دانلود مقاله ISI انگلیسی شماره 92551
ترجمه فارسی عنوان مقاله

یکپارچه سازی بهینه از منابع انرژی تجدید پذیر برای سیستم خنک کننده، گرمایش و قدرت سیستم ترکیبی سه گانه مستقل بر اساس الگوریتم بهینه سازی ذرات تکامل

عنوان انگلیسی
Optimal integration of renewable energy sources for autonomous tri-generation combined cooling, heating and power system based on evolutionary particle swarm optimization algorithm
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
92551 2018 53 صفحه PDF
منبع

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

Journal : Energy, Volume 145, 15 February 2018, Pages 839-855

ترجمه کلمات کلیدی
انرژی تجدید پذیر، خنک کننده ترکیبی گرمایش و قدرت، ذخیره انرژی، بهینه سازی ذرات تکامل،
کلمات کلیدی انگلیسی
Renewable energy; Combined cooling; Heating and power; Energy storage; Evolutionary particle swarm optimization;
پیش نمایش مقاله
پیش نمایش مقاله  یکپارچه سازی بهینه از منابع انرژی تجدید پذیر برای سیستم خنک کننده، گرمایش و قدرت سیستم ترکیبی سه گانه مستقل بر اساس الگوریتم بهینه سازی ذرات تکامل

چکیده انگلیسی

Renewable energy (RE) sources can be integrated to serve autonomous tri-generation combined cooling, heating and power (CCHP) systems, so that the advantages of zero environmental emissions as well as higher energy efficiencies in generation and consumption are realized simultaneously. However, to override the inherent intermittent availability of RE sources and to enhance the performance of RE-CCHP systems, it is necessary to include thermal and electrical storage mechanisms. The objective of this study is to develop a simulation model for optimization of different configuration alternatives of autonomous RE-CCHP system for meeting cooling, heating and electrical loads, based on photovoltaic-thermal (PVT) panel, wind turbine (WT), thermal energy storage (TES), electrical energy storage (EES), absorption chiller (CHABS), electric chiller (CHELEC) and electric heater (EH). For operation of autonomous RE-CCHP system, two operational strategies, namely, following electric load (FEL) and following thermal load (FTL), are used. For optimization, a newly developed evolutionary particle swarm optimization (E-PSO) algorithm is examined and validated. It is demonstrated that the most cost effective configuration alternative of the autonomous RE-CCHP system is PVT+WT+EES+TES+CHABS+EH operating based on FTL operational strategy, where utilization of CHELEC is not needed.