کاربرد الگوریتم بهینه‌سازی کپک مخاطی (SMOA) در بهره‌برداری بهینه از سامانه سه‌مخزنه برق‌آبی

نوع مقاله : مقاله پژوهشی

نویسنده

گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه قم، قم، ایران.

10.22059/jwim.2023.364129.1096

چکیده

مدیریت انرژی برق‌آبی تحت شرایط تغییر اقلیم ضروری است. در این پژوهش برای بهینه‌سازی سامانه سه‌مخزن برق‌آبی از الگوریتم بهینه‌سازی کپک مخاطی1 (SMOA) استفاده می‌شود و برای ارزیابی عملکرد SMOA، نتایج آن با الگوریتم ژنتیک2 (GA)، مقایسه می‌شود. قبل از هر چیز، عملکرد SMOA برای تابع آزمون اکلی3 سنجیده می‌شود که عملکرد موفقیت‌آمیزی داشته است. در گام بعد، بهینه‌سازی بر روی سامانه سه‌مخزنه برق‌آبی سازبن مخزنی، سیمره و کرخه جریانی واقع در حوضه آبریز کرخه (ایران) استفاده می‌شود. بهینه‌سازی مسئله برق‌آبی برای دوره پایه 2005-1976 و دوره آینده 2069-2040 تحت سناریوی تغییر اقلیم RCP8.5 اجرا می‌شود. تابع هدف عبارت است از کمینه‌سازی کمبود تأمین انرژی برق‌آبی. برای بهینه‌سازی مسئله سه‌مخزنه برق‌آبی، نتایج نشان می‌دهند که مقدار تابع هدف بر‌اساس SMOA به مقدار بهینه مطلق نزدیک می‌باشد به‌ویژه در دوره‌ تغییر اقلیم. به‌طور کلی، عملکرد SMOA برای دست‌یابی به مقدار بهینه تابع هدف در دوره‌های تغییر اقلیم نسبت به دوره پایه بهتر و جواب‌ها پایاتر می‌باشد. در مقایسه بین SMOA و GA برای حالت بهره‌برداری سه‌مخزنه در دوره پایه و دوره آتی تحت سناریوی RCP8.5، عملکرد SMOA در رسیدن به مقدار مطلوب تابع هدف بسیار بهتر، سرعت همگرایی بیش‌تر، مدت زمان اجرا کم‌تر و جواب‌های تابع هدف پایاتر می‌باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Application of the Slime Mould Optimization Algorithm (SMOA) in the Hydropower Three-Reservoir System Optimal Operation

نویسنده [English]

  • Parisa-Sadat Ashofteh
Department of Civil Engineering, University of Qom, Qom, Iran.
چکیده [English]

Hydropower energy management is essential under climate change conditions. In this research, Slime Mould Optimization Algorithm (SMOA) is used to optimize the system of three hydropower reservoirs, and its results are compared with Genetic Algorithm (GA) to evaluate the performance of SMOA. First of all, SMOA performance is measured for Akley test function, which has been successfully performed. In the next step, the optimization is used on the three-reservoir hydropower system of Sazbon reservoir, Seymareh and Karkheh stream located in the Karkheh basin (Iran). The optimization of the hydropower problem is carried out for the baseline period of 1976-2005 and the future period of 2040-2069 under the RCP8.5 climate change scenario. The objective function is to minimize the lack of hydropower supply. For the optimization of the three-reservoir hydropower problem, the results show that the value of the objective function based on SMOA is close to the absolute optimal value, especially in the period of climate change. In general, the performance of SMOA to achieve the optimal value of the objective function in climate change periods is better than the baseline period and the solutions are more stable. In the comparison between SMOA and GA for the three-reservoir operation mode in the baseline and future period under the RCP8.5 scenario, the performance of SMOA in reaching the desired value of the objective function is much better, the speed of convergence is higher, the run-time is shorter, and the solutions of the objective function are more stable.

کلیدواژه‌ها [English]

  • Climate change
  • Genetic algorithm
  • Hydropower three-reservoir system
  • Slime mould optimization algorithm

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مدیریت آب و آبیاری
دوره 13، شماره 4
دی 1402
صفحه 929-944

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