The report outlines the developments in the optimization methodology for resilience measures, aimed at application to realistic networks, the implementation of the new version of the RELIEF tool, and new active measures for the resilience of distribution networks.

First, it revisits the fundamentals of cost-benefit analysis and the original formulation of the optimization methodology for the portfolio of active and passive measures to enhance the resilience of the power system. The developments include:

The proposal of an efficient solution algorithm, based on parallel computing, that combines Generalized Pattern Search (GPS) and Enhanced Unidirectional Search techniques.

A more advanced characterization of the analyzed threat (with a focus on wet snowfalls).

The introduction of an efficient technique for selecting multiple contingencies, based on identifying relevant clusters of lines prone to failure.

The report then describes the software implementation developments for the evolution of the RELIEF tool, particularly the creation of a PostGres database for the systematic management of electrical and physical network data, the functionality for importing data in CIM format, code versioning, access services to external databases, encapsulation of functional modules, and the development of a new Graphical User Interface (GUI) that allows visualization of network and threat data, as well as analysis results in a Geographical Information System (GIS) environment.

Additionally, active measures are proposed, based on thyristor voltage regulators, ballast loads, and/or storage systems, to ensure a minimum anti-icing current on the branches of a distribution network.
Finally, the report presents the results of applying RELIEF to two case studies: the optimization of active and passive measures on a realistic transmission network model and the simulation of active measures on a distribution network. The results of the first case study demonstrate the scalability and applicability of the optimization module even on realistically sized networks, achieving an optimal portfolio of measures for improving resilience, considering both the costs of the measures and the evolution of climate scenarios. The distribution case study shows the potential and limitations of the applicability of active measures.