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In this paper, we introduce an application of a high-performance MultiPeriodAC Optimal Power Flow (MPOPF) solver, called "BATTPOWER", to simulate activedistribution grids for a near-future scenario. A large-scale Norwegiandistribution grid along with a large population of Electric Vehicles (EV) arehere taken as the case-study. We suggest and analyse three operationalstrategies (in terms of control of charge scheduling fleet of EV) for theDistribution System Operator (DSO): (a) uncoordinated/dumb charge scheduling,(b) coordinated charge scheduling with the objective of energycost-minimisation without operational constraints of the grid, and (c)coordinated charge scheduling with the objective of energy cost-minimisationalong with the operational constraints of the grid. The results demonstratethat the uncoordinated charging would lead to: 1) overloading of lines andtransformers when the share of EVs is above 20%, and 2) higher operationalcosts than the proposed control strategies of (b) and (c). In strategy (b)operational line/transformer limits are violated when the populations of EVsare growing above 36%. This implies that current market design must be alteredto allow active control of a large proportion of DERs within grid operationallimits to achieve cost minimization at system level. To our knowledge, the workpresented in this paper is the first ever attempt to do a comprehensiveanalysis of the impact of EV charging demand on a real Norwegian distributiongrid. Moreover, the inference of the analysis says that the Norwegiandistribution networks are more prone to congestion problems than the voltageproblems for the EV demand which includes a smart charging scheme accountingfor grid conditions.

BATTPOWER Application: Large-Scale Integration of EVs in an Active Distribution Grid -- A Norwegian Case Study