تامین توان الکتریکی ایستگاه¬های مخابرات سلولی در ریزشبکه-های مجزا با اولویت بکارگیری منابع تجدیدپذیر و خودروهای الکتریکی با ارائه رویکرد برنامه¬ریزی غیرخطی مختلط با اعداد صحیح
محورهای موضوعی : فناوری اطلاعات و ارتباطات
1 - پژوهشگاه ارتباطات و فناوری اطلاعات
2 - پژوهشگاه ارتباطات و فناوری اطلاعات
کلید واژه: دکل مخابراتی, تامین توان الکتریکی, خودرو های الکتریکی, ریزشبکه, گازهای گلخانه ای,
چکیده مقاله :
این مقاله، موضوع تامین توان اقتصادی و زیست محیطی برای ایستگاه های مخابرات سلولی در یک ریزشبکه مجزای مستقر در مناطق صعب العبور را مورد بررسی قرار داده است. ریزشبکه، شامل ژنراتوردیزلی، سیستم فتوولتاییک و منبع ذخیره هیدروژنی است. امکان تبادل انرژی ریزشبکه با باتری خودرو الکتریکی متصل شده به ریزشبکه، مورد بررسی قرار گرفت. با استفاده از شارژ/دشارژ هوشمند خودروهای الکتریکی تامین توان المان های ریزشبکه، صورت گرفته شده و حداکثر استفاده از انرژی های پاک به عمل آمده است. مدل ریاضی مسئله فوق به عنوان یک برنامه ریزی غیرخطی مختلط با اعداد صحیح ارئه شد که ماهیت غیرخطی المان ها را مدلسازی می کند. در قالب بهینه سازی چندهدفه، بجز هزینه، گازهای گلخانه ای نیز از اهداف مسئله بوده و تعادلی بین این دو هدف متناقض در جبهه پارتو ایجاد شده است. در این مسئله، پارامتر های غیرقطعی، مانند تولید انرژی خورشیدی، الگو های رفتاری راننده ها (زمان رسیدن به ایستگاه شارژ، زمان خروج از ایستگاه شارژ، و مسافت روزانه طی شده، تولید) توسط سناریو های تصادفی مدلسازی شده است. نتایج به دست آمده نشان می دهد که شارژ/دشارژ هوشمند خودروهای الکتریکی، سهم چشمگیری در کاهش ریسک عملیاتی ریزشبکه، هزینه ی کل و گازهای گلخانه ای دارد. به طوریکه، استفاده از روش برنامه ریزی اقتصادی/زیست-محیطی پیشنهاد شده، منجر به %60/18 کاهش در مقدار گازهای گلخانه ای می شود.
The cellular base stations are communication devices that ensure the connection in the world. Nevertheless, they are usually installed in remote places. This paper, studied the energy procurement of a cellular base stations in an independent microgrid with a hydrogen-based energy storage system, photovoltaic (PV) system, electric vehicles and a diesel generator. A new mixed-integer nonlinear programming model was used to deal with nonlinearities of the system components. The paper studied different uncertainties, such as the connection rate in cellular base stations, the driver of the electric vehicle, and PV generation, using stochastic programming method. The potency of the proposed method was studied in different case studies. The results prove that smart electric vehicle chargers reduce the risks and also cost/emission objective functions. The usage of this model can reduce the emissions as much as 18.60%.
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