Technical, economic and uncertainty modelling of a wind farm project
Abstract Wind is one of the fastest-growing renewable sources of electricity. As with most renewables, the economic viability relies on public subsidies. Even among renewables, the economic evaluation of wind projects is particularly challenging due to the unpredictability of the energy source, wind, and the high sensitivity of the project profitability to changes in a number of parameters. This makes the uncertainty analysis an important topic of research in the wind power sector. This study presents a method of combining two uncertainty analysis methods, sensitivity study and the Monte Carlo method, together with a technical and economic model of a wind farm, in an effort to improve the understanding of the practical effects of the uncertainties, and how they affect the financial risks of wind projects.
Due to the tasks of the national energy saving policy and other reasons, the sales quantity of 2011 for traditional car shows a downward trend, after the rapid growth phase of 2009–2010. Comparatively, the new energy vehicles are more suitable for national energy reduction policies. The new energy vehicle industry should be the trend of the future development for the automobile industry. Therefore, a reasonable plan for state-owned new energy vehicle industry is quite important. This article developed an adaptive balanced scorecard knowledge-based system for industry strategic planning. This knowledge-based system also uses the partial least squares regression analysis to determine the specific strategy weights. So this adaptive BSC knowledge-based system can help providing recommendations for the industry development plan.