PROA ANALYTICS (APR – 2507)

Operational Forecasting of Cloud Cover to Tackle the Intermittency From Solar and Battery Hybrid Power Plants

Engineering, IT, Mathematics and Statistics

PLEASE NOTE

• Proa Analytics’ office is bases in Hallam, Victoria. Ideally this internship will be a hybrid arrangement with some onsite attendance.
• This internship may be eligible for funding through the Australian Government Women in STEM and Entrepreneurship (WiSE) grant. Female STEM HDR students are encouraged to apply.

ABOUT THE INDUSTRY PARTNER

Proa is a fast-paced, innovation-driven start-up. They are an industry leading provider of solar forecasting, energy analytics, management, and weather monitoring solutions for the renewables industry. Proa’s talented team is comprised of mechanical, software and mechatronics engineers, physicists, and IT specialists.

WHAT’S IN IT FOR YOU?

• Work with a dynamic team developing cutting edge technology at the forefront of the energy transition.
• Experience the journey of commercializing research from blue sky ideas to a commercial solution running in critical energy infrastructure.
• Challenge your analytical and coding skills to work a complex problem involving large datasets of various sources in an operational environment.
• Learn how to organise, structure and communicate complex research outcomes.

RESEARCH TO BE CONDUCTED

Over the last four years, the Proa team has pioneered the development of a world-class Energy Management System (EMS), capable of transforming a solar farm with a small battery into a scheduled generator. This groundbreaking technology, currently operational at multiple sites, combines “classic” P50 solar forecasts with P100 or high-confidence solar forecasts through an advanced optimization-based control technique. Proa has developed highly innovative methods and algorithms using data from ground-based weather stations, sky cameras, weather radars, weather models and geostationary satellites to produce P100 forecasts. These high-confidence forecasts are a core component of the control solution to guarantee the supply of stable electricity by the solar farms.

This project will dive into the methods, algorithms and data used to produce the P100 forecasts to peer review, validate, document and improve the research outcomes gathered over the last four years. The validation and assessment of P100 forecasts is non-trivial because of inter-temporal relationships associated to the manner the BESS in the hybrid system is dispatched. The project will also explore how to improve and consolidate a robust validation and benchmarking framework.

SKILLS WISH LIST

If you’re a postgraduate research student and meet some or all the below we want to hear from you. We strongly encourage women, indigenous and disadvantaged candidates to apply:

• Currently pursuing a PhD degree in Engineering, Science or Mathematics.
• Excellent problem-solving and analytical skills.
• Programming in MATLAB
• Mathematical modelling of physical systems.
• Experience working with large datasets.
• Familiarity with image processing and/or machine learning techniques
• Excellent verbal and written English communication.
• Demonstrated experience producing high-quality technical and scientific documentation.
• Eagerness to learn and contribute to a collaborative work environment.

RESEARCH OUTCOMES

• Review of the current documentation and methodologies related to the P100 forecasts developed by Proa’s team over the last four years.
• Explore the validation datasets and create a benchmarking framework and simulation tool to expand the validation of current and future methodologies.
• Improve one or more of the methodologies currently being used in Proa’s production environment.
• Produce a comprehensive report outlining methods, results and potential improvements.

ADDITIONAL DETAILS

The intern will receive $3,000 per month of the internship, usually in the form of scholarship payments.

It is expected that the intern will primarily undertake this research project during regular business hours and maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.

The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.

Please note, applications are reviewed regularly and this internship may be filled prior to the advertised closing date if a suitable applicant is identified. Early submissions are encouraged.

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