12 avril 2019

Context and objectives

In a context of sustainable development, clean energy is strongly promoted in the European energy mix. Among the various solar energy technologies, Concentrating Solar Power (CSP) will play a key role in the future: its share of global electricity is envisioned to reach 11% in 2050 [1]. The main drawback of CSP technologies is their costs, that drop slower than those of photovoltaics. This PhD is part of the SFERA-III project (see https: //, funded by the European Union’s Horizon 2020 research and innovation programme. Two main topics will be addressed during this PhD: (a) the short-term (up to 30 min) forecast of direct normal irradiance (DNI), which can be defined as the direct irradiance received on a plane normal to the Sun, using a sky imager, and (b) the model-based predictive control (MPC) of a solar fuel reactor using the aforementioned forecasts.

Users of solar concentrating research infrastructures (RIs) are hosted for a short period of time to carry out their experiments. That is why an efficient use of the solar resource during this period is critical for obtaining valuable and exploitable experimental results. One way to increase the useful on-sun experimental time available to RI users during their stay is to provide them accurate intrahour forecasts of DNI, both before the experiments and, through a continuous update, while they are being made.

Because solar energy is inherently variable and intermittent, dynamic control and automation tools are needed to ensure continuous processes. In this sense, the SFERA-III project adresses, among other things, the developement of a MPC-based controller dedicated to solar fuel production under varying solar conditions. Such a tool has to offer highly-valuable know-how and software assets for the further development of solar fuel production technologies, for both near- and long-term concerns.