5 Reliability Modeling for Utilities Projects –Scouting Phase -- Shell

8/13/2019 5 Reliability Modeling for Utilities Projects Scouting Phase -- Shell

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Reliability Modeling for Utilities Projects Scouting Phase

Ryan Stephens

Celesta White

Nazim Nathoo


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Outline

Introduction & RM Overview

RM for Utilities Example: Decision-making for Scouting Phase

Cogen Project


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What is a Reliability Modeling Study? Reliability Modeling Study is a

- structured process to mathematically simulate the stochasticperformance of plant hardware and process systems as well as

local/global network of systems. Results can be used by project teams to .

- ensure current, new and revamped plants can meet definedoperating/project premises such as production levels, availabilitytargets, environmental regulations, etc. For new and revamped

plants, ensure design meets premise for the lowest capitalinvestment.

- make objective data-driven decisions around appropriate equipmentcapacity, sparing philosophy and system/hardware selection optionsto meet project premises get the emotion out!

- assist with defining feed and product contracts as well as security ofsupply

- determine storage and logistics requirements.

- assure project funding entities or lenders that their investment willresult in the expected return (production).


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Definition of Terms RM

Up TimeAvailability = ----------------------------------

Up Time + Down Time

Actual (Projected) Production

Capacity Utilization Production Efficiency = -------------------------------------------Production Capacity*

*Design, Maximum, Business Plan

Copyright 2008 by Shell Oil Company. All rights reserved.


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Plant-Wide Reliability

Individual Product Efficiency Individual Product Volumes

Traditional

RAM Modelling

MaintenanceStrategies

Unit Availability

Equipment Availability

Storage and Inventory Management

Unit Interdependency

Operational Flexibilitye.g. Revised Slate

Slowdowns Back-up Routes

Component Reliability

MTTF RCA

FMEA

UnitConfiguration

MTTR

Sales Strategy / Logistics

System Configuration

Reliability Modeling

Unit

Restarts

Unit Capacities

Utilities

Unit Utilization PerformanceForecasting


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Applications and Scope This methodology is applied to a wide range of assets, such as:

- Refineries

- Petrochemical complexes

- Gas production and distribution networks- Utility production and distribution networks

- Systems involving product transport and logistic (shipping, rail,trucks, pipelines)

- Upstream extraction and processing Depending on the asset and the objectives of the study, the

scope of the project might include:- Feedstock availability

- Multiple production plants (down to equipment level)

- Intermediate tanks

- Product tanks

- Product export

- Utility systems


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Performance Analysis: Typical

Objectives Quantifying the future performance of the system

and its components (production and utilization).

Optimization of the system design (e.g.configuration, redundancy, storage, capacity,equipment sparing, etc).

Optimization of the asset operations (e.g.

maintenance philosophy, inventory management,product export, load shedding rules, etc).

Identification of bottlenecks and key performancedrivers (e.g. where to focus reliability improvement

efforts). Evaluation and prioritization of investment

opportunities (based on life cycle cost analysis).


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Reliability Modelingfor Utilities


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RM vs. Excel-based Analyses

Excel or spreadsheet-based analyses of utility

systems do not provide a complete, in-depthview of likely outcomes- Such analyses may under or overestimate sparing done via

N+1, N+2 type approaches.

Operating reality, of course, involves random,unplanned and stochastic events.

- RM attempts to emulate real-life behavior by taking into

account the stochastic operational behavior of bothproducers and users in a utility (or any production) system.


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Background Shell site must comply with upcoming regulations

limiting emission of NOx, SOx and dust, which cannot

be done with current equipment and employed fuelmix.

The objective of the Cogen Scouting Study was to

identify the future steam balance and optimal steam &

power generation facilities for the site, in order to:- Comply with emissions regulations,

- Increase steam & power generation efficiency,

-Reduce CO2 footprint,

- Increase reliability,

- Increase operational flexibility,

- Allow capability for integration with a potential JV project in

proximity to the site.


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Scope of Reliability Modeling

Several options were screened for ranking

based on NPV, reliability, CO2 efficiency,CAPEX, JV integration, and flexibility of steambalance. These options were narrowed down

to 3 scenarios for further investigation.

Shell Global Solutions was asked to conduct a

more detailed reliability analysis of these

options to help the project team to betterunderstand the impacts of these options on

HP steam reliability.


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Basic Assumptions The reliability study was limited to the following scope:

- HP Steam System Only: The impacts to the MP and LP

system are impacted by the HP steam demand as defined bythe individual HP steam users.

- In practice, as much of the scheduled maintenance aspossible will be forced to coincide with plant turnarounds. Asthe turnaround schedule is not yet confirmed, the studylooked at the impacts if all scheduled maintenance could notbe done in conjunction with plant TAs.

- Cracker trip scenario was included.

- System Life was 19 years (3 full GT maintenance cycles).

- Simulation Start Year = 2010.


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Option Descriptions

Option Description

Option 0.1

Base Case: 1 Fr6B GT + 2 end-of-life HP Steam

Boilers with stand-alone capability + 1 stand-alone HPsteam boiler

Option 2aMinimum Export Cogen Case: 2 parallel Cogen Trains+ 1 new Auxilliary Boiler

Option 2b 3P Integration Cogen Case: 1 Cogen Train + 1 newAuxilliary Boiler + 3rd Party Steam Import

Option 2cInterim Case: 1st Cogen Train + old GT + 2 old HPSteam Boilers

Option 3Maximum 3rd Party Integration: 2 new Auxilliary

Boilers + Steam & Power import


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Failure & Scheduled Maintenance DataComponent Failure Mode MTTF (yr) MTTR (hr) Impact (%)Heavy Duty GTs (old) Trip 0.02 2 100

Unplanned Shutdown 1.00 72 100

Offline GT Wash 0.17 4 100

Heavy Duty GTs (new) Trip 0.08 3 100



Heavy Duty GTs (IGCC, syngas) Trip 0.02 2 100



Boilers (old) Trip 0.25 3 100


Boilers (new) Trip 0.50 2 100


HRSG Trip 0.50 2 100

Unplanned Shutdown 2.00 72 100Offline GT Wash 0.17 1 100

Cracker Trip 1.00 2 100

Public HV grid Blackout 25.00 24 100

Unscheduled Failures

Component Activity Frequency (yr) Duration (hr)

Heavy Duty GTs Combustor Inspection 1.0 72

Hot Gas Path Inpsection 3.0 168Major Overhaul 6.0 504

IGCC GTs Combustor Inspection 0.5 72

Hot Gas Path Inpsection 3.0 168

Major Overhaul 6.0 504

Boilers (old) Preventative Maintenance 2.0 672

Boilers (new) Preventative Maintenance 4.0 504

HRSG (with cold air fan) Preventative Maintenance 4.0 336

Scheduled Activities


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Overall Plant Availability

# /

(/)

()

*

0. 1 11.

0. 1 2.

2. 10 . .% .%

. 1 . .0% .%

2. 1 .1 .% .%

2. 11 . .% .%

.2%

.2%

*

.

While the system will operate at 100% steam demandfor over 99% of the time, when there is an outage it isimportant to understand the duration and extent of theexpected outages in order to plan mitigation (i.e., loadshedding) accordingly.


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Results Summary

While the system will operate at 100% steam

demand for over 99% of the time, when there

is an outage it is important to understand theduration and extent of the expected outages in

order to plan mitigation (i.e., load shedding)

accordingly.


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Expected Shortfall Duration

0%

10%

20%

0%

0%

0%

0%

0%

0%

0%

02 2 2 2 2 2

0.1

2

2

2


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Expected Shortfall Size

0%

10%

20%

0%

0%

0%

0%

0%

0%

0%

12 1210 101 1200 20020 2000 000 0

0.1

2

2

2


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Conclusions The majority of the outages for Option 0.1

occur when one boiler is down for

maintenance (either scheduled or unplanned)and another boiler trips. For this case, GT

trips do not impact steam production, and is

therefore the most reliable scenario even withthe less reliable old boilers.

For the three new cases, most of the outages

occur when a GT trips (2 hrs) or requires anoff-line wash (4 hours) during an extended

outage of another steam producer.


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Conclusions (2) The reliability model provided quantitative

insight into the differences in both power and

steam reliability of the various optionsexamined, including expected downtime

duration & extent so that the project team

could begin thinking of mitigation and loadshedding options.

5 Reliability Modeling for Utilities Projects –Scouting Phase -- Shell

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