Learnings

Outcomes

The MILES project was able to detect seven faults that existing UK Power Networks’ systems also detected. MILES was able to pinpoint the faults to within 200-400m of accuracy. This is good for an overhead line network. However, UK Power Networks will not be developing the project further as it was determined that MILES is not as cost competitive as some newer fault passage indicators, as both the hardware and software costs of MILES were cost prohibitive relative to fault passage indicators that emerged during the project period. It should be noted that MILES may be more useful in networks where the overhead line spans longer distances. Typically, very large and rural areas, such as in Canada where the technology was developed.

Lessons Learnt

1.                   MILES is a novel means of fault location and is accurate to within 200-400m on an 11kV OHL feeder network. This exceeds the performance of present FPIs.

2.                   The accuracy of the fault’s location was directly correlated to the type of fault. The MILES Algorithm had better accuracy for Phase to Phase versus Phase to Earth. Improvements to the algorithm were identified and were to be explored further had we chosen to adopt into business as usual. Provision of additional data sources to the algorithm were also to be considered.

3.                   Fault location issues identified were:

a.       Small Voltage Variation – A fault is located based on a non-significant voltage variation. This is caused by small voltage variations produced by a phase-to-ground fault.

b.       Signal synchronisation when MILES is unable to synchronize waveforms from multiple sensors. This problem occurs more frequently when many faults are recorded in a short period of time and when the voltage variation is small.

c.        Bad topology – This occurs when sensors are temporarily displaced on a different feeder by a switching operation. The network is then in an abnormal operation. Bad topologies caused by abnormal network configuration could be resolved by interfacing with the ADMS for MILES to receive current switch states and adjust its topology accordingly.

4.                   The reliability of the sensors used in the project was low. Five of thirty sensors failed during configuration or in the field. Reliance on single type of sensor is also a risk to the solution. Alternative sensors were identified and were to be explored further had we chosen to adopt into business as usual.

5.                   MILES, and similar systems which leverage monitoring data in novel ways, may result in more accurate solutions than simpler monitoring equipment such as FPIs, but may not be able to outcompete them in financial terms, due to high hardware and software costs. 

6.                   Simple monitoring equipment may also develop and get better and/or cheaper over time as well, thus the business case will evolve and will be monitored.