مدیریت نیروگاه‌های ذخیره انرژی بزرگ: بهینه‌سازی شارژ و دشارژ با الگوریتم جستجوی فاخته
محورهای موضوعی : مهندسی قدرت
بهنام مطلبی نژاد
1
(گروه مهندسی برق، واحد علی آباد کتول، دانشگاه آزاد اسلامی ، علی آباد کتول، ایران)
مجید حسینا
2
(گروه علوم مهندسی، دانشگاه حکیم سبزواری، سبزوار، ایران)
مجتبی واحدی
3
(گروه مهندسی برق، واحد شاهرود، دانشگاه آزاد اسلامی ، شاهرود ، ایران)
محمود سمیعی مقدم
4
(گروه مهندسی برق، واحد دامغان،دانشگاه آزاد اسلامی، دامغان، ایران)
کلید واژه: الگوریتم تکاملی, بهینه‌سازی, پست فوق توزیع, نیروگاه‌های بزرگ ذخیره انرژی,
چکیده مقاله :
در حال حاضر، با رشد روزافزون جامعه و نیازهای افزایشی به انرژی، استفاده از منابع انرژی تمیز و قابل انعطاف برای تامین نیازهای اجتماعی امری ضروری و حیاتی شده است. . با توجه به پیشرفت‌های فناوری، امروزه امکان ارتقاء نیروگاه‌های ذخیره انرژی به مقیاس بزرگ وجود دارد. معماری و فناوری مدرن این نیروگاه‌ها امکان استفاده بهینه از منابع تجدیدپذیر انرژی را تسهیل کرده و در نتیجه، هزینه‌های انرژی را به شکل چشمگیری کاهش داده و بهره‌وری انرژی را افزایش می‌دهند. همچنین، با استفاده از الگوریتم‌های هوش مصنوعی و بهینه‌سازی، می‌توان عملکرد و عملیات نیروگاه‌های ذخیره انرژی را بهبود بخشید. در این مقاله، به بررسی مدیریت نیروگاه‌های ذخیره انرژی بزرگ پرداخته می‌شود. این مقاله اقدامات نوآورانه‌ای در مدیریت این نیروگاه‌ها ارائه می‌دهد، که شامل محدودیت‌هایی برای تعداد فرآیندهای شارژ و دشارژ در نظر گرفته شده است. به علاوه، الگوریتم جستجوی فاخته به عنوان یک روش قوی و کارآمد در حل مدل پیشنهادی مورد استفاده قرار می‌گیرد. این الگوریتم توانایی پیدا کردن جواب‌های بهینه سراسری را دارد و می‌تواند در بهبود کارایی و افزایش سودآوری نیروگاه‌های ذخیره انرژی بزرگ تأثیرگذار باشد. نتایج شبیه‌سازی نشان می‌دهد که بهره‌بری از این رویکرد در مدیریت نیروگاه‌های ذخیره انرژی مقیاس بزرگ تأثیرات اقتصادی قابل توجهی را به همراه دارد. این تأثیرات شامل کاهش هزینه‌های انرژی، افزایش بهره‌وری، استقلال بیشتر از منابع سوخت فسیلی، حفظ پایداری شبکه برق و بهبود عملکرد سیستم انتقال برق می‌شود.
They are directly integrated into smart distribution networks and can supply stored energy during peak demand periods, while absorbing and storing energy during periods of low demand. This capability helps maintain a balance between supply and demand in power grids, preventing voltage fluctuations and the inability to meet peak loads during high-demand hours. Thanks to technological advancements, it is now possible to upgrade large-scale energy storage facilities. The modern architecture and technology of these facilities facilitate the efficient utilization of renewable energy sources, significantly reducing energy costs and increasing energy efficiency. Additionally, through the use of artificial intelligence algorithms and optimization techniques, the performance and operations of large-scale energy storage facilities can be enhanced. This article focuses on the management of large-scale energy storage facilities, introducing innovative measures that include constraints on the number of charge and discharge processes. Furthermore, the use of the advanced Fakete search algorithm is employed as a powerful and efficient method for solving the proposed model. This algorithm has the capability to find global optimal solutions and can significantly improve the efficiency and profitability of large-scale energy storage facilities. Simulation results demonstrate that adopting this approach in managing large-scale energy storage facilities leads to significant economic impacts. These impacts include reduced energy costs, increased efficiency, greater independence from fossil fuel resources, the preservation of grid stability, and improved performance of the power transmission system.
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