کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6768339 | 512471 | 2014 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Methodology of risk analysis by Monte Carlo Method applied to power generation with renewable energy
ترجمه فارسی عنوان
روش تجزیه و تحلیل ریسک با استفاده از روش مونت کارلو برای تولید برق با استفاده از انرژی های تجدید پذیر
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
This paper presents a methodology that uses the Monte Carlo Method (MCM) to estimate the behavior of economic parameters which may help decision, considering the risk in project sustainability. In order to show how this methodology can be used, a Grid-Connected Photovoltaic System (GCPVS) of 1.575 kWp, located on the roof top of the laboratory building of the Grupo de Estudos e Desenvolvimento de Alternativas Energéticas - GEDAE, at the Universidade Federal do Pará - UFPA, Belém - Pará - Brazil, and operating since December 2007, is analyzed. This system was chosen because it was the first GCPVS installed in the Brazilian Amazon Region, being the first risk evaluation on using a renewable energy source connected to the grid in the Region. This work also presents a similar treatment for the case of a stand-alone photovoltaic system (SAPVS) installed in the remote Santo Antônio Village, municipality of Breves, Pará, Brazil, considering the risk of investment assumed by an investor in power generation projects with similar characteristics or using other renewable energy sources. The last case allows a better assessment for other important applications of renewable energy in the Amazon Region, where the demand for energy is growing, but is still costly and often not a priority in government actions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable Energy - Volume 69, September 2014, Pages 347-355
Journal: Renewable Energy - Volume 69, September 2014, Pages 347-355
نویسندگان
Edinaldo José da Silva Pereira, João Tavares Pinho, Marcos André Barros Galhardo, Wilson Negrão Macêdo,