Reducing Carbon Emission of Greenhouses Using Hybrid Renewable Energy Systems (A case study in Iran)

سال انتشار: 1398
محل انتشار: کنفرانس بین المللی مطالعات بین رشته ای در مدیریت و مهندسی
کد COI اختصاصی: ICOCS03_166
زبان مقاله: انگلیسی
تعداد مشاهده: 755

نویسندگان

Master of Science student, Renewable Energy and Environmental Engineering Department, Faculty of New Sciences and Technology, University of Tehran, Iran

Arash Kargarzadeh

Master of Science student, Renewable Energy and Environmental Engineering Department, Faculty of New Sciences and Technology, University of Tehran, Iran

Roghayeh Ghasempour

Associate Professor, Renewable Energy and Environmental Engineering Department, Faculty of New Sciences and Technology, University of Tehran, Iran

چکیده

Iran is one of the main consumers of fusil fuels and most Iranian power plants uses fusil fuels to produce electricity. Large industrial greenhouses as one the main consumers of electricity and also as the main producers of food for the society, produce large amount of carbon emissions each year. In order to reduce the use of fusil fuels and reducing carbon emission in these large industrial greenhouses, a hybrid renewable energy system is designed for an industrial greenhouse and all technical, economic and environmental parameters of it are considered and discussed over. All sensitivity analysis of the project effective parameters such as fluctuations of inflation rate, discount rate and diesel price are considered along with the changes of the system and the case study in Alborz province during the project life time, such as PV degradation and increasing of the electrical load of the greenhouse. The study indicates that the optimum on-grid PV/WT/Bio-Gen/Diesel-gen system with the Net Present Cost of 1.73 M$ and Cost of Energy of 0.0918 $ can save 338,396 kg carbon in the 1st year of the project and this amount increases to 439,293 kg in the last year of the project.

کلیدواژه ها

Carbon footprint, Greenhouse, Hybrid energy system, Renewable energy, Environmental analysis

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