v2.1.0
Release note
GENERAL
- Adaptation of farao to PowSyBl v3.5.0: https://github.com/powsybl/powsybl-core/releases/tag/v3.5.0
CRAC
- The package crac-results-extensions enables to extend the crac object model with complementary information regarding the RAO output.
- The package crac-loopflow-extensions enables to extend the crac object model with complementary information regarding the consideration of loopflows into the RAO
- A Crac constructor following the builder pattern has been added in order to facilitate the construction of the Crac object model
- The frm (Flow Reliability Margin) is a new attribute which have been added to the Cnecs, and which is now subtracted from the Cnecs thresholds during the RAO
- The package crac-io-cne enables to export the crac object model into a CNE .xml file
- It is now possible to specify a timestamp in the crac importer to filter the data
- Switches topology network actions can now be applied on the network
LOOPFLOWS
- A significant new feature of this release is the possibility to monitor, during the RAO, the loopflows on some critical network element, and to ensure that they remain below a threshold defined as the maximum of (i) a threshold defined as input in the crac-loopflow-extensions (ii) the initial loopflow value computed before the application of any remedial action
MNECS
- Another significant new feature of this release is the integration of mnec (Monitored Network Element and Contingency) in the RAO. The margin of the mnec is not optimized. However, the RAO ensures that the margin of those mnecs is (i) positive or (ii) above their initial value.
AMPERE OR MEGAWATT
- A setting of the RAO's configuration gives the possibility to optimize the margin of the Cnecs in Ampere, or in Megawatt. Note than one unit is not just an homothety of the other one, as the margin in ampere tend to give more weights to the lower voltage levels than the margin in megawatt.
AC, DC AND FALLBACK
- The settings of the RAO now enable to define a default and a fallback configuration of the sensitivity computation. It could be typically used to define a default AC configuration, and a DC fallback configuration to prevent the fact that some of the sensitivity computations could diverge.
OTHER RAO FEATURES
- The package rao-commons exposes some "utils" blocks of the RAO, one of them being a cross quality-check of the Crac and Network.
- The node evaluations of the search-tree can now be made in parallel, using several threads of the same machine.
- The logs of the RAO have been made more verbose. The logback framework has been added into the tests in order to facilitate the management of the FARAO's logs.
- The configuration of the RAO (RaoParameters) has significantly evolved since the previous release, with many new parameters and a new organisation of the parameters.
- The RAO can now interact with the systematic sensitivity analysis service provided by PowSyBl
IMPORTANT REMARKS
- As you can see with the content of this release, the code of farao-core is still evolving significantly from one release to the next. Several of those evolutions are impacting, in one way or another, the API of FARAO and consequently the applications that rely on it. We are indeed in a stage in which we are still allowing ourselves to bring many breaking changes to our API (crac-api, rao-api).
- These quick evolutions of the API gives us the flexibility in the current stages of the FARAO development to question some of our initial choices, and adapt some parts of the source in order to make them more robust, scalable, easy-to-read and fitted to the newly developed features.
- Eventually the API of FARAO will be stabilized, and breaking changes will be made with parsimony and be accompanied by more documentation. But this stabilization will come later as some new ground-breaking features are expected in the next release (including the curative remedial actions), and so impacting modification will still be made in the following releases.
- The website of FARAO has been updated since the previous release, with many new pages which describe the algorithms implemented into the RAOs: see https://farao-community.github.io/