تجزیه و تحلیل هزینه و پیش بینی برای یک کارخانه اتانول سوختی در یک کشور آفریقایی روستایی و محصور در خشکی: رویکرد عامل زبان
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|23374||2009||10 صفحه PDF||سفارش دهید||6335 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 119, Issue 1, May 2009, Pages 207–216
Research on improving ethanol production as an alternative to petroleum based fuel has been accelerating for both ecological and economical reasons. A simplified procedure for rapid ball-park cost estimate that can be used as a research tool by energy policy makers for targeting area of cost reduction in a project, for comparing alternative design and for reviewing achieved costs on completed projects is described. In this study, an operating, commercial scale fuel-ethanol plant annexed to a sugar industry and based on molasses in a poorly accessible rural and landlocked African country was used to determine the cost structure. Analysis of the breakdown of the fixed capital investment (FCI) cost, based on the principle of factorial method of capital cost estimation and using Lang factor (fL) analysis was used to create an econometric model for calculating FCI cost. The model suggests a Lang factor of 2.40 and 2.81 for outside and inside battery limits plant, respectively.
The use of ethanol as an alternative motor fuel has been steadily increasing around the world for several reasons. These reasons can be attributed mainly to an international convergence of ecological, political, economic and social factors (Von Sivers and Zacchi, 1995; Berndes et al., 2001; Zhang et al., 2003; Farrell et al., 2006; Amigun et al., 2008; Cardona and Sanchez, 2007; Sorbara, 2007). Domestic production and use of ethanol for fuel can decrease dependence on foreign oil, reduce trade deficit, reduce air pollution and carbon dioxide emissions and create jobs in rural communities relatively cost effectively compared to other agro-industrial alternatives (Goldemberg, 2007; Cardona and Sanchez, 2007). Specifically, the expanded use of fuel-ethanol would have significant health benefits in replacing lead as an octane enhancer in most African countries where leaded fuel is still widely used (Johnson and Matsika, 2006). Africa represents the largest leaded fuel user in the world. Of a total of 44 countries in Sub-Saharan Africa, 17 countries use leaded fuel only, 13 dual systems and 14 unleaded (UNEP, 2005). Ethanol programmes that produce a blend of ethanol and gasoline (gasohol) for use in existing fleets of motor vehicles have been pursued in a number of African countries (most of these plants are concentrated at the southern tip of the continent), including Malawi, Zimbabwe, Kenya and South Africa. Others countries with molasses distillation plants include Mauritius, Swaziland, Zambia, Mozambique, Tanzania, Angola, Uganda, Egypt and Ethiopia. Many of these countries are landlocked, which means that it is not feasible to sell molasses as a byproduct on world market, while oil imports are also very expensive. Rapid cost estimating systems are necessary to enable product designers and product development teams to make sound decisions early in the conceptual design phase and not, as is often the case, provide fodder for later value-analysis teams. Techniques for capital cost estimation have been developed over the years (Guthrie, 1969; Wilson, 1971; Ulrich, 1984; Kharbanda and Stallworthy, 1988; Turton et al., 1989; Peters and Timmerhaus, 1991; Sinnott, 1996; Brennan, 1998; Garret, 1998; Brennan and Golonka, 2002; Jebson, 2002). Estimating the cost of a process plant can vary from a rapid ball-park estimate to a carefully prepared, detailed calculation, depending on how much information is available, level of accuracy required, how much time and effort is available to do the estimate (Montaner et al., 1995). The total fixed capital cost of a process plant may be estimated as the sum of the fully installed costs for each item of equipment, based on estimate of purchased equipment cost and the additional cost of any associated plant by using appropriate factors (factor methods) (Brennan and Golonka, 2002; Marouli and Maroulis, 2005). These factors, known as ‘Lang factors—fLfL’, are characteristic of the industry sector considered, particularly the type of products manufactured, the average cost of equipment items used, plant capacity and location (Lang, 1948). Most of the existing Lang factors are from American and European sources, and are fairly old. In most African countries typically characterised by low labour rates for semi and unskilled personnel and very few locally established engineering equipment suppliers and or specialist support services, the purchased equipment is mostly imported, leading to increased cost due to additional freight, legal, administrative, custom and import duties and insurance fees. The use of Lang factors, which are based on high labour cost, on project with no additional cost of equipment importation, may well result in a preliminary capital cost which is unrealistic, and the project may probably not proceed. The greater the uncertainties of capital cost, the more cautious investors are likely to be. Hence, the more accurate these factors are, the greater the likelihood of the more marginal projects proceeding to the benefit of all concerned. The study of economic parameters involved in the functioning of an ethanol plant has rarely been carried out from an engineering point of view, and there are no publications in this regard for ethanol plants in Africa. This paper aims to present an analysis of the breakdown of the fixed capital investment (FCI) cost of one African distillery, operating in a landlocked country, in a poorly accessible rural area in an equation format. This simplified procedure will enable easier and more rapid use of the data in numerical and economic models, and in the preliminary design and optimisation of fuel ethanol plants in Africa.
نتیجه گیری انگلیسی
Capital cost analyses of the rural African distillery annexed to an existing sugar mill have been carried out. Lang factor fL of 2.40 was obtained on the basis of the purchased cost of equipment for OBL plant. Using installed equipment cost as basis, the resulting factor is 2.0. For IBL plant, fL=2.81 was observed with installed equipment cost of 2.22. The value of 2.40 and 2.81 are significantly lower than general green-fields sites values of 3.6 and 4.5 commonly used in the literature—but not that different to values of 3.0 and 2.75 reported for mill-annexed maize ethanol plants in the USA. Whilst no comparative results appear to have been published for the sugarcane based ethanol industry, the evidence in the case of OBL plant supports the notion that Lang factors for African installations (in particular in landlocked and/or rural locations) will be slightly lower than those of corresponding installations elsewhere. This is explained by the relatively higher costs of procuring equipment coupled to the relatively lower costs of installation and site work. Another important conclusion from the analysis of the distillery's capital cost appears to be that the factored approach to capital cost estimation remains a useful method in its own right, and also provides means of checking the validity of estimates made by more detailed methods. The ability to present an analysis of the breakdown of the capital investments of a rural African distillery, in an equation format enables easier and more rapid use of the data in numerical and economic models, and in the preliminary design and optimisation of biofuel process plants. A very significant cost but hidden cost of commercial scale ethanol plants is the cost of site development such as building and upgrading roads, water supply systems, and pollution control systems and electricity generating capacity. This is expected to be very significant in the case of stand-alone plant while an annexed plant will lead to better economics.