Optimal energy and flexibility self‐scheduling of a technical virtual power plant under uncertainty: A two‐stage adaptive robust approach

This paper presents a two-stage adaptive robust optimization framework for day-ahead energy and intra-day flexibility self-scheduling of technical virtual power plant (TVPP). The TVPP exploits diverse distributed resources’ (DERs) capabilities in order to offer services wholesale market as well preserving the distribution network's operational constraints presence DER uncertainties. aims at maximizing its profit markets considering worst-case uncertainty realization. In proposed framework, first stage models TVPP's participation strategy determines DERs’ optimal dispatch. second addresses determine capability provision by adjusting their dispatch realization characteristics associated with photovoltaic units, electric vehicles, heating, ventilation air conditioning systems, other responsive loads transmission requests are considered using an approach. Adopting duality theory, model is formulated mixed-integer linear programming problem solved column-and-constraint generation algorithm. implemented on standard test system effectiveness demonstrated.