The power system is poised to undergo radical transformations in the medium to long term from various perspectives: technical (new energy generation and storage technologies), social (new consumption habits and the electrification of the heating and transport sectors), regulatory and economic (new market forms, new interactions between energy vectors and system elements), and climatic (increased occurrence of extreme weather events).

The electrical infrastructure system, specifically the transmission networks, will necessarily need to evolve to adapt to changes—some of which are only partially foreseeable—in boundary conditions, and to anticipate needs and issues that currently, or in the past, did not or did not yet raise concerns.

Economic resources for investments in large infrastructure projects are limited; however, it is desirable that the future power system maintains high standards of adequacy, safety, stability, flexibility, and sustainability, all while aiming to maximize the social welfare of the community. Consequently, the decision-making problem of optimal network planning is evidently complex and multi-objective, involving choices that must be made years in advance of their impact on systems evolving with uncertain trajectories.

This research project aims to develop a new software tool to support transmission network planners in identifying and evaluating optimal development operations. Specifically, the focus will be on finding an optimal mix of the best locations for new transmission lines, optimal reinforcement of existing lines, and the best locations for new energy storage systems. The tool will be characterized by:

• Mathematical modeling;
• Generality, meaning applicability to any network;
• Modularity, meaning it will be flexible and extendable.

It will be based on a Genetic Algorithm that will iteratively propose increasingly promising network development candidates, interpreting economic/energy indicators derived from the analysis of one or more software tools queried at a lower hierarchical level to assess the effects of new hypothetical expansion strategies.

The document explains in detail the context, motivations, algorithmic structure, and implementation specifics of this innovative tool.