A researcher from Central Queensland University believes he has developed a renewable energy forecasting system that could be used in conjunction with a “smart” electricity grid. This would ensure that renewable technologies such as solar and wind would become more reliable and dependable energy sources in the future.
Rahat Hossain, a PhD student at CQUniversity’s Power Engineering Research Group within the Institute for Resource Industries and Sustainability (IRIS), believes his work will mean Australia can reduce its reliance on coal-powered electricity.
“Solar and wind energy systems have for some time been considered promising power generators, however a common drawback has been the unpredictable nature and dependence on weather changes,” Rahat explained.
“However, by integrating and forecasting the two power sources in a hybrid forecasting system, many of the problems can be overcome.”
By collating historical data on weather patterns over the last decade from the CSIRO, Hossain has been able to “train” the neural network in his forecasting model to perform predict conditions within the short term (hourly) to medium term (daily) within the same platform.
“This feature is one of the major innovations and indicating the great robustness of the proposed hybrid renewable energy forecasting system,” he said.
Hossain believes that if Australia wants to meet it 2020 target of 20 percent reduction in carbon dioxide levels, the Federal Government should fund a trial solar/wind hybrid power station in Central Queensland utilising his forecasting technology.
“If Australia is to meet these targets we have to begin using alternative systems and this hybrid system has real benefits for Australia’s climate and landscape. Australia has large amounts of land that could be used for wind turbines and also is best located to source solar radiation.”
The field of renewable energy forecasting is a growing one and earlier this year Sandia National Laboratories researchers in the USA announced a solar forecasting system to monitor how clouds affect large-scale solar photovoltaic (PV) farms.
Image credit: CQUniversity Australia
