دانلود مقاله ISI انگلیسی شماره 92514
ترجمه فارسی عنوان مقاله

چندین هدف بهینه سازی افق به منظور برنامه ریزی مطلوب سیستم انرژی تجدید پذیر ترکیبی

عنوان انگلیسی
Multi objective receding horizon optimization for optimal scheduling of hybrid renewable energy system
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
92514 2017 41 صفحه PDF
منبع

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

Journal : Energy and Buildings, Volume 150, 1 September 2017, Pages 583-597

ترجمه کلمات کلیدی
بهینه سازی چشم انداز چندین هدف، سیستم مدیریت انرژی، برنامه ریزی مطلوب، سیستم انرژی تجدید پذیر ترکیبی،
کلمات کلیدی انگلیسی
Multi objective receding horizon optimization; Energy management system; Optimal scheduling; Hybrid renewable energy system;
پیش نمایش مقاله
پیش نمایش مقاله  چندین هدف بهینه سازی افق به منظور برنامه ریزی مطلوب سیستم انرژی تجدید پذیر ترکیبی

چکیده انگلیسی

In this paper, a methodology for energy management system (EMS) based on the multi-objective receding horizon optimization (MO-RHO) is presented to find the optimal scheduling of hybrid renewable energy system (HRES). The proposed HRES which is experimentally installed in educational building comprising the PV panels, wind turbine, battery bank and diesel generator as the backup system. The data acquisition system provides input profiles for receding horizon optimizer. A mixed-integer convex programing technique is used to achieve the optimal operation regarding to two conflicting operation objectives including diesel fuel cost and battery wear cost. The Pareto frontiers are presented to show the trade-offs between two operation objective functions. Analysis of obtained results demonstrates that the system economic and technical performance are improved using longer prediction horizon. The results show that using longer time view (from 6 h to 24 h) the total share of renewable energy in supplying weekly demand can be improved up to 18.7%. Therefore, the proposed methodology can manage system to make a better use of resources resulting in a better system scheduling. The sensitivity analysis also demonstrates the effectiveness of seasonal variations of available renewable resources on the optimal operation scheduling.