Configuration

Dedicated parameters

Name	Type	Default value	Description
enable-losses-compensation	boolean	false	When set to true, adds losses compensation step of the algorithm. Otherwise, all losses will be compensated using chosen power flow compensation strategy.
losses-compensation-epsilon	double	1e-5	Threshold used in losses compensation step of the algorihm. If actual losses are below the given threshold on a branch, no injection is created in the network to compensate these losses. Used to avoid creating too many injections in the network. May have an impact in overall algorithm performance and memory usage.
sensitivity-epsilon	double	1e-5	Threshold used when filling PTDF and PSDF matrices. If a sensitivity is below the given threshold, it is set to zero. Used to keep sparse matrices in the algorithm. May have an impact in overall algorithm performance and memory usage.
rescale-mode	enum	NONE	Use NONE if you don’t want to rescale flow decomposition results. Use ACER_METHODOLOGY for the ACER methodology rescaling strategy. Use PROPORTIONAL for a proportional rescaling. See Flow parts rescaling for more details.
proportional-rescaler-min-flow-tolerance	double	1e-6	Option only used if rescale-mode is PROPORTIONAL. Defines the minimum DC flow required in MW for the rescaling to happen.
dc-fallback-enabled-after-ac-divergence	boolean	true	Defines the fallback behavior after an AC divergence Use True to run DC loadflow if an AC loadflow diverges (default). Use False to throw an exception if an AC loadflow diverges.
sensitivity-variable-batch-size	int	15000	When set to a lower value, this parameter will reduce memory usage, but it might increase computation time

Impact of existing parameters

Any implementation of load flow provider and sensitivity analysis provider can be used, as the entire algorithm only relies on common loadflow API and sensitivity analysis API.

Thus, flow decomposition algorithm relies on load flow parameters and sensitivity analysis parameters.