Intelligent Energy Trading,
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Machine learning models have been widely used for price forecasting in various contexts. Yet, in electricity markets, they often fail to deliver meaningful insights that lead to significant performance improvements beyond analytical models. As the share of renewables grows, alongside the inherent volatility driven by fluctuating demand, weather, and other external factors, effective forecasting of […]

Garbage in, garbage out! Inaccurate assumptions in modelling can significantly skew the outcomes of power system and market studies. Yet, obtaining precise input data for battery storage systems is often challenging. Take the Hornsdale Power Reserve in South Australia, for example. While many studies might use its 194 MWh nameplate capacity as the input, it […]

While many forecasting tools have been developed to improve forecasts of renewable generation, their accuracy is limited by the inherent predictability of the data used – that is, how predictable the renewable resource is in different regions and times of the year. Here we explain explains why predictability matters and how considering it can save consumers and investors millions of dollars. […]