Deregulated power systems with high renewable penetration often involve complex decision-making by self-interested private investors. In this work, we study the setting of privately developed and shared network capacity, where the power grid infrastructure, renewable generation and storage units are built by profit-driven investors. Specifically, we consider a case where demand and generation sites are not co-located, and a private investor installs generation capacity and a power line between the two locations providing also access to rival competitors (local generators and storage investors) against a fee. We show such a setting leads to a bilevel Stackelberg-Cournot game between the line investor (leader) and local investors (followers) and develop a data-driven solution to derive the profit-maximising capacities installed by players at equilibrium, based on analysis of a large-scale empirical dataset from a grid upgrade project in the UK. Our method provides a realistic tool to analyse decision-making of private investors in such games and subsequently encourage further adoption of renewable generation.
|Title of host publication||Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020)|
|Publication status||Accepted/In press - 15 Jan 2020|
|Event||19th International Conference on Autonomous Agents and Multi-agent Systems 2020 - Auckland, New Zealand|
Duration: 9 May 2020 → 13 May 2020
|Conference||19th International Conference on Autonomous Agents and Multi-agent Systems 2020|
|Abbreviated title||AAMAS 2020|
|Period||9/05/20 → 13/05/20|