Automation and sensing of string/combiner box level failures on utility scale solar farm SCADA data

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Supervisor

Research areas

Description

One of the challenges of solar farm operation, is determining the locations of performance limiting solar panels. 3MVA central inverters are now state-of-the art, hence over 9000 panels are aggregated behind one maximum power point tracker. Isolating underperforming panels has the obvious benefit of improving plant operation, however sometimes more importantly it enables panel failures to be more closely tracked which has implications on panel suppliers obligations.

You will work with the asset management team at CWP Renewables to develop a methodology for assessing string level failures from SCADA data. You will have unparalleled access to two utility scale solar farms SCADA data (under a NDA) where you will develop the fault sensing algorithms. Your methodologies will them be deployed in the automatic debugging of a solar farm operation.

This is and external project supervised by Andrew Thomson <Andrew.Thomson@cwprenewables.com>.

Requirements

Competencies in programming will be necessary.

Updated:  10 February 2019/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing