1 resultado para Technological forecasting
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
The acceleration of technological change and the process of globalization has intensified competition and the need for new products (goods and services), resulting in growing concern for organizations in the development of technological, economic and social advances. This work presents an overview of the development of wind energy-related technologies and design trends. To conduct this research, it is (i) a literature review on technological innovation, technological forecasting methods and fundamentals of wind power; (ii) the analysis of patents, with the current technology landscape studied by means of finding information in patent databases; and (iii) the preparation of the map of technological development and construction of wind turbines of the future trend information from the literature and news from the sector studied. Step (ii) allowed the study of 25 644 patents between the years 2003-2012, in which the US and China lead the ranking of depositors and the American company General Electric and the Japanese Mitsubishi stand as the largest holder of wind technology. Step (iii) analyzed and identified that most of the innovations presented in the technological evolution of wind power are incremental product innovations to market. The proposed future trends shows that the future wind turbines tend to have a horizontal synchronous shaft, which with the highest diameter of 194m and 164m rotor nacelle top, the top having 7,5MW generation. The materials used for the blades are new materials with characteristics of low density and high strength. The towers are trend with hybrid materials, uniting the steel to the concrete. This work tries to cover the existing gap in the gym on the use of technological forecasting techniques for the wind energy industry, through the recognition that utilize the patent analysis, analysis of scientific articles and stories of the area, provide knowledge about the industry and influencing the quality of investment decisions in R & D and hence improves the efficiency and effectiveness of wind power generation