دانلود مقاله ISI انگلیسی شماره 54141
عنوان فارسی مقاله

عوامل زیست محیطی خاموشی های مسکونی برنامه ریزی شده در توزیع توان الکتریکی شهر فینیکس آریزونا

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
54141 2012 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Environmental determinants of unscheduled residential outages in the electrical power distribution of Phoenix, Arizona
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Reliability Engineering & System Safety, Volume 99, March 2012, Pages 161–171

کلمات کلیدی
توزیع، برق؛ وقفه؛ خاموشی برق؛ قابلیت اطمینان
پیش نمایش مقاله
پیش نمایش مقاله عوامل زیست محیطی خاموشی های مسکونی برنامه ریزی شده در توزیع توان الکتریکی شهر فینیکس آریزونا

چکیده انگلیسی

The sustainability of power infrastructures depends on their reliability. One test of the reliability of an infrastructure is its ability to function reliably in extreme environmental conditions. Effective planning for reliable electrical systems requires knowledge of unscheduled outage sources, including environmental and social factors. Despite many studies on the vulnerability of infrastructure systems, the effect of interacting environmental and infrastructural conditions on the reliability of urban residential power distribution remains an understudied problem. We model electric interruptions using outage data between the years of 2002 and 2005 across Phoenix, Arizona. Consistent with perceptions of increased exposure, overhead power lines positively correlate with unscheduled outages indicating underground cables are more resistant to failure. In the presence of overhead lines, the interaction between birds and vegetation as well as proximity to nearest desert areas and lakes are positive driving factors explaining much of the variation in unscheduled outages. Closeness to the nearest arterial road and the interaction between housing square footage and temperature are also significantly positive. A spatial error model was found to provide the best fit to the data. Resultant findings are useful for understanding and improving electrical infrastructure reliability.

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