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Optimisation, benchmark testing and comparison of droop control variants in microgrids
Author(s) -
Eberlein Simon,
Rudion Krzysztof
Publication year - 2021
Publication title -
iet smart grid
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.612
H-Index - 11
ISSN - 2515-2947
DOI - 10.1049/stg2.12036
Subject(s) - voltage droop , microgrid , benchmark (surveying) , controller (irrigation) , control theory (sociology) , stability (learning theory) , computer science , inverter , power (physics) , control engineering , engineering , control (management) , voltage source , voltage , agronomy , physics , geodesy , quantum mechanics , artificial intelligence , machine learning , geography , electrical engineering , biology
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.

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