlenecks<br />
– Identify system modifications<br />
– Optimize reliability spending<br />
• Input data:<br />
– Unit per<strong>for</strong>mance data<br />
– Block flow diagrams<br />
– Stream routing<br />
– Utility system<br />
– Turnaround schedules<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
• Data collection<br />
Refinery Wide Analysis<br />
Methodology<br />
• On-site engineering assistance<br />
• Study basis document<br />
• Run TARO model<br />
• Assess per<strong>for</strong>mance of preliminary design<br />
• Run Sensitivities<br />
• Present findings to project team<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Agenda<br />
• Definitions<br />
• Approach<br />
• Applications/Case Studies<br />
• Typical Findings/conclusions<br />
• Wrap up <strong>and</strong> discussion<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Key Downstream Projects<br />
• Shell Global Solutions<br />
– ULSD/LSG project,<br />
– Steam distribution,<br />
– Hydrogen distribution,<br />
– Petrochemical networks<br />
• Shell Canada LSG/ULSD<br />
• ExxonMobil Joliet Refinery<br />
• CNRL – upgrading facility<br />
• SASOL GTL plants worldwide<br />
• ChevronTexaco gasifier plant<br />
• Petrola/ChevronTexaco Elefsis<br />
• Syncrude – Fort McMurray<br />
Upgrader<br />
• Sunoco LSG projects (3)<br />
• BP Whiting environmental units<br />
• BP Chemicals (PTA, PX, Styrene,<br />
TMA petrochemical plants<br />
worldwide)<br />
• OMV Schwechat refinery, Austria<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
• Modifications<br />
(US$10-200Million)<br />
– Hydrotreater<br />
upgrades/revamps<br />
– Debottlenecking<br />
– Utility upgrades<br />
Project Types<br />
• New built units/plants<br />
(US$100-1000 Million)<br />
– New PTA/PX plants<br />
– New plasticizer plant<br />
– Elefsis refinery upgrade<br />
– New hydrotreaters<br />
(LSG/ULSD)<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Two Case Studies<br />
• Shell Canada Montreal<br />
• USA Refiner<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 1 – Montreal Refinery<br />
LSG Upgrade<br />
• Shell Canada was implementing a gasoline sulphurreduction<br />
program<br />
• Employing Institut Francais du Petrole (IFP) Prime<br />
G+ technology<br />
• To be implemented at Montreal (MER) <strong>and</strong> Sarnia<br />
(SMC) refineries with gasoline sulphur levels of<br />
30ppm with minimal octane loss<br />
• Each project capital expenditure was approx.<br />
US$50 Million<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 1 – Analysis objectives<br />
• Validate the technology availability<br />
• Assist in design decision making process regarding :<br />
– Unit sizing<br />
– Equipment sparing<br />
– Equipment design<br />
• Generate equipment criticality listing<br />
• Integrate the impact of outside battery limit events<br />
• Assist into developing maintenance strategies<br />
(maintainability: spare parts decisions, equipment design)<br />
Noted that study was instigated too late to effect design changes<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Shell Montreal Refinery Configuration<br />
CCU Unit<br />
(Cat Naphtha)<br />
Des. Cap: 18,000 BPSB<br />
TK-74<br />
Volume: 90,000 bbls<br />
TK-105<br />
Volume: 50,000 bbls<br />
Refinery Off-spec Storage:<br />
Product in TK-105 needs to be recycled<br />
through the Crude Distillation Unit<br />
GHT<br />
Des. Cap: 20,000 BPSB<br />
Norm Cap.: 18,000 BPSD<br />
Min. Cap.: 8,000 BPSD<br />
Over Capacity: 10%<br />
Normal Route<br />
LCN<br />
HCN<br />
1st 1 Backup Route to Off-spec Tank<br />
st Backup Route to Off-spec Tank<br />
TK-61<br />
Volume: 47,500 bbls<br />
TK-60<br />
Volume: 47,500 bbls<br />
2nd 2 Backup Route in case of storage tank top-out<br />
nd Backup Route in case of storage tank top-out<br />
Recycle Route<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 1 – Key configuration<br />
parameters<br />
• Design feed rate to GHT is 18 Mbbls/d<br />
• GHT unit has 10% overcapacity<br />
• 90 Mbbls dedicated GHT storage<br />
• + additional 50 Mbbls offspec storage – requires rerun<br />
through crude unit<br />
• No downstream export constraints<br />
• GHT modelled at equipment level<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 1 Results –<br />
GHT Unit Criticality<br />
Overall GHT Availability 97%<br />
Other Critical Equipment<br />
2.8%<br />
Hydro/Splitter Section<br />
12.1%<br />
Hydrogen Supply<br />
13.4%<br />
HCN/HDS Section<br />
33.0%<br />
Power Trips - GHT only<br />
0.7%<br />
Instrument Trips - GHT<br />
only<br />
0.0%<br />
GHT Turn Around<br />
38.0%<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 1 – Results<br />
Unit Utilization<br />
• Predicted onstream factor <strong>for</strong> CCU unit is 96.4%<br />
• Large available storage + 10% GHT overcapacity<br />
effectively decouples CCU per<strong>for</strong>mance from GHT<br />
• GHT onstream factor is mainly determined by<br />
available feed from CCU – not by its own<br />
availability/uptime<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 1 – Sensitivity Analysis<br />
Overcapacity negates the use <strong>for</strong> redundant pumps<br />
Reduction of GHT overcapacity from 10% to 5% does not<br />
noticeably impact on achieved GHT per<strong>for</strong>mance:<br />
CN Production Efficiency %<br />
0.963<br />
0.962<br />
0.961<br />
0.96<br />
0.959<br />
0.958<br />
0.957<br />
0.956<br />
Montreal Refinery: CN Production Efficiency (%)<br />
0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10%<br />
GHT Overcapacity %<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 1 – Conclusions<br />
• HCN/LCN production efficiency is driven by<br />
feed availability from the CCU<br />
• The intermediate storage negates any impact<br />
from GHT unavailability<br />
• Potential <strong>for</strong> decreasing CAPEX or OPEX<br />
through accepting lower GHT availability <strong>and</strong> /<br />
or lower overcapacity margin without significant<br />
impact production<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
How Useful Was the Work?<br />
• Highlighted the need <strong>for</strong> intermediate tank planning<br />
• Unit size could have been reduced<br />
• Developed alternate scenarios to assess impact <strong>and</strong><br />
assist decision-making: metallurgical problems; spare<br />
pumps; unit capacity<br />
• Impact of H2 availability quantified <strong>and</strong> found worse<br />
than expected<br />
• Changed design of feed exchanger<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 2 – Overall Refinery Analysis<br />
• Major refinery upgrade to meet LSG spec<br />
• Key changes to refinery configuration:<br />
– Addition of FCC Splitter unit <strong>and</strong> Merox unit<br />
– PRTR/HDF/CCR units revamped to increase capacity<br />
– Increased steam dem<strong>and</strong> resulting in increased loading of<br />
boilers (reduction in spare capacity)<br />
• Assess the ability of the refinery to deliver the<br />
desired quantities of gasoline subsequent to the<br />
revamp<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 2 – Block Flow Diagram<br />
CDU<br />
COK<br />
ASP<br />
CHD<br />
FCC<br />
Sales<br />
Sales<br />
PRTR<br />
FCC<br />
Splitter<br />
Sales<br />
HDF<br />
ALK<br />
CCR<br />
MEROX<br />
Sales<br />
Sales<br />
Sales<br />
Sales<br />
Direct Link<br />
between<br />
FCC/PRTR<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 2 – Results<br />
Impact of upgrade project on bottom line per<strong>for</strong>mance:<br />
2.1% reduction in achieved gasoline production efficiency<br />
Why?<br />
• FCC on-stream factor reduces by 1.4%,<br />
• CHD on-stream factor reduces by 1.3%<br />
• CDU on-stream factor reduced by 2.7%<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Case Study 2 – Improvement Options<br />
• Independent steam supply <strong>for</strong> CCR =0.4%<br />
increase in gasoline production efficiency<br />
• Fresh feed capacity increase <strong>for</strong> FCC =0.2%<br />
increase in gasoline production efficiency<br />
• More time between catalyst change-out<br />
shutdowns =increase in production efficiency by<br />
0.2%<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Agenda<br />
• Definitions<br />
• Approach<br />
• Applications/Case Studies<br />
• Typical Findings/Added Value<br />
• Wrap up <strong>and</strong> discussion<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Specific TARO Analysis Conclusions<br />
examples<br />
• Overcapacity allows reduction in redundancy/availability<br />
• Additional steam source improves key product efficiency by 0.4%<br />
• Available storage tanks could be taken out of service without reducing<br />
unit on stream factor<br />
• Analysis shows unit loading will be significantly lower than design<br />
capacity<br />
• Removal of the spare feed charge pump will not reduce the on stream<br />
factor<br />
• Potential <strong>for</strong> 0.6% efficiency improvement if cross-over line is installed<br />
between two units increasing operational flexibility during outages<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
General Findings of <strong>Clean</strong> Fuel<br />
Projects TARO analysis<br />
• Projects focus on unit availability only<br />
– Missing opportunity to save CAPEX by balancing<br />
availability/overcapacity/storage.<br />
• Projects increase loading on key utility systems<br />
– Reduces available redundancy<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Deliverables – Value Added<br />
(System ‘Knowledge’)<br />
• Quantifying impact of unit reliability on product yield<br />
• Develop underst<strong>and</strong>ing of refinery ‘bottle-necks’<br />
• Assessing impact of different sparing philosophies<br />
• Assessing impact from storage capacities, <strong>and</strong> additional capacity to<br />
enable re-cycling without impact on normal throughputs<br />
• Quantifying potential sales under-deliveries<br />
• Impact of scheduled turnarounds - optimization<br />
• Establishing unit reliability targets <strong>and</strong> benchmarking norms<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Agenda<br />
• Definitions<br />
• Approach<br />
• Applications - Case Studies<br />
• Typical Findings<br />
• Wrap up <strong>and</strong> discussion<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Per<strong>for</strong>mance <strong>Modeling</strong><br />
• Uses <strong>Reliability</strong> <strong>and</strong> Unit interaction<br />
• Asset evaluation/Asset modification<br />
• <strong>Clean</strong> <strong>Fuels</strong> Projects<br />
• Equipment vs. unit models<br />
• Ongoing planning tool<br />
• How are your projects evaluated?<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
Questions<br />
<strong>and</strong><br />
Discussion<br />
2003 <strong>Clean</strong> <strong>Fuels</strong> Challenge
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