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Stochastic life cycle assessment and cost analysis in renewable energy systems

Milousi Maria

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Summary

Life Cycle Assessment (LCA) is a systematic, analytical process for assessing the environmental implications of systems or products, from raw material extraction (or “cradle”) through manufacture, use, and end of life (the “grave”). Though it is clear that LCA results are subject to many sources of uncertainty, it is also important to know to what extent the outcome of such an analysis is affected by various types of uncertainty (such as parameter, scenario and model uncertainty) and may occur in the goal and scope definition, the inventory analysis and the impact assessment of an LCA. Proper evaluation of the inherent uncertainties provides useful information for the reliability of LCA-based decisions and a necessary guide for future minimization of inaccuracies. The selection of a proper technique is largely based on the type and extent of details required by the specific case-study (i.e. sensitivity analysis, Monte Carlo simulation, Markov chain, Multiple linear regression, Fuzzy set theory and fuzzy logic, etc.).There have been several attempts to spot and highlight various statistical-stochastic uncertainties in LCA, as they are increasingly affecting the relevant methodologies, databases and software. The thesis contains a detailed LCA and techno-economic study of selected Renewable Energy Systems: geothermal power plants, photovoltaics (thin-film and crystalline) and solar thermal collectors (flat plate and vacuum tube). The advanced software SimaPro accompanied with the updated ecoinvent database have been used for the implementation of the LCA case studies, while all technical and economic calculations have been performed through RETSCreen.

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