بهینه‌سازی چندهدفه مدل جیره‌بندی بهره‌برداری از مخزن با استفاده از الگوریتم‌های هوشمند

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی منابع آب، دانشگاه بیرجند

2 استادیار گروه مهندسی آب دانشگاه بیرجند

3 استادیار گروه مهندسی آب دانشگاه کشاورزی و منابع طبیعی رامین خوزستان

چکیده

مسائل بهره‌برداری از مخزن دارای اهداف مختلف و متنوع هستند که به ندرت منتهی به یک جواب بهینه می‌شوند و معمولاً در آن‌ها مجموعه‌ای از جواب‌های بهینه (پارتو) موجود است. حل این گونه مسائل در گذشته تنها با کاربرد روش‌های ساده کننده میسر بوده است که از آن جمله می‌توان به استفاده از ضرایب وزنی برای اهداف مختلف و تبدیل آن‌ها به یک تابع هدف استفاده کرد. اما در سال‌های اخیر با توسعه الگوریتم‌های چند هدفه تکامل‌گرا، ابزار مناسبی برای حل آن‌ها فراهم شده است. یکی از مسائل کلاسیک در این مدل جیره‌بندی بهره‌برداری از مخزن است که کاربرد آن برای کاهش اثرات خشکسالی در مدیریت منابع آب بسیار متداول است. در تحقیق حاضر بهینه‌سازی چند هدفه مدل جیره‌بندی با استفاده از الگوریتم‌های NSGA-II،MOPSO ، SPEA-IIو AMALGAM انجام شد. در این راستا، یافتن مقادیر بهینه ضرایب جیره‌بندی سد طالقان در یک دوره آماری 35 ساله آبدهی و با دو هدف کمینه نمودن شاخص اصلاح شده کمبود و بیشینه نمودن شاخص اعتمادپذیری (دو هدف متناقض با یکدیگر)، در دستور کار قرار گرفت. نتایج نشان داد دوره جیره‌بندی در ماه‌های فصل گرم (نیمه اول سال) است که مقادیر KP مربوط به همه آن‌ها را بیشینه نمود. مقادیر KP در ماه‌های سرد نیز به سمت کمترین مقدار پیش رفته که در حقیقت نزدیک شدن به همان سیاست SOP را در پی خواهد داشت. همچنین در این تحقیق کارایی الگوریتم‌های مذکور برای ارائه دامنه وسیعی از جواب‌های بهینه مشاهده شد.

کلیدواژه‌ها


عنوان مقاله [English]

Multi-Objective Optimization of the Hedging Model for reservoir Operation Using Evolutionary Algorithms

نویسندگان [English]

  • sadegh sadeghitabas 1
  • mohsen pourreza bilondi 2
  • mehrdad taghian 3
1 MSc Student of Water Resources Management, University of Birjand
2 Ass. Prof. of Water Engineering, University of Birjand
3 Ass. Prof. of Water Engineering, Agriculture and Natural Resources University, Ramin, Khoozestan
چکیده [English]

Multi-objective problems rarely ever provide a single optimal solution, rather they yield an optimal set of outputs (Pareto fronts). Solving these problems was previously accomplished by using some simplifier methods such as the weighting coefficient method used for converting a multi-objective problem to a single objective function. However, such robust tools as multi-objective meta-heuristic algorithms have been recently developed for solving these problems. The hedging model is one of the classic problems for reservoir operation that is generally employed for mitigating drought impacts in water resources management. According to this method, although it is possible to supply the total planned demands, only portions of the demands are met to save water by allowing small deficits in the current conditions in order to avoid or reduce severe deficits in future. The approach heavily depends on economic and social considerations. In the present study, the meta-heuristic algorithms of NSGA-II, MOPSO, SPEA-II, and AMALGAM are used toward the multi-objective optimization of the hedging model. For this purpose, the rationing factors involved in Taleghan dam operation are optimized over a 35-year statistical period of inflow. There are two objective functions: a) minimizing the modified shortage index, and b) maximizing the reliability index (i.e., two opposite objectives). The results show that the above algorithms are applicable to a wide range of optimal solutions. Among the algorithms, AMALGAM is found to produce a better Pareto front for the values of the objective function, indicating its more satisfactory performance.

کلیدواژه‌ها [English]

  • Hedging
  • Multi objective Optimization
  • Reservoir operation
  • meta-heuristic algorithms

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