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            <title xml:lang="en">Investigation of LCA simplification approach: the wind power electricity case</title>
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                <forename type="first">Pierryves</forename>
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                <forename type="first">Isabelle</forename>
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                <forename>Magalie</forename>
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            <idno type="halRefHtml">&lt;i&gt;21st Setac Europe Annual Meeting&lt;/i&gt;, May 2011, Milan, Italy. p. 183-184</idno>
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                <title xml:lang="en">Investigation of LCA simplification approach: the wind power electricity case</title>
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                <title level="m">21st Setac Europe Annual Meeting Abstracts book</title>
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                  <title>21st Setac Europe Annual Meeting</title>
                  <date type="start">2011-05-15</date>
                  <date type="end">2011-05-19</date>
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                <term xml:lang="en">Simplified LCA</term>
                <term xml:lang="en">Wind power electricity</term>
                <term xml:lang="en">GHG performances</term>
                <term xml:lang="en">Variability assessment</term>
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              <p>Scientific publications related to the electricity generation systems from Life Cycle Assessment (LCA) show great variability in their results and conclusions. Thus it leads policy makers to consider LCA somehow as an inconclusive method. Moreover, LCA is usually considered in the industry sector as time and energy consuming. This study concerns the onshore wind power electricity greenhouse gases (GHG) performances. It aims at developing a correlation facilitating access to these performances as a function of key parameters. A thorough LCA literature survey and analysis of the ecoinvent 2.1 wind turbine (WT) LCAs have highlighted the importance of a limited numbers of parameters. These, have been classified into 3 categories: technical (related to the intrinsic WTs characteristics such as weights or power curve), geographical (related to the wind conditions on the implantation site) and methodological (the lifetime defined arbitrarily). A 17 WTs sample has been selected (from 800kW to 4.5MW) which is assumed to be representative of wind turbines installed since 2003, and forecasted for the near future. The WT are characterized by their component weights, tower heights and their power curves. The WTs inventories have been built considering the main assumptions highlighted by the literature survey and the ecoinvent inventory assessment. For instance, we kept the same lifetime for both the moving and fixed part . We did not consider the end of life because this is too systems specific (regarding the possible scenarios).Then the electricity production for the WTs has been calculated according to their power curve and the mean wind speed. The correlation relating GHG impacts per kWh produced by each turbine to the key parameters has then been defined across the whole sample. A confidence interval (based on the relative standard deviation) has been found out to vary according to wind speed. For a 20 years WT lifetime, the GHG performances vary from 6.8 g CO2 eq/kWh ― 10.6% (vwind= 9 m/s) to 38.3 g CO2 eq/kWh ± 14.8% (vwind=4m/s). For average wind condition in Europe (6 m/s) the correlation results (13g CO2eq/kWh ±12.2%) are in accordance with the literature average results (13.5 g CO2 eq/kWh). Moreover, varying the life time of WTs from 10 to 30 years have induced a high variability of GHG performances from 8.7 to 26.1 gCO2eq/kWh ± 12.2% (for vwind= 6 m/s), GHG performances of WTs are therefore found to be very sensitive to this methodological parameter.</p>
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