CAPITULO II Del derecho de accesión
DE ALGUNAS PROPIEDADES ESPECIALES CAPITULO I
In this study, a hybrid LCA model has been developed to analyze the environmental impacts of two onshore and two offshore wind turbines. The analysis result of applying this method showed that although the resource consumption of offshore wind turbines is higher than onshore wind turbines (except for concrete which is mainly used in the foundation of onshore wind turbines), offshore wind turbines have less environmental impacts than onshore wind turbines per kWh electricity generation in their life cycle period. On average, the GHG emissions for onshore and offshore wind turbines are 17.37 and 7.44 g CO2 eqv/Kwh, consequently. In addition, V90 wind turbines are more environmentally friendly than V80 wind turbines per kWh of generated electricity, while they emit 14% less GHG emissions in onshore and 30% less in offshore wind turbines. This is because V90-3.0MW generates more electricity during its lifetime than V80-2.0MW.
In this research, the impacts of net electricity production and life cycle period on the net environmental footprint of wind turbines have been also analyzed. The results indicate that by increasing the lifetime of each wind turbine, the environmental footprint of electric power generation for each onshore and offshore plant will significantly be reduced. Therefore, the longer lifetime the wind turbine has, the less environmental impact the wind turbine generates per kWh electricity production. In addition, our results also show that the more capacity the wind turbine has, the less environmental impact the wind turbine generates in its lifetime.
Moreover, data collection phase in each LCA analysis consumes considerable amount of time and budget. The precision of life cycle inventory plays a vital role in accuracy of final results. Therefore, in order to reduce the errors resulting from mistakes in input material
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quantification, a Monte Carlo simulation method is used to account for the variability in input material. This method then was coupled with compromise programming to find the best energy mix for the building in the state of Florida. The results showed that different mixes are suitable for different economic and environmental weights. Nonrenewable energies, or specifically in this research wind energies, are more suitable while the environmental weights are higher than weight of cost. On the other hand, when the weight of cost dominates the importance of environment, natural gas gets the highest chance of selection in the energy mix.
In U.S., offshore wind power plants are still not used as much as on shore wind power plants. Until 2009, all wind power plants in U.S. had been located on land (Wiser et al., 2010). However, the findings of this research show that offshore wind turbines generate less environmental impacts in their entire life cycle period when compared to onshore wind turbines. Therefore, it is important to note that offshore wind power technologies can be a viable solution to minimize the net environmental impact associated with electricity generation in U.S.
In this research, only four different types of wind turbines were analyzed. The optimum energy mix would be more accurate if different wind turbines in different regions were studied with the same LCA methodology. Moreover, for the nonrenewable energy sources the average value of costs and GHG emissions from publically available data were used. The availability of specified data for the state of Florida is one of the shortcomings of this research. Also, the constructability of the offshore wind turbines is less than onshore wind turbines. This can be another criterion for the decision makers to look at in the future studies.
Last but not least, using wind turbines for electricity generation has a wide range of economic, social, and ecological benefits, such as employment, reduced dependency on foreign
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energy sources, or minimized land use for power generation. For future studies, we recommend to extend the existing LCA methodology, and develop a triple bottom line (TBL) sustainability assessment model in which economic, social, and ecological impacts of wind energy systems can be analyzed by using the same EIO analysis framework. To accomplish this, several TBL sustainability assessment metrics should be merged with input-output analysis that will provide a more comprehensive sustainability analysis of wind technologies.
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V80 Onshore V90 Onshore V80 Offshore V90 Offshore Steel & Stainless Steel 1,708,838 2,359,539 1,498,516 1,656,421
Cast Iron 38,349 42,771 40,304 42,771 Glass Fiber 744,502 798,998 758,899 798,998 Epoxy 381,710 404,556 384,566 404,556 Copper 266,838 297,459 279,961 297,459 Oil 6,007 6,696 6,302 6,696 Aluminum 12,462 13,892 13,075 13,892 Polyester 18,569 20,754 19,661 20,754 3,177,275 3,944,664 3,001,284 3,241,546 Crushed Stone 63,014 65,187 20,882 22,215
Aggregate and Sand 132,526 137,095 45,212 48,098
Geotextile(HDPE) 10,634 11,001 - - Concrete 2,009,673 2,800,254 1,145,076 1,618,878 Iron 8,249 11,377 4,456 6,321 Steel 13,267 40,425 23,872 48,907 Aluminum 12,590 19,535 20,404 32,559 Copper 5,156 8,001 90,334 144,149 Polibutadiene 1,479 2,295 2,397 3,826 PVC 12,970 13,417 - - Lead - - 61,352 97,902 PEX - - 2,772 4,424 2,269,557 3,108,589 1,416,757 2,027,280 diesel 54,166 60,184 144,442 144,442 Oil 6,007 6,696 6,302 6,696 glass fibers 174,887 184,477 175,530 184,477 epoxy resin 116,591 122,985 117,020 122,985 Stainless Steel 30,371 33,856 31,865 33,856 Cast Iron 4,678 5,215 4,908 5,215 Copper 40,026 44,619 41,994 44,619 Oil 901 1,004 945 1,004 Aluminum 1,869 2,084 1,961 2,084 429,496 461,121 524,967 545,379 Steel 103,999 149,409 114,110 128,763 Stainless Steel 26,694 29,768 33,652 35,722 Cast Iron 40,949 46,702 48,742 52,591 Glass Fiber 19,948 21,338 24,329 25,606 Epoxy 10,812 11,446 13,059 13,735 Copper 4,073 4,559 6,081 6,909 Oil 906 1,009 1,140 1,211 Aluminum 358 452 546 698 Polyester 1,492 1,668 1,896 2,001 Crushed Stone 164,843 164,843 67,412 67,412
Aggregate and Sand 391,129 391,129 164,667 164,667
Geotextile(HDPE) 181 181 - - Concrete 151,799 204,465 106,735 141,846 Polibutadiene 82 123 164 246 PVC 294 294 - - Lead - - 1,180 1,770 PEX - - 1,180 284 917,557 1,027,386 584,894 643,461 Costs($) - 2012 costs Operation and Maintanance Services Total Transportation Total Manufacturing of the Wind Turbine
and related Components Total Construction and Erection Total Phase Material
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