RP1034 Carbon Value Engineering

Electricity networks are entering a period of disruption due to rapidly advancing new distributed energy technologies. This project aims to address the question of whether existing market arrangements can facilitate efficient investment and operation of distributed energy resources (DERs), and how different arrangements may help facilitate more efficient outcomes. As the advent of DERs may precipitate a transfer of ownership of electricity assets to from governments and corporates to individuals and smaller organisations, these questions are fundamental to the future social and economic wellbeing of our society.

This project uses an iterative methodology that will be repeated multiple times to conduct investigations into the retail, wholesale and forwards/futures markets of the Australian National Electricity Market (NEM). This process involves identifying key market features using new developments in AI and machine learning to process large data streams from market operators. The next step is to build a model that simulates these markets. This model will be extended to include high-penetration DERs to measure the impact of distributed energy on existing competition indicators. These results are intended to determine recommendations for improvements in DER integration in the NEM. A key feature of this research will be the application of algorithmic game theory to model oligopolistic competition in electricity markets, and determine the impact of adding near-zero marginal cost electricity (ie. distributed renewables) to existing and experimental market models.