Electric power systems are currently undergoing a transition towards decentralization, with small-scale distributed units playing an increasingly pivotal role in energy generation. As the phasing-out of fossil fuels continues, the significance of distributed energy resources is growing, not only as sources of primary energy but also as providers of crucial ancillary services.

To facilitate this transition, it is imperative to open the national ancillary services market to a broader spectrum of units and develop holistic strategies to optimally exploit these resources.

This work extends the analyses already carried out by the authors within the framework of the Research Fund for the Italian Electrical System by proposing an iterative Mixed Integer Linear Programming model combined with a constrained k-means clustering method to define the ancillary services market bidding strategy for an aggregate of residential users. Numerical simulations are conducted to prove the effectiveness of the proposed models, using as a reference the current Italian regulatory framework.

The techno-economic analyses are performed both from local and systemic perspectives.

The local perspective evaluates the economic advantages of the proposed strategies both for users and aggregators, while the systemic one enables the assessment of the benefits of the ancillary service provision by distributed energy resources in a predominantly decarbonized electric power system. In this regard, a 2030 energy scenario compliant with the European Green Deal is simulated and the values of the flexibility margin of distributed energy resources are accurately evaluated.