Prototype large-scale renewable energy system optimisation for Victoria, Australia

This paper presents results from a prototype renewable energy network optimisation model, which is driven with output from a high resolution mesoscale weather model of the current climate. The network model estimates potential power output for various combinations of wind and solar farms across a large domain of several hundred kilometres and calculates the required back-up power capacity needed to meet demand. The model finds the network configuration that minimises the cost of the system, and shows that considerably less installed capacity of both renewables and back-up is required if the choice of locations for wind and solar farms takes into account the covariance in the wind and solar fields.

► We model the integration of numerical weather data into a renewable energy network. ► We optimise 6 scenarios to meet electrical demand. ► Lower costs occur when the covariance of wind and solar is taken into account. ► Optimising with observational weather data was shown to be a costly alternative.