Future high renewable electricity scenarios — Insights from mapping the diversity of near least cost portfolios

This paper reports on future electricity generation scenarios modelled using NEMO, a model that applies a genetic algorithm to optimise a mix of simulated generators to meet hourly demand profiles, to the required reliability standard, at lowest overall industry cost. The modelling examined the least and near least cost technology portfolios for a scenario that limited emissions to approximately one quarter of those from the Australian National Electricity Market (NEM) at present. It was found that all the near least cost solutions (within 15% of the least cost solution) involved wind capacity in the range of 31-51 GW, with 98.8% of these near least cost portfolios having at least 35 GW of wind installed. In contrast, the near least cost solutions consistently involved much lower quantities of PV, with 90% of the near least cost portfolios having less than 4.9 GW of installed PV capacity. This suggests that policies to promote high levels of wind deployment and grid integration are likely to be important for achieving low cost, low emissions outcomes, while policies to promote significant PV deployment may be less warranted in the absence of cost effective supporting technologies, such as battery storage or significant demand side participation.