بهینه سازی چند هدفه از یک نیروگاه سه نسلی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|13466||2010||10 صفحه PDF||سفارش دهید||8000 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Policy, Volume 38, Issue 2, February 2010, Pages 945–954
A multi-objective optimization method was developed for the design of trigeneration plants. The optimization is carried out on technical, economical, energetic and environmental performance indicators in a multi-objective optimization framework. Both construction (equipment sizes) and discrete operational (pricing tariff schemes and operational strategy) variables were optimized based on realistic conditions. The problem is solved using a multi-objective evolutionary algorithm. An example of a trigeneration system in a 300 bed hospital was studied in detail in order to demonstrate the design procedure, the economic and energetic performance of the plant, as well as the effectiveness of the proposed approach even under fluctuating energy prices.
Combined generation of different kinds of energy has become a mainstream application of distributed generation during the last decades. The proven advantages of cogeneration technology made it useful firstly in large-scale industrial plants and later on commercial or even resident buildings. Most recent advances, allow the investment of trigeneration systems that produce electricity, heat and cooling, utilizing the primary energy of a fuel even more efficiently, economically, reliably and with less harm to the environment than centralized dedicated production (Wu and Wang, 2006).
نتیجه گیری انگلیسی
The design of a trigeneration plant can be formulated into a multi-objective optimization problem where the final objective criteria are economic, energetic and environmental indices and the decision variables express sizing and operational characteristics. The Pareto-optimal set of efficient solutions can be used for the decision-making process as it clearly shows the impact of any trade-off and its effect on plant performance. Eventual underestimation of benefits involved, due to the assumptions made, will keep the design on the safe side.