The power system is poised to undergo radical transformations in the medium to long term, from both a technical perspective (new energy generation and storage technologies, and new interactions between energy vectors and system elements), a social perspective (new consumption habits and electrification of the thermal and transport sectors), a regulatory and economic perspective (new market forms), and a climatic perspective (increased occurrence of extreme weather events).
Economic resources for investments in substantial infrastructure projects are limited. However, it is desirable that the future power system maintains high standards of quality, adequacy, safety, and sustainability, while also aiming to maximize the socio-economic welfare of the community. This implies that the decision-making problem of optimal network planning is evidently complex, multi-objective, and multi-scenario.
In this research project, a new software tool has been developed to assist transmission network planners in identifying and evaluating optimal development interventions. Specifically, the focus is on finding a synergistic mix between optimal location of new transmission lines, optimal reinforcement of existing lines, and optimal location of new energy storage systems, considering the constraints on the construction of new projects. The tool is based on a Genetic Algorithm that iteratively proposes increasingly promising network development candidates, interpreting the economic-energy indicators derived from analyses of one or more software tools queried at a lower hierarchical level to assess the effects of new hypothetical expansion strategies.
This report presents the application phase of this tool to address the problem of optimal network development selection. Starting from the same test network, the results of two studies are analyzed in detail: one with a purely economic perspective, seeking the most cost-effective development plans in terms of cost-benefit analysis, and another with a broader perspective, seeking optimal expansion plans according to four indicators of economic, electrical, and environmental nature.