A mixed-integer distributed approach to prosumers aggregation for providing balancing services. (December 2021)

• Record Type: Journal Article
• Authors: La Bella, Alessio; Falsone, Alessandro; Ioli, Daniele; Prandini, Maria; Scattolini, Riccardo
• Is Part Of: International journal of electrical power & energy systems. Volume 133(2021)
• Publication Date: 2021-12
• Subjects: Balancing services -- Prosumers aggregation -- Distributed MILP optimization; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.107228
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A scalable optimization scheme is designed for prosumers providing ancillary services. Prosumers are modelled using MILPs, enabling to consider different operating modes. The distributed algorithm to promptly manage large-scale aggregations. The numerical results show the effectiveness of the approach for varying aggregations' sizes. Abstract: This paper addresses the provision of ancillary services in smart energy systems. A large number of prosumers are aggregated by an Energy Service Provider (ESP) in order to provide a manual Frequency Restoration Reserve (mFRR) service, which consists in offering some degree of flexibility and be willing to provide a power variation over a given time interval upon reception of an explicit manual request by the Transmission System Operator (TSO). The main focus of this paper is to define how the ESP can optimally distribute the requested flexibility effort to the prosumers in the pool, promptly providing the agreed mFRR service upon request of the TSO. In particular, a scalable strategy is proposed, able to account for integer decision variables like on/off commands, while reducing the combinatorial complexity of the problem and preserving privacy of local information via distributed computations. Lead and rebound effects are avoided by maintaining the originally scheduled energy exchange profile before and after the time interval where the TSO request must be satisfied. The simulation results show the effectiveness of the proposed approach in terms of scalability and quality of the obtained feasible solution.