Stochastic techno-economic assessment based on Monte Carlo simulation and the Response Surface Methodology: The case of an innovative linear Fresnel CSP (concentrated solar power) system. (15th April 2016)

• Record Type: Journal Article
• Authors: Bendato, Ilaria; Cassettari, Lucia; Mosca, Marco; Mosca, Roberto
• Is Part Of: Energy. Volume 101(2016)
• Page Start: 309
• Page End: 324
• Publication Date: 2016-04-15
• Subjects: Monte Carlo simulation -- Response surface methodology -- Renewable energy -- Stochastic business plan -- Investment evaluation -- Linear Fresnel concentrated solar power; CSP Fresnel concentrated solar power -- KPI key performance indicators -- RSM response surface methodology -- IRR internal rate of return -- NPV net present value -- PBP payback period -- DPBP discounted payback period -- LEC levelized cost of energy -- LCC life cycle cost -- MCM Monte Carlo method -- GCPVS grid-connected photovoltaic system -- SAPVS stand-alone photovoltaic system -- DNI direct normal irradiance -- DPR discounted profitability ratio -- ROI return on investment -- ROE return on equity -- PCR project cover ratio -- MSPE mean square pure error -- MSPE MED MSPE of the mean -- MSPE STDEV MSPE of the standard deviation -- ENEA Italian National Agency for New Technologies, Energy and Sustainable Economic Development -- pdf probability density function -- FCC face-centred composite -- ANOVA analysis of variance -- OFCF cash flows -- WACC interest rate; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.02.048
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Combining technological solutions with investment profitability is a critical aspect in designing both traditional and innovative renewable power plants. Often, the introduction of new advanced-design solutions, although technically interesting, does not generate adequate revenue to justify their utilization. In this study, an innovative methodology is developed that aims to satisfy both targets. On the one hand, considering all of the feasible plant configurations, it allows the analysis of the investment in a stochastic regime using the Monte Carlo method. On the other hand, the impact of every technical solution on the economic performance indicators can be measured by using regression meta-models built according to the theory of Response Surface Methodology. This approach enables the design of a plant configuration that generates the best economic return over the entire life cycle of the plant. This paper illustrates an application of the proposed methodology to the evaluation of design solutions using an innovative linear Fresnel Concentrated Solar Power system. Highlights: A stochastic methodology for solar plants investment evaluation. Study of the impact of new technologies on the investment results. Application to an innovative linear Fresnel CSP system. A particular application of Monte Carlo simulation and response surface methodology.