The DIA-SOLAIRE project aims to develop integrated diagnostic and prognostic approaches for existing and future photovoltaic (PV) power plants. These approaches will be hybrid, integrating both physical models and models based on experimental data, while exploring the potential of statistical and machine learning methods. The aim is to extend the lifetime of PV power plants and to optimize the management of their energy performance, while taking into account technological, human and environmental factors of influence, over the medium and long term, in a context of climate change. Energy production drifts and their causes can be identified, and performance and profitability projections can be proposed by introducing degradation distributions and economic models. Finally, changes in maintenance practices brought about by the implementation of artificial intelligence tools will be analyzed with PV plant operators. The tools developed will incorporate a man-machine interface enabling users and operators to support them in making decisions in real time, based on adapted performance criteria.