Jafarian, MohammadMohammadJafarianNouri, AlirezaAlirezaNouriRigoni, ValentinValentinRigoniKeane, AndrewAndrewKeane2024-07-012024-07-012023-03IEEE Transactions on Power Systems0885-8950http://hdl.handle.net/10197/26379An indispensable step towards coordinating the actions of distribution and transmission system operators (DSOs-TSO) is to estimate the range of flexibility that can be offered to the TSO by DSOs. Within this context, a data-driven probabilistic approach is proposed to evaluate the capability of a distribution network in providing active and reactive power support in real-time. To this end, in an offline phase, a linear discriminant analysis model, together with a piecewise linear model of the distribution network are trained to delineate the boundary of a region representing the adherence to distribution network operational constraints. In the implementation phase, this region comprises the feasible set of a series of optimization problems, formulated to determine the support provision capability. These optimization problems are of iterative linear programming type, which allows for real-time applicability. The evaluated support capability can be deemed as the available reserve in real-time transmission operation, which enables providing a coordinated response towards unexpected events, and facilitates the participation of distributed resources in the balancing market by granting an up-to-date estimation of available supports. This approach is tested on the IEEE 123-node system and verified through comparison with an AC optimal power flow technique.enDistribution networksReal-time systemsEstimationTrainingOptimizationProbabilistic logicReactive powerJournal Article3821806181910.1109/tpwrs.2022.31749562022-05-16SFI/16/IA/4496SFI/15/SPP/E3125https://creativecommons.org/licenses/by/3.0/ie/