个人信息Personal Information
副教授
硕士生导师
性别:男
毕业院校:南开大学
学位:博士
所在单位:化工海洋与生命学院
学科:化学工程. 工业催化
电子邮箱:xiaopengzhang@dlut.edu.cn
Comparative study of three boil-off gas treatment schemes: From an economic perspective
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论文类型:期刊论文
发表时间:2019-12-01
发表刊物:ENERGY CONVERSION AND MANAGEMENT
收录刊物:EI、SCIE
卷号:201
ISSN号:0196-8904
关键字:BOG recondensation; LNG cold energy power generation; BOG combustion power generation; Net present value
摘要:Since the tanks and pipes of the liquified natural gas terminal cannot realize absolute insulation, the generation of the boil-off gas is inevitable. The existence of boil-off gas will threaten the production safety of the system, so it is necessary to properly treat it. However, the boil-off gas treatment system has the problems of high energy consumption and waste of liquified natural gas cold energy. There is no comprehensive comparison between different boil-off gas treatment schemes. To solve these problems, this paper firstly compares three different boil-off gas treatment schemes, including the two-stage boil-off gas recondensation system with pre-cooling (case 1), the integrated boil-off gas recondensation and liquified natural gas cold energy power generation system (case 2) and the combined boil-off gas fueled gas turbine and liquified natural gas cold energy power generation system (case 3). Then, the influence of electricity price, interest rate and boil-off gas content on the net present value of systems are explored. The results show that case 3 has the largest net power output, followed by case 2 and case 1. For example, when the boil-off gas content is 0.15, the net output power of case 3 is 34.05 MW, the net output power of case 2 is 0.15 MW, while the net output power of case 1 is - 0.53 MW. Electricity price, interest rate and boil-off gas content have an important impact on the net present value of systems. The net present value of systems increases with increasing boil-off gas content, and decreases as interest rate increases. Under the same boil-off gas content and interest rate conditions, case 3 is more suitable when the electricity price is higher, while case 2 is more appropriate at the lower electricity price.