Ararat Wind Farm

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Forecasts for wind generators operating in the National Electricity Market (NEM) have historically been provided by the Australian Wind Energy Forecasting System (AWEFS).The Australian Energy Market Operator (AEMO) is currently undertaking the Market Participant 5-minute Forecast (MP5F) program that will allow renewable energy generators to provide their own 5-minute ahead forecasts. To improve the quality of 5-minute forecasting capabilities in Australia, ARENA is providing funding to a number of projects.DNV GL have been delivering renewable energy forecasting services since 2003, and currently forecast for more than 50 GW of projects in 20 countries around the globe. The majority of these forecasts, and all of those currently delivered in Australia, are for half-hourly averaging periods. In some other markets DNV GL already delivers 5-minute averaged forecasts, with good levels of accuracy. The challenge is to implement this service in the Australian market and to improve upon the quality of these forecasts.The Ararat Wind Farm project, overseen by DNV GL, aims to deliver five-minute forecasting at the Ararat Wind Farm, and to assess the potential of machine learning approaches to further improve accuracy.Key resultsForecast accuracy is not necessarily a predictor of FCAS Causer Pay charges. DNV GL observed that Causer Pays factors and charges can be greater for self-forecasts than those expected from the use of AWEFS, even when the accuracy of the self-forecasts is better than AWEFS.Financial performance of forecasts is dynamic. It is possible to calculate hypothetical CP charges for historical forecast scenarios, to evaluate the relative financials performance of different forecasts.DNV GL created two models – the Refined Model and the CP Optimised Model. Financial evaluations of the various forecast models were undertaken with the Refined Model delivering worse financial outcomes than the AWEFS for certain periods. The CP Optimised Model was found to deliver improved financial outcomes however this was based on generation of historical forecasts.Variations in the nature of the electricity market can mean that a forecast model that is performing well at a given time may rapidly cease to offer financial benefits.

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