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The share of end-users with installed rooftop photovoltaic (PV) systems iscontinuously growing. Since most end-users are located at the low voltage (LV)level and due to technical limitations of LV networks, it is necessary tocalculate PV hosting capacity. Most approaches in calculating a network'shosting capacity are based on three-phase optimal power flow (OPF)formulations. Linearized and relaxed three-phase OPF formulations respectivelylose their accuracy and exactness when applied to solve the hosting capacityproblem, and only non-linear programming (NLP) models guarantee the exactsolution. Compared to linearized or relaxed models, NLP models require a highercomputational time for finding an optimal solution. The binary variables upliftthe problem to mixed-integer (MI)NLP and increase the computational burden. Toresolve the scalability issues in calculating the hosting capacity ofsingle-phase connected PVs, we propose a method that does not entail binaryvariables but still ensures that PVs are not connected to more than one phaseat a time. Due to a risk of a sub-optimal solution, the proposed approach iscompared to the results obtained by the MINLP formulation. The comparisonincludes values of the solution time and technical quantities such as networklosses, voltage deviations, and voltage unbalance factor.

Solving scalability issues in calculating PV hosting capacity in low voltage distribution networks