This document summarizes a fault level study conducted collaboratively between Aurora Energy and Transend. It outlines the methodology used, including computer modeling of the distribution network using Geomedia and DINIS software. The results identified 10 sites with elevated fault levels. Further actions proposed include prioritizing sites based on a risk metric, gap analysis to define constraints and future goals, and developing costed options to mitigate risk in a value-based manner.

1. Fault Level Study
Kurt Pudniks
20/01/2012
I like talking to engineers best. They build bridges, they’re very precise, very
disciplined, yet I find they have roving minds
--Ralph Richardson, English writer

2. Overview
• Fault level management
– Collaborative risk management (Transend + Aurora)
– Review of initial report
– Fault risk metric
• Computer modelling
– Geomedia
– DINIS
• Results
• Further actions

3. Fault level management
• Risk management
– Awareness of hotspots
– Costed options to mitigate risk
• Review of Initial report
– Identified 10 sites of elevated fault level
• Fault risk metric
– A fractional quantity
• (fault level) / (fault rating)
– Fault level
• Two levels modelled by DINIS min and max
– Fault rating
• Inherent (+ relatively constant) property of the distribution network

4. Computer modelling
• Geomedia
– Geospatial model with T’s, cables, conductors, fuses, switches
– Thematic colour coding (around 13kA connection agreement)
• LEVEL RATING
• 0kA – 10kA blue red
• 10kA – 15kA purple purple
• 15kA – 100kA red blue
• DINIS
– Fault level study possible with min and max upstream configurations
– Export and overlay fault level per T node (CSV file)
• Following slides show results
– Prelim concept
– Results across ~10 sites (excl Wesley Vale)

6. Results
• 10 sites
– Bridgewater
– Chapel Street
– Creek Road
– Electrona
– Emu Bay
– Kingston
– Mowbray
– Rokeby
– Trevallyn
– Wesley Vale

15. Further actions
• Collaboration with Transend
– Prioritise based on risk metric (fault level / fault rating)
– Elimination of low risk sites
– Focus on details of higher risk sites
• Gap analysis
– Define the gap
– Understand the current constraints (contours)
– Develop a future goal state (contours)
• Costed options (landscaping exercise)
– Expensive silver bullet solutions
– Cheaper, targeted, distributed solutions
– Chart the value for money (ROI) against risk metric
• Maybe iB/C aka value based planning (multi attribute optimisation)