مشخصات مقاله | |
ترجمه عنوان مقاله | بهینه سازی ظرفیت و عملکرد سیستم CCHP (سیستم ترکیبی خنک کننده حرارت و قدرت) با استفاده از الگوریتم ژنتیک |
عنوان انگلیسی مقاله | Optimization of capacity and operation for CCHP system by genetic algorithm |
انتشار | مقاله سال 2010 |
تعداد صفحات مقاله انگلیسی | 11 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | scopus – master journals – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
7.900 در سال 2017 |
شاخص H_index | 140 در سال 2018 |
شاخص SJR | 3.162 در سال 2018 |
رشته های مرتبط | مهندسی برق – مهندسی کامپیوتر |
گرایش های مرتبط | الکترونیک قدرت – سیستم های قدرت – الگوریتم و محاسبات |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | Applied Energy |
دانشگاه | School of Energy and Power Engineering, North China Electric Power University, Baoding, Hebei Province 071003, China |
کلمات کلیدی | سیستم ترکیبی خنک کننده حرارت و قدرت، بهینه سازی، ظرفیت، استراتژی عملیات، الگوریتم ژنتیک |
کلمات کلیدی انگلیسی | (Combined cooling heating and power (CCHP) system, Optimization, Capacity, Operation strategy, Genetic algorithm (GA |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.apenergy.2009.08.005 |
کد محصول | E11780 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Outline Abstract Keywords Nomenclature 1. Introduction 2. CCHP system 3. Optimization 4. Application 5. Analysis and discussion 6. Conclusion Acknowledgements References |
بخشی از متن مقاله: |
Abstract The technical, economical and environmental performances of combined cooling, heating and power (CCHP) system are closely dependent on its design and operation strategy. This paper analyzes the energy flow of CCHP system and deduces the primary energy consumption following the thermal demand of building. Three criteria, primary energy saving (PES), annual total cost saving (ATCS), and carbon dioxide emission reduction (CDER) are selected to evaluate the performance of CCHP system. Based on the energy flow of CCHP system, the capacity and operation of CCHP system are optimized by genetic algorithm (GA) so as to maximize the technical, economical and environmental benefits achieved by CCHP system in comparison to separation production system. A numerical example of gas CCHP system for a hotel building in Beijing is given to ascertain the effectiveness of the optimal method. Furthermore, a sensitivity analysis is presented in order to show how the optimal operation strategy would vary due to the changes of electricity price and gas price. Introduction Combined cooling, heating and power (CCHP) system is broadly identified as an alternative for the world to meet and solve energyrelated problems, such as increasing energy demands, increasing energy cost, energy supply security, and environmental concerns [1–6]. A good CCHP system must yield economical savings, but more importantly must yield real energy savings as well as reducing the emission of pollutants. The performance of CCHP system is closely dependent on its design and operation. Aiming to maximize the benefits from CCHP system in comparison to traditional separation production (SP), it is necessary to optimize the design and operation strategy. Many studies have been reported on this topic. Better performances (e.g. operations cost, carbon dioxide emission reduction (CDER), and primary energy consumption (PEC)) can be obtained when the optimization was applied to design and/or operate CCHP systems. The optimized CCHP systems have different components. For example, the prime mover includes gas turbine [7–9], steam turbine [10,11], gas engine [12,13], a steam Rankine process using biomass fuels [14], and the cooling system adopts compression [15], absorption [7,15], and ejector refrigeration cycle [11], etc. |