1. Assessing the Reliability of Large Scale Distribution Networks with Different Asset Management Strategies and Resource Constraints David Clements Pierluigi Mancarella 12/11/14

2. Not how but why? Both industrial and academic studies are generally carried out on small areas of network Doing so requires making assumptions about surrounding network and repair crews Purpose of this work to understand when this is valid and when it could lead to incorrect results

3. How (Briefly) A Sequential Monte Carlo Model Incorporating Hidden Failures in protection Assets Maintenance Resource Constrained Repair (Only one at a time) Open Ring Topology (5 Transformers, 40 feeders, 20 rings). Scaled up either through assumptions or in software.

4. More complicated version Check for Line Failures Generate Breaker Failures Capture Supply Lost Reconfigure Network to Restore Supply Capture Supply Lost Repair Faults Maintenance Events Finish Period=0 Start True False Is Fault present on network? Period=Period +1 Period = NextFailure Event True False

5. Case Study Look at predicting network performance for different reliability levels 3 Ways to consider staff levels Ignore it! Model a single piece of network and assume staff are always available for repairs. Repairs don’t affect maintenance. Make some assumptions. Model a single piece of network but take account of affect of repairs limiting maintenance. Model Everything!

6. Case Study

7. Add Condition Monitoring

8. Why? “It’s obvious” But hard to quantify, not necessarily understood by everyone It’s financially significant: we need to get this right Networks Maintenance Team Responsible For Percentage ErrorCost due to Incentives (Millions) Failure RateUnlimited Manpower Limited Manpower With Assumptions Unlimited Manpower Limited Manpower With Assumptions Standard20.6%0.0% £ 2.0 £ 0.1 Standard64.8%0.9% £ 16.1 £ 3.0 Double23.0%0.3% £ 9.8 £ 1.0 Double630.0%10.1% £ 99.5 £ 33.6 Double (Affect of Condition Monitoring)65.9%0.5% £ 19.6 £ 1.6

9. Any Questions?