کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11007382 | 1521388 | 2018 | 53 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Predictive management of cogeneration-based energy supply networks using two-stage multi-objective optimization
ترجمه فارسی عنوان
مدیریت پیشگیرانه از شبکه های تامین انرژی مبتنی بر همگنی با استفاده از دو مرحله ای بهینه سازی چند هدفه
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کلمات کلیدی
مدیریت انرژی، بهینه سازی چند هدفه، ریزشبکه، همگام سازی، کنترل پیش بینی مدل، برنامه ریزی خطی مختلط عدد صحیح،
mixed-integer linear programming - برنامه ریزی خطی مخلوط عددیMulti-objective optimization - بهینه سازی چند هدفهCogeneration - تولید همزمان گرما و برق یا به اخنصار تولید همزمان معروف به CHPMicrogrid - ریزشبکه Energy management - مدیریت انرژیModel predictive control - کنترل پیش بین، کنترل پیش بینی مدل
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی (عمومی)
چکیده انگلیسی
A predictive management system for cogeneration unit-based energy supply networks using two-stage multi-objective optimization was developed to tackle a trade-off between energy savings and operating cost reduction. The developed system integrated support vector regression-based energy demand prediction, MILP (mixed-integer linear programming)-based schedule planning, and rule-based operation control. The contribution is to develop two-stage MILP-based multi-objective schedule planning, which is extension of an ε-constraint method, and operation control rule of multiple cogeneration units. In the first-stage schedule planning, primary energy consumption in the prediction horizon is minimized, and a reduction rate of primary energy consumption is calculated. In the second-stage schedule planning, an operating cost is minimized additionally subject to satisfaction of partial achievement of the reduction rate of primary energy consumption calculated in the first stage. An energy-saving achievement rate is regarded as a decision-making parameter to control a trade-off between energy savings and cost reduction, of which definition is quantitatively apprehensible for decision makers. Annual operating simulation of an energy supply network using four fuel-cell-based cogeneration units revealed that the developed predictive management system has high controllability to the trade-off between the energy-saving rates (18.9%-21.6%) and the operating cost reduction rate (19.0%-15.6%), caused by a time-of-use power tariff structure.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 162, 1 November 2018, Pages 1269-1286
Journal: Energy - Volume 162, 1 November 2018, Pages 1269-1286
نویسندگان
Tetsuya Wakui, Kento Sawada, Ryohei Yokoyama, Hirohisa Aki,