The feasibility of national and supra-national low‑carbon power systems (LCPSs) is becoming no longer in question. Nevertheless, such systems still present serious challenges to become a reality. Perhaps, the major issue arises because they should be sustainable, reliable and economical, but these features are difficult to conciliate as the penetration of renewables increases. Indeed, renewable energy generation is weather dependent, which translates into the power system by introducing unavoidable intermittencies in the electricity generation. In addition, the design and optimization of LCPSs involves accounting for additional cost, demand, power transmission and reliability constraints, as well as regulatory and political issues.

The models used in the design and simulation of LCPSs require appropriate databases of renewable energy resources, spanning multiple decades and, ideally, accounting for climate change scenarios. The size of the models’ input databases and the complexity of the optimization procedures to find the best distribution of power plants makes this problem intractable for most of the real cases. Nevertheless, it can be solved by taking some idealized hypothesis that are still realistic at some extend. However, a high share of renewable involves to also tackle the problem of the relatively low predictability of the wind and solar resources. At this regard, the probabilistic forecasts might play a key role in the operation of such power systems.

This project aims at contributing to the planning and development of an optimized LCPS in Spain by providing enhanced and specialized weather databases of renewable resources, analysis tools and design guidelines to policy makers for an optimal distribution of the power plants. To this end, the project has four general objectives. First, to develop specialized historical, forecast and climate change databases of wind and solar renewable resources for Spain. Second, to propose roadmaps for the optimal distribution of wind and solar power plants under various design constraints that can be used as guidelines for the upgrade of the current Spanish power system to a LCPS. And, last but not least, to analyze potential weaknesses and vulnerabilities of a power system with high shares of wind and solar energies from the point of view of: 1) the spatial and temporal patterns of weather variability and extreme weather events (third objective), and 2) the limitations in the predictability of the wind and solar resources and the potential benefits of the use of probabilistic forecasts for which new methods will be proposed and evaluated (fourth objective).

The work requires combining the experience and knowledge in various areas such as meteorology, artificial intelligence and evolutionary/meta-heuristic optimization. For this reason, the project has been planned and organized as a coordinated project which involves personnel from two areas of knowledge: Earth Sciences and Computer Science. Atrás