Two-Stage Stochastic Optimal Energy Management of Microgrids for Participation in Flexibility Markets

The increasing importance of flexibility markets has arisen in empowering distributed energy resources to assist grid operators in balancing the electricity system. This necessitates new optimization algorithms capable of optimally computing flexibility for day-ahead flexibility markets and implementing flexibility requests in intraday operations. This paper proposes a two-stage (day-ahead and intraday) flexibility optimization formulation for a Microgrid (MG). Chance constraints with separation constraints approximation, tuned by a risk aversion parameter, handle uncertainties. An experiment involving a diverse set of energy assets is performed, simulating a relevant energy flexibility request, which is successfully satisfied, demonstrating the capabilities of the proposed solution.