LTAG(LCO to Aromatics and Gasoline)是石科院近期开发的将劣质催化柴油(LCO)转化为高辛烷值催化汽油或轻质芳烃的技术。它是先将催化柴油中的多环芳烃选择性加氢饱和,后经催化裂化开键断裂生成目的产品。为了达到消耗催柴库存与降低...LTAG(LCO to Aromatics and Gasoline)是石科院近期开发的将劣质催化柴油(LCO)转化为高辛烷值催化汽油或轻质芳烃的技术。它是先将催化柴油中的多环芳烃选择性加氢饱和,后经催化裂化开键断裂生成目的产品。为了达到消耗催柴库存与降低柴汽比的目的,我厂在催柴加氢装置与1套催化裂化装置中推行LTAG工艺。展开更多
After the great east Japan earthquake in 2011, Japanese energy system has been expected to prioritize safety and trustworthiness. Now, distributed power systems are considered as one solution, but utilizing exhaust he...After the great east Japan earthquake in 2011, Japanese energy system has been expected to prioritize safety and trustworthiness. Now, distributed power systems are considered as one solution, but utilizing exhaust heat is an important task to be solved. The purpose of this study is to build a simulation model to harness waste heat of commercial buildings. We obtained two types of data： distributed power system in 1/15 scale model of supermarket, restaurant and real world energy consumption of the two buildings. Results showed cold cabinets, whose electricity was affected by temperatures outside and inside, consumed most in supermarket. While air conditioning, affected by air enthalpy of outside and inside, consumed most in restaurant. According to our simulation with gas engine, PV （photovoltaic） panel, PCM （phase change material）, thermal storage, FCU （fan coil unit） and refrigerated cabinets in scale model, we could reduce 27% of CO_2 emission and 25% of running cost by selecting optimal size.展开更多
文摘LTAG(LCO to Aromatics and Gasoline)是石科院近期开发的将劣质催化柴油(LCO)转化为高辛烷值催化汽油或轻质芳烃的技术。它是先将催化柴油中的多环芳烃选择性加氢饱和,后经催化裂化开键断裂生成目的产品。为了达到消耗催柴库存与降低柴汽比的目的,我厂在催柴加氢装置与1套催化裂化装置中推行LTAG工艺。
文摘After the great east Japan earthquake in 2011, Japanese energy system has been expected to prioritize safety and trustworthiness. Now, distributed power systems are considered as one solution, but utilizing exhaust heat is an important task to be solved. The purpose of this study is to build a simulation model to harness waste heat of commercial buildings. We obtained two types of data： distributed power system in 1/15 scale model of supermarket, restaurant and real world energy consumption of the two buildings. Results showed cold cabinets, whose electricity was affected by temperatures outside and inside, consumed most in supermarket. While air conditioning, affected by air enthalpy of outside and inside, consumed most in restaurant. According to our simulation with gas engine, PV （photovoltaic） panel, PCM （phase change material）, thermal storage, FCU （fan coil unit） and refrigerated cabinets in scale model, we could reduce 27% of CO_2 emission and 25% of running cost by selecting optimal size.
