Abstract
The electric grid had become a vast complex cyber-physical system, and its digitalization is a reality in the close future that would result in a tremendous amount of information, controls, and uncertainties. Distributed energy resources (DERs), such as distributed generation (DG), demand response (DR), distributed energy storage systems (DESS), and electric vehicle (EV) are increasing the level of uncertainty but also the capabilities of new controls on the distribution networks. The future electric grid will need more flexibility and coordination between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) to be able to operate in a reliable, secure and economical fashion. To overcome uncertainties and reliability issues, DSO is moving toward the so-called active distribution network (ADN) which is the crucial piece of for enabling new flexibility at the TSO level. In this paper, we propose a methodology for the estimation of the ADNs flexibility based on the feasibility region at the TSO-DSO interface. A Monte Carlo sampling method is applied to generate random ADN states. The proposed methodology is analyzed in both the 5-bus ring distribution test system and the 33-bus IEEE radial distribution system.
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