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Wind Forecasting Demonstration Project

Sector: Education • Location: Australia

Source: Australian Renewable Energy Agency (ARENA)

Project
Closed

Meridian Energy Australia (MEA) and the University of Melbourne are developing innovative techniques to improve 5 minute ahead, Unconstrained Intermittent Generation Forecasts (UIGF) for the Australian Energy Market Operator (AEMO).This will be done at the 131 MW Mt Mercer Wind Farm in Victoria and the 70 MW Mt Millar Wind Farm in South Australia, which are both owned and operated by MEA. The proj

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The project “Wind Forecasting Demonstration Project” is an infrastructure initiative in the Education sector, located in Australia. Taiyo aggregates data on it from Australian Renewable Energy Agency (ARENA).

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Description

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Meridian Energy Australia (MEA) and the University of Melbourne are developing innovative techniques to improve 5 minute ahead, Unconstrained Intermittent Generation Forecasts (UIGF) for the Australian Energy Market Operator (AEMO).This will be done at the 131 MW Mt Mercer Wind Farm in Victoria and the 70 MW Mt Millar Wind Farm in South Australia, which are both owned and operated by MEA. The project will develop a real-time wind forecasting system, which will optimise information from a number of data sources and forecast models. Both proven and yet to be developed techniques will be used to provide forecasts to AEMO for both wind farms to help AEMO predict how much energy will be produced in order to better balance electricity supply with demand.How the project worksAs the transition to cleaner energy solutions continues, the number of variable renewable resources in the overall energy mix will increase. This creates challenges for AEMO to accurately balance supply and demand across the entire system in real time.This wind forecasting demonstration project will first develop a methodology that will allow MEA to provide an accurate, 5-minute ahead forecast of the output from the Mount Mercer Wind Farm and Mount Millar Wind Farm. It will do this by combining data-driven and physics-based modelling, relevant weather phenomena such as wind, rain and thunderstorms and the onset of calm night-time conditions that affect the amount of wind that will be generated. The benefits to the National Electricity Market (NEM) of these improved forecasts will also be investigated.

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