Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1731033 | Energy | 2016 | 16 Pages |
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.
Keywords
FCCIRRLCCLECROIKPIMCMCSPPBPDPRDiscounted payback periodWACCMSPEENEAnet present valueInvestment evaluationRenewable energyReturn on equityReturn on investmentdirect normal irradianceProbability density functionanalysis of varianceANOVACash flowsPayback periodRoeDNIMonte Carlo SimulationMonte Carlo methodResponse surface methodologyRSMGrid-connected photovoltaic systemStand-alone photovoltaic systemKey performance indicatorsNPV یا negative predictive valueInternal rate of returnInterest rateLevelized cost of energyLife cycle costPCRPdf
Related Topics
Physical Sciences and Engineering
Energy
Energy (General)
Authors
Ilaria Bendato, Lucia Cassettari, Marco Mosca, Roberto Mosca,