The problem with evaluating the investment in a multi-site photovoltaic plant, such as that proposed in this paper (which can be viewed as a profitability analysis), is that it requires the development of an innovative methodological approach. By setting an upper limit of capital to invest, among sites with different Direct Normal Irradiations (DNI), those in which many photovoltaic systems can be installed are identified as is the optimal size within predefined ranges. The primary objective is to maximize the net return on investment for a multi-site plant with a lifespan of approximately twenty years. The proposed approach uses a stochastic business plan, through which data are generated via the Monte Carlo simulation. Subsequently, using the Response Surface Methodology procedure, it is possible to identify the regression meta-model that describes the optimum region and therefore the point (investment amount for individual sites and the corresponding size of plants) that maximizes the overall Net Present Value. The proposed approach is completely generalized and, as such, can be replicated. A properly conducted test case is presented and clearly illustrates the methodology.

A stochastic methodology to evaluate the optimal multi-site investment solution for photovoltaic plants

Bendato, Ilaria;Cassettari, Lucia;Mosca, Roberto;Mosca, Marco
2017

Abstract

The problem with evaluating the investment in a multi-site photovoltaic plant, such as that proposed in this paper (which can be viewed as a profitability analysis), is that it requires the development of an innovative methodological approach. By setting an upper limit of capital to invest, among sites with different Direct Normal Irradiations (DNI), those in which many photovoltaic systems can be installed are identified as is the optimal size within predefined ranges. The primary objective is to maximize the net return on investment for a multi-site plant with a lifespan of approximately twenty years. The proposed approach uses a stochastic business plan, through which data are generated via the Monte Carlo simulation. Subsequently, using the Response Surface Methodology procedure, it is possible to identify the regression meta-model that describes the optimum region and therefore the point (investment amount for individual sites and the corresponding size of plants) that maximizes the overall Net Present Value. The proposed approach is completely generalized and, as such, can be replicated. A properly conducted test case is presented and clearly illustrates the methodology.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/890932
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