A cluster-based optimization approach to support the participation of an aggregator of a larger number of prosumers in the day-ahead energy market

Optimizing the participation of a large number of prosumers in the electricity markets is a challenging problem, especially for portfolios with thousands or millions of flexible resources. To address this problem, this paper proposes a cluster-based optimization approach to support an aggregator in the definition of demand and supply bids for the day-ahead energy market. This approach consists of two steps. In the first step, the aggregated flexibility of the entire portfolio is computed by a centroid-based clustering algorithm. In the second step, the supply and demand bids are defined by an optimization model that can assume the form of a deterministic or a two-stage stochastic problem. A case study of 10,000 prosumers from the Iberian market is used to evaluate and compare the performance of the bidding optimization models with and without pre-clustering. The numerical results show that the optimized bidding strategies outperform an inflexible strategy by more than 20% of cost savings. The centroid-based clustering algorithm reduces effectively the execution times of the bidding optimization problems, without affecting the quality of the energy bids.