Engineering is evolving in the same way than society is doing. Nowadays, data is acquiring a prominence never imagined. In the past, in the domain of materials, processes and structures, testing machines allowed extract data that served in turn to calibrate state-of-the-art models. Some calibration procedures were even integrated within these testing machines. Thus, once the model had been calibrated, computer simulation takes place. However, data can offer much more than a simple state-of-the-art model calibration, and not only from its simple statistical analysis, but from the modeling and simulation viewpoints. This gives rise to the the family of so-called twins: the virtual, the digital and the hybrid twins. Moreover, as discussed in the present paper, not only data serve to enrich physically-based models. These could allow us to perform a tremendous leap forward, by replacing big-data-based habits by the incipient smart-data paradigm.

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Several solar-gas hybrid power plants based on the parabolic trough system are under construction in the MENA region and in Spain. The thermodynamic cycle of these plants is divided into topping cycle and bottoming cycle according to their temperature range. Since the solar collectors supply heat at a medium temperature level, up to 400°C, the existing technology uses a steam bottoming cycle (steam turbine). The present study aimed at investigating the thermodynamic feasibility of using air bottoming cycle (gas turbine) instead of the steam bottoming cycle. A thermodynamic scheme of solar air bottoming cycle was proposed. The case study considered an existing small size capacity gas turbine (<50 MW) as a topping cycle. The thermodynamic performance of the proposed solar air bottoming cycle was compared to two reference cases, without solar energy, a steam bottoming cycle and a conventional air bottoming cycle.