Asset Investment Management (AIM) March 2017

Transcription

1 Asset Investment Management (AIM) March 2017

2 AIM Introduction Designed to demonstrate the benefits of different asset management strategies. Requirement to plan and implement different asset management strategies. Avoidance of failure Reduction in operating cost Regulatory drivers Cost of replacement AIM has been developed to an effective asset related method to plan, justify and implement effective risk management strategies.

3 What is AIM? 3

4 Methodology 1. Asset health index (HI) and aging rate 2. Probability of failure for each asset (POF) 3. Consequences of failure 4. Financial risk 5. Future scenarios and intervention options Health Index Probability of failure Consequences Risk 1 10 L M H L M H L M H

5 Condition - Health Index

6 AIM End-to-End Solution Inspection Data Client AIM Oil Test Records Asset Management System Data Interface Area Defect Records Nightly Data Update and Model Run 6

7 Data Requirements AIM maximises the value of asset data by accepting data from a wide variety of sources, including; Corporate data stores/systems Non controlled sources such as: Excel XML/CSV Qualitative data Business rules Expert knowledge Historical experience 7

8 Data Types Asset Definition Data Condition Data Test Data Fault Records Location/ Environment Duty Filters Risk/Criticality Network Performance Financial Safety Environment

9 Application Architecture 1. AIM Asset Investment Management Visualisation Analytics Engines Static Views Custom Views Dashboards Network View % replace ment Target interven tions CNAIM interve ntions Smart Interve ntions AIM Model and Data Broker User Interface Data Integration Data Repository Algorithm Engine API CNAIM CBRM CNAIM AIM Core Target Modelling Engines 3 rd Party Modelling Engines

10 Value delivered by AIM AIM has discrete asset models Captures companies engineering knowledge about assets Analysed asset by asset harder initially, but worth it Monetarised risk and consistent methodology allow different assets to be compared. Assets can be viewed by:- Health now or at any point in the future Probability of failure / consequences of failure Financial Risk This approach has helped clients typically achieve the same results in terms of risk profile for a 20% in capital investment

11 AIM in more detail

12 AIM Model Families Model Families: Common Network Asset Indies (CNAIM) electricity distribution CNAIM flexible calibration AIM Standard Models AIM Standard Models with flexible inputs and calibration CBRM Bespoke Target Development Optional Extras: Data Mappings Enhanced Methodology CNAIM Interventions Smart Interventions Integration Customised Data Interface Customised Reports

13 AIM Standard Models 1. LV Pole 2. LV UGB 3. LV Switchgear and Other 4. HV OHL Support - Poles 5. HV Switchgear (GM) - Primary 6. HV Switchgear (GM) - Distribution 7. HV Transformer (GM) 8. EHV OHL Support - Poles 9. EHV OHL Fittings 10.EHV OHL Conductor (Tower Lines) 11.EHV OHL Support - Towers 12.EHV UG Cable (Gas) 13.EHV UG Cable (Non Pressurised) 14.EHV UG Cable (Oil) 15.Submarine Cables 16.EHV Switchgear (GM) 17.EHV Transformer kV OHL Fittings kV OHL Conductor (Tower Lines) kV OHL Support - Tower kV UG Cable (Gas) kV UG Cable (Non Pressurised) kV UG Cable (Oil) kV CBs kV Transformer 26.LV Cables 27.HV Cables

14 AIM Standard Models Methodology Overview Aligned with CNAIM but with additional functionality and control over calibrations Health Assessment Location Factor, Duty Factor, Initial Health Index (HI1) Observed condition up to 10 inputs for each asset class Measured condition up to 10 inputs for each asset class Years to End of Life and predicted Year of Intervention Oil analysis (DGA, FFA) for transformers with modified rate of change to account for duration between tests Oil analysis diagnostic flags for transformers Oil Condition for tapchangers and transformers inputs for different oil types (mineral, ester) Reliability separate component attributes for transformers and steel towers B2 Forecast Ageing Rate including clause to prevent early mortality Current and future year health score, HI Bands for reporting Current and future Probability of Failure K formula adapts to client failure rate

15 AIM Standard Models Methodology Overview Criticality / Consequences Network performance Safety Financial Environment Total Consequence Criticality Index Monetised Risk for Current and Future Years New Asset Risk, Delta Risk % Replacement Intervention including simple costing and Risk future year Target Intervention including simple costing and Risk future year HI Y0-Y25, per asset tabular view, no intervention

16 AIM Standard Models Reporting Example HI current year vs HI future year graph histogram

17 AIM Standard Models Reporting Example Investment scenarios risk vs time

18 AIM Standard Models Additional Features Single asset view Separate component identification for 132kV transformer system and transformer and roll up of components using maximum (to cater for Single Phase Transformers) Data population report Data population history report Calibration update report Upload intervention from.csv for target interventions Per asset data population

19 AIM Standard Models Optional Extras Defect/Fault/SOP analysis Vegetation module Leak rate analysis (e.g. for Oil or Gas Cables) FFA/DGA correction due to top ups/oil change Highly configurable criticality inputs with switches Non Condition failures or associated functionality POF modifiers this may form part of a future implementation Test result analysis (other than that presently included in CNAIM, such as DGA for Transformers) Manufacture date graph/result aggregation (replaced by age) Separate failure mode calculations, relative POF process, risk per failure mode etc. Data Transformations/mappings bespoke to client NPV Bushings Result extraction bespoke to client

20 Optional Extra - Bushings Option provided as add-on to Transformer Model Standard methodology to HI/FHI only Bushings are rolled up to make Maximum Bushing HI Per transformer The HI for all Bushings provided on Single Asset View for Transformer

21 Optional Extra - NPV Year by year calculation of discounted delta risk Year by year calculation of NPV Calculation of optimum replacement year for each asset Calculation of HI in replacement year Count of asset replacements in each year in a table Count of asset replacements in each year in a histogram Single asset view NPV profile

22 Optional Extra - Mappings Transforms data to form required by Standard Model / CNAIM model Available on all families of assets May include modules/sophisticated modelling

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