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In this paper, the Authors present the results of their research conducted to stochastically define a method to assess investments in electric production plants using renewable energy with particular reference to photovoltaic plants. The method is broken down into six sequential steps where particularly suitable instruments are used for stochastic applications such as: the Monte Carlo method, the Design of Experiments and the Response Surface Methodology. It is therefore possible to obtain regression meta-models as output that allow us to highlight the cause and effect relationship between some input variables and the main assessment parameters of an investment. The method's declared objective is to allow possible investors to use a reliable assessment instrument and to provide clearly interpretable quantitative answers.

In this paper, the authors, consistent with the philosophy of Sustainable Manufacturing, propose a generalised methodology for replacing/supplementing traditional energy sources with renewable energy sources. The methodology, developed stochastically, makes extensive use of Discrete Event Simulation and the Monte Carlo method to optimize, for each hour of operation, the ratio of production from Renewable Energy Sources to supply from traditional sources. The final output is summarised as a Cumulative Distribution Function of the hourly lack of power produced by Renewable Energy Sources compared to system demands. In this way, the manager can, sufficiently in advance, select the most appropriate procurement strategy.