نوع مقاله : پژوهشی

نویسندگان

1 گروه مهندسی برق- واحد خمین، دانشگاه آزاد اسلامی، خمین، ایران

2 گروه مهندسی برق و کا مپیوتر- دانشکده فنی مهندسی گلپایگان، دانشگاه صنعتی اصفهان، گلپایگان

چکیده

در این مقاله نسخه جهش یافته دینامیکی الگوریتم بهینه ­سازی گرگ خاکستری برای حل مسئله پخش بار اقتصادی- زیست­ محیطی سیستم قدرت استاندارد 40 واحدی به همراه دو مزرعه بادی پیشنهاد شده است. لذا تابع هدفی جامع از هزینه­های بهره­برداری که ترکیبی از هزینه­های مستقیم انرژی باد، هزینه جریمه تخمین بیش از حد، هزینه جریمه تخمین کمتر از حد، هزینه واحد حرارتی و هزینه آلایندگی، ارائه شده است. با توجه به ماهیت تصادفی سرعت باد توان تولیدی توسط توربین­های بادی غیرقابل پیش­بینی است، بنابراین از تابع توزیع احتمال ویبول برای مدل­سازی توان مزرعه­های باد در این مقاله استفاده شده است. هزینه بهره­برداری مزرعه بادی به­صورت احتمالاتی در نظر گرفته شده است تا سناریوهای باد با احتمال پایین تاثیر کمتری در هزینه نهایی داشته باشند. شبیه­سازی­ها در قالب سه بخش انجام شده است و به­منظور اعتبارسنجی با مرجع­های دیگر مورد مقایسه واقع شده است. نتایج حاصل شده از بهینه­سازی­ها در هر سه سناریو و مقایسه آن با الگوریتم­های هوشمند تائیدی بر عملکرد بهتر و دقت بالاتر الگوریتم پیشنهادی نسبت به نسخه اصلی الگوریتم گرگ خاکستری و همچنین سایر الگوریتم­ها دارد.

چکیده تصویری

ایجاد یک جهش در الگوریتم گرگ خاکستری برای حل مسئله توزیع اقتصادی-زیست‌محیطی نیروگاه‌های ادغام شامل حرارتی و بادی

تازه های تحقیق

- یک نگاه کلی به برنامه مشارکت واحدهای نیروگاه های حرارتی دارد که پیامد عدم توجه به آن وقوع پدیده ای مخرب برای محیط زیست و افزایش هزینه در پی مصرف ناصحیح از واحد تولیدی است.

- بطور کلی نبود یک برنامه کافی و جامع برای ورود و خروج بهینه واحدهای تولید در مسئله مشارکت بهینه تولید، سبب افزایش هزینه و نهایتا مصرف بی رویه و نااگاهانه سوخت می­گردد.

- همچنین حضور نیروگاه های تجدیدپذیر در کنار نیروگاه های سنتی، موجب کاهش سطح آلایندگی و نهایتا کاهش هزینه تولید توان، در برنامه مشارکت می­شود.

- در آخر یک بررسی دقیق در حوزه الگوریتم های بهینه­سازی برای حل مسئله مشارکت واحدها ارائه شده است، که نسبت به نسخه ­های اولیه الگوریتم دقت بالاتری دارد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Apply a Mutation in Gray Wolf Optimization Algorithm to Solve the Economic-Environmental Dispatch Problem of Integrated Power Plants Including Thermal and Wind

نویسندگان [English]

  • Mahdi Afroozeh 1
  • Hamidreza Abdalmohammadi 2
  • Mohammad-Esmaeil Nazari 2

1 Department of Electrical Engineering- Khomein Branch, Islamic Azad University, Khomein, Iran

2 Electrical and Computer Engineering Group- Golpayegan College of Engineering, Isfahan University of Technology, Golpayegan, Iran

چکیده [English]

In this paper, a dynamic mutant version of the gray wolf optimization algorithm (MGWO) is proposed to solve the economic-environmental dispatch (E-ED) problem of a standard 40-unit power system with two wind farms. Thus, a comprehensive objective function of operating costs is presented, which is a combination of wind energy costs, over-estimated penalty costs, under-estimated penalty costs, thermal unit costs and emission costs. Due to the random nature of wind speed, the power generated by wind turbines is unpredictable. Therefore, the Weibull probability distribution function has been used to model the wind farm power in this paper. The cost of operating a wind farm is considered probabilistic so that low-probability wind scenarios have less effect on the total operation cost. The simulations are performed in the form of three section and the optimization results are compared with several meta-heuristic algorithm results for validation. The results of the optimizations in all three scenarios and its comparison with other algorithms confirm the better performance and higher accuracy of the proposed MGWO algorithm than the original version of the gray wolf algorithm (GWO) as well as other algorithms.

کلیدواژه‌ها [English]

  • economic environmental dispatch
  • mutant gray wolf optimization algorithm
  • Steam valve effect
  • Wind Farms

Citation: M. Afroozeh, H.R. Abdolmohammadi, M.E. Nazari, "Apply a mutation in gray wolf optimization algorithm to solve the economic-environmental dispatch problem of integrated power plants including thermal and wind", Journal of Intelligent Procedures in Electrical Technology, vol. 14, no. 56, pp. 59-76, March 2024 (in Persian).

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