دانلود مقاله ISI انگلیسی شماره 14558
ترجمه فارسی عنوان مقاله

ارزش بازار برای انرژی حرارتی همزمان:استفاده از برآورد قیمت سایه بکار گرفته شده در سیستم تولید همزمان در کشور کره

عنوان انگلیسی
Market value for thermal energy of cogeneration:: using shadow price estimation applied to cogeneration systems in Korea
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
14558 2005 7 صفحه PDF
منبع

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

Journal : Energy Policy, Volume 33, Issue 14, September 2005, Pages 1789–1795

ترجمه کلمات کلیدی
- تولید همزمان - قیمت سایه - دوگانگی -
کلمات کلیدی انگلیسی
Cogeneration,Shadow prices,Duality,
پیش نمایش مقاله
پیش نمایش مقاله  ارزش بازار برای انرژی حرارتی همزمان:استفاده از برآورد قیمت سایه بکار گرفته شده در سیستم تولید همزمان در کشور کره

چکیده انگلیسی

This study empirically analyzes the appropriateness of the current tariffs for district heating in Korea. For this purpose, we adopt the duality concept applied to the output distance function, and estimate the shadow price of heat produced from cogeneration. In addition, the analytical model takes account for the inputs of labor and capital as well as fuel as input outlays of cogeneration. The empirical results show that the current heat tariff determined by the public energy policy might be undervalued by about 15–53%. This implies that the retail price of district heating in Korea might be distorted at least in the sense of economics.

مقدمه انگلیسی

Cogeneration is the sequential generation of two different forms of useful energy from a single primary energy source. The two different forms of energy may be electrical energy and thermal energy or mechanical energy and thermal energy. The sequences of generation can be any combination of different forms of useful energy. Cogeneration is widely known to be an energy efficient technology (Kwon and Yun, 2003).1 While providing the same quantity of two different required forms of energy, it has the advantage of reducing the primary energy cost.

نتیجه گیری انگلیسی

Table 1 shows the estimation results of parameters based on Eq. (16) with various l’s; l ¼ 0:1; 0.5, and 0.9. For each level of l; we randomly pick up 1000 sets of 39 observations from the whole sample with replacement. That is, for each value of l; the model in Eq. (16) has been estimated 1000 times with different sets of observations. The estimated parameters in Table 1 are the sample means of those parameters. Our results show that most of the parameters estimated for different l’s are consistent with one another.