An Australian Agency for Renewable Energy has a funded project that uses machine forecasting technology that predicts solar and wind power. This technology aims to secure and integrate these innovations into the country’s electricity grid.

The funded project started in October 2018 with the efforts of Palisade and Worley Energy and Monash University’s Innovation Hub. Moreover, the said collaboration aims to provide solar and wind energy generators with reliable and more accurate five-minute self-forecasting abilities.

In addition, the forecasting methodology’s development was initiated and led by one of Monash University’s doctors, Christoph Bergmeier. He also collaborated with the Department of Business Statistics and Econometrics led by the Innovation Hub of Monash Energy Institute.

However, Dr. Bergmeir stated that expecting short-term renewable power generation will not be an easy job. This is because green energy can’t be immediately generated on demand since it’s still meant to be extracted from natural resources like the sun and wind.

So, to obtain ample power generation and a stable network, he says that we have to establish an efficient short-term forecasting methodology.

Moreover, by enhancing the predictability and accuracy of 5-minute-ahead forecasts required by our country’s electricity market’s standards, the forecasting generation solutions designed by the Monash and Worley team will enable more reliability and security.

In fact, this can be possible when more precise and systematic forecasts reduce the probability of unsatisfactory dispatch, thereby supporting an increased level of available renewable resources in today’s market without compromising the grid stability.

In this case, the project’s key advantages include enhanced renewable power grid penetration due to increased renewable generation dispatchability and FCAS’s payment reduction.

Moreover, Denis Marshment, the Vice President of Data Customer Solutions, stated that their forecasting method could provide direct value to their current renewable consumers since they already targeted lower charges for FCAS.

In addition, with the official launching of PowerPredict, Australia’s renewable generators can already benefit from their energy forecasting technology. This is notable because, in 2020, inaccurate power forecasting cost Australia’s generators two hundred ten million dollars. Because of this, utilizing innovative machine algorithms for 5-minute-ahead predictions is considered valuable.

Additionally, their enhanced forecasting algorithms have already obtained a forty-five percent improvement in their consumers’ energy output predictions.

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