Large-scale aggregation of prosumers toward strategic bidding in joint energy and regulation markets

Abstract Increased penetration of distributed energy resources is unleashing the flexibility of large-scale prosumers in deregulated markets. To explore prosumers’ potential market revenues, some existing studies have focused on the strategic bidding of prosumers aggregation. A majority of those studies assume the price-taker role of the aggregator while a few studies assume the price-maker role of the aggregator. However, it remains an open question as to how the increasing number of prosumers influences the profit of a strategic aggregator. Therefore, we conduct a numerical analysis in this paper to quantify the profits of aggregating large-scale prosumers. A stochastic bi-level optimization model is proposed to depict the strategic behavior of prosumers aggregation bidding in joint energy and regulation markets. This bi-level model is transformed into a mixed-integer linear programming model by employing the Karush-Kuhn-Tucker conditions based on strong duality theory. Case studies based on 120,000 prosumers from Australia demonstrate that the strategic bidding behavior of an aggregator can lead to a 7.5% decrease in operation costs, and increasing the number of prosumers will lead to a larger gap between non-strategic and strategic behavior.