Mimetic: Market Simulation Tools – Manifold Cloud
Mathematical optimisation is not well understood and is therefore under-utilised. Access for all participants to the quantitative insights of optimisation are necessary to develop grid planning tools essential for the energy transition.
Cartesian carries out the task of maintaining the huge and complex datasets that are required but do not relate to the specific questions of users. This means increased quantitative agency without a learning curve.
Our software is faster by design. Build future worlds in less time than it takes to make a cup of tea.
Prescient: Demand Forecasting
Our machine learning approach and use of large historic datasets allow us to identify the interrelationship between weather, customer volume, and demand.
These models help energy retailers understand their current and future risk profile, simulate their customer acquisition strategy, and reduce hedging costs by more accurately predicting their demand profile.
Manifold Trace: Trace Modelling
We have developed generation profiles of wind and solar farms in Australia based on historic weather data spanning 40 years. These traces open for assessment the true range of outcomes in a post-transition grid, from individual power station to system-level analysis.
Gemini: Our replicate NEM dispatch engine
We have twinned the National Electricity Market (NEM) dispatch engine to produce Gemini. This replicate dispatch engine allows heavy experimentation with the intricacies of bid/constraint interaction dynamics in the NEM.
