fulcrum3d solar and wind forecasting for the nem€¦ · fulcrum3d cloudcam solar forecasting for...

Fulcrum3D Solar and Wind

Forecasting for the NEM

ARENA Insights Forum 25 June 2019

AGENDA

2

1.Who is Fulcrum3D?

2.Project overviews:

o CloudCAMTM solar forecasting for the NEM

o Wind forecasting for the NEM

3.What we have learnt so far.

2ARENA Insights Forum Fulcrum3D Solar and Wind Forecasting for the NEM 25 June 2019

• Robust state-of-the-art technology solutions that add value to

wind and solar investments

• Founded in 2011 by the existing management team

• Track record in technology development and commercialisation

(e.g. Fulcrum3D Sodar, Solar Monitoring, FlightDECK, CloudCAM)

• Strengths in hardware, software, data management, comms and

cybersecurity

Who is Fulcrum3D?


Clients we Support


Fulcrum3D CloudCAM Solar Forecasting

for the NEM Project

Project Partner: Genex Power Project overview:

• Installed nine Fulcrum3D CloudCAMs at Genex’s 50MW Kidston Solar Farm.

• Initial focus is on providing AEMO with five minute forecasts through their MP5F API with the aim of reducing Causer Pays penalties.

• The viability of other short term forecasting applications will also be assessed, including the potential interaction with Kidston’s planned pumped hydro plant.


Why self forecasting can do better

Satellite

NWP

On site camera



for the NEM Project

Project Partner: Genex Power Project overview continued:

• CloudCAM detects clouds, predicts cloud movement and provides cloud forecasts from seconds up to more than 15 minutes in advance.

• Invented in 2012 with ARENA's involvement for remote, offgrid PV-battery-diesel hybrid systems. PV output is ramped down when clouding is predicted. This enables the diesels to pick up the load and avoid battery discharge / recharge.

• CloudCAM Hardware is robust and field tested.

• 17 cameras installed in Australia and Pacific IslandsThis project is supporting the next stage of CloudCAM software

development - the integration of multiple CloudCAMs and other datasets across a large solar farm to enable forecasting for the NEM.



for the NEM Project

Project Partner: Genex Power

Clearsky:no cloud

detectedNote camera flare, dirt

etc removed

Cloud:

robust cloud

detected and

identifiedSite specific horizon

mask removes impacts

of local vegetation etc


Further Background:

• AEMO’s MP5F API now allows semi-scheduled generators to provide AEMO with their own availability forecasts. Accurate self forecasts should lower Causer Pays charges.

• This project is the first use of multiple distributed CloudCAMs integrated for live data feed to network controller to allow forecasting over a large solar farm.

• Large datasets drawn from plant monitoring equipment e.g.:

• Back of panel temperatures

• Array status

• Inverter status

• Panel soiling etc.

Are integrated to develop an accurate plant power model. This model is essential for delivering accurate power forecasting.


for the NEM Project

Project Partner: Genex Power


Simultaneous photos from the nine

Kidston CloudCAMs


Animation of Kidston CloudCAM images


What we have learnt so far

• CloudCAM hardware continues to perform well

• The API is functional and AEMO is working through the kinks

• Current API challenges around having two forecast providers on site

• Power modelling is non-trivial but providing bonus insights

• SCADA integration takes time and careful planning

• Great project partners are essential:• Genex are excellent partners

• UGL (Kidston O&M contractors) are invaluable

CloudCAM Solar Forecasting for the NEM


Wind Forecasting for the NEM at Pacific

Hydro’s Clements Gap, Crowlands and

Taralga Wind Farms

Project Partner: Pacific Hydro Project overview:

• Again the focus is on providing AEMO with five minute forecasts through their MP5F API with the aim of reducing Causer Pays penalties.

• The viability of other short term forecasting applications will also be assessed.

• The philosophy of the forecasting approach focuses on developing detailed turbine-agnostic, site-specific, real-time models using the vast amount of data available from:

• sensors already installed and connected to wind farm SCADA systems

• new sensing equipment around wind farm perimeters (Sodars and/or masts).

Fulcrum3D Sodar at Clements Gap wind farm




Taralga Wind Farms

Project Partner: Pacific HydroProject overview continued:

• Installed one Fulcrum3D Sodar at Clements Gap (SA) wind farm and two at Taralga Wind Farm (NSW)

• A fourth Sodar will be installed at CrowlandsWind Farm (VIC)

• Areas of innovation include the approach to wind formatting and the use of Fulcrum3D Sodars to detect changes in wind conditions – several kilometers upstream of the wind farm – in all weather conditions.

Fulcrum3D Sodar at Taralga wind farm




Taralga Wind Farms

Project Partner: Pacific Hydro

Second Fulcrum3D Sodar at Taralga wind farm

Project overview

continued:

• Sodars will be

moved during the

project to find the

optimal

forecasting

location


What we have learnt so far

• Higher dimensional models of SCADA data alone perform better than AWEFS.

• Experience and early evidence give confidence that upstream sensing will surpass this.

• Dealing with extreme wind speed events is likely to remain non-trivial.

• Great project partners are essential – our thanks and acknowledgement to Pacific Hydro for their insight and support.

Fulcrum3D Wind Forecasting for the NEM


Thank you

fulcrum3d solar and wind forecasting for the nem€¦ · fulcrum3d cloudcam solar forecasting for...

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