Robust methods are needed for decision support in distribution systems.
The tools must be able to handle flexible sources as generation, loads, storages as well as different topologies from the perspective of loss minimization and self-healing concepts.
Tools should be open-source and sufficient general to be used as building blocks in more specialized concepts
Work performed
A distribution system load flow is developed in Python.
It has the classical Forward-Backward-Sweep as a core but is flexible in terms of system topologies (radial operation) and provides a number of sensitivities for impact of changing active and reactive loads at individual buses.
Calculates an optimal voltage profile where both active and reactive power may be decision variables
Significant results
A toolbox developed which can be used by researchers in CINELDI and students as a building block for more tailor-made concepts.
Open-source available on Github.
Currently used by researchers for studying flexibility
Impact for distribution system innovation
The tool gives the option to quickly prototype and test special concepts.
A kernel for more advanced coordination and optimization concepts.
