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تخصیص بهینه منابع تجدیدپذیر در شبکه‌های توزیع با در نظر گرفتن عدم قطعیت بر اساس تئوری تصمیم‌گیری شکاف اطلاعاتی با استفاده از الگوریتم اجتماع سالپ بهبودیافته | ||
| مدل سازی در مهندسی | ||
| دوره 20، شماره 68، فروردین 1401، صفحه 207-223 اصل مقاله (985.92 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22075/jme.2021.23075.2078 | ||
| نویسندگان | ||
| رحیم فتحی1؛ بهروز طوسی* 2؛ سجاد گلوانی2 | ||
| 1برق قدرت، دانشکده فنی، دانشگاه ارومیه, ارومیه - ایران | ||
| 2گروه مهندسی برق قدرت- دانشکده برق کامپیوتر-دانشگاه ارومیه | ||
| تاریخ دریافت: 23 فروردین 1400، تاریخ بازنگری: 13 تیر 1400، تاریخ پذیرش: 24 شهریور 1400 | ||
| چکیده | ||
| در این مقاله تخصیص بهینه منابع تجدیدپذیر با هدف کمینه‌سازی هزینه تلفات توان و هزینه بهبود قابلیت اطمینان و با در نظر گرفتن عدم قطعیت تولید و مصرف بر اساس روش جدید تئوری تصمیم‌گیری شکاف اطلاعاتی (IGDT) ارائه شده است. متغیرهای تصمیم‌گیری شامل مکان، ظرفیت نصب و ضریب قدرت و همچنین شعاع عدم قطعیت تولید منابع تجدیدپذیر و بار شبکه با استفاده از الگوریتم اجتماع سالپ بهبودیافته (ISSA) بصورت بهینه تعیین شده است. در روش ISSA، عملکرد روش اجتماع سالپ سنتی (SSA) برای بهبود سرعت و دقت همگرایی با استفاده از عمل‌گرهای روش دیفرانسیلی تکاملی (DE) بهبود یافته است. مساله پیشنهادی با دو روش قطعی و روش مبتنی بر IGDT با راهبرد ریسک گریز بر روی شبکه توزیع 33 شینه استاندارد IEEE پیاده‌سازی شده است. نتایج به دست آمده نشان می دهد که برای شبکه 33 شینه برای توربین بادی با افزایش 20% بودجه عدم قطعیت، بار شبکه 61/7 % افزایش یافته و تولید توربین بادی به مقدار 06/44% کاهش یافته است. همچنین نسبت به حالت قطعی مقدار هزینه تلفات و هزینه قابلیت اطمینان به ترتیب 87/20 و 58/4 درصد افزایش یافته و سود مالی شبکه نیز 33/6% کاهش یافته است. | ||
| کلیدواژه‌ها | ||
| الگوریتم اجتماع سالپ؛ تخصیص بهینه منابع انرژی تجدیدپذیر؛ تئوری تصمیم‌گیری شکاف اطلاعاتی؛ دیفرانسیل تکاملی؛ عدم قطعیت؛ قابلیت اطمینان | ||
| عنوان مقاله [English] | ||
| Optimal Allocation of Renewable Resources in Distribution Networks Considering Uncertainty Based on Info-Gap Decision Theory Using Improved Salp Swarn Algorithm | ||
| نویسندگان [English] | ||
| Rahim Fathi1؛ Behrouz Tousi2؛ sadjad galvani2 | ||
| 1Electrical Faculty. Urmia University. Urmia. Iran | ||
| 2Department of electrical power engineering, faculty of electrical engineering, urmia university | ||
| چکیده [English] | ||
| In this paper, the optimal allocation of renewable energy resources is presented with the aim of minimizing cost of power losses and reliability improvement considering generation and load uncertainty using new approach named information gap decision theory (IGDT). Decision variables include location, size and power factor of renewable resources, also the maximum uncertainty radius of generation and load using improved salp swarm algorithm (ISSA). In the ISSA method, the performance of traditional salp swarm algorithm is improved to increase convergence speed and accuracy using evolutionary differential operators. The problem is implemented as deterministic and IGDT-based methods on 33 bus-IEEE networks with risk aversion. In the wind turbine scenario, the results showed that for the 33 bus network in the deterministic method that is increased by 20% in IGDT, the network load is increased by 7.61% and wind turbine generation is decreased by 44.06%. Also, compared to the deterministic method, the losses cost and reliability cost increased by 20.87% and 4.58%, respectively and the net saving is decreased by 6.33%. | ||
| کلیدواژه‌ها [English] | ||
| Salp Swarm Algorithm, Optimal Allocation of Renewable Resources, Info-Gap Decision Theory, Differential Evolutionary, Uuncertainty, Reliability | ||
| مراجع | ||
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