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Grid-forming inverter control is recently discussed for bulk power systems and is already in use for islanded microgrids. A common control type is the droop control. Numerous variants of the basic droop control have been proposed. However, there is lack of performance comparison of the droop variants in literature. Their superiority has only been demonstrated for some specific microgrid scenarios. This work composes benchmark scenarios to assess and compare the applicability of droop control variants and also their combination with virtual impedances under practical conditions. A number of microgrid topologies and the interaction with synchronous machines are considered to benchmark the performance. Static criteria, such as the steady-state power sharing, as well as dynamic stability criteria, are taken into account for modal analysis. To guarantee a meaningful comparison, a genetic algorithm tailored to the problem is used to optimise controller parameters for each controller type. Results indicate that the combination with virtual impedance has a more decisive effect on stability than the droop variant. The outcome is relevant for microgrid stability analysis in numerous contexts, such as optimal placement of inverters or topology optimisation, where the choice of the most suitable controller type with optimised parameter sets is key.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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This paper is addressing the issues regarding reduction of the necessary network expansion by taking flexibility options into account. If a certain amount of the annual energy from renewable generation is curtailed, the expansion of the power grid can be reduced. This paper presents a comparison of the necessary expansion of a high voltage distribution grid (110kV) under consideration of different curtailment approaches for renewable energy sources. Here, the necessary expansion is calculated, if a static or a dynamic curtailment is applied and then compared with the calculations without any curtailment mechanism. The curtailment methods are tested using a probabilistic expansion planning method based on the calculation of probabilistic load flow.

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