مدیریت توان راکتیو در شبکه توزیع با درنظرگرفتن عدم قطعیت‌ها در حضور تجهیزات جبران‌کننده توان راکتیو گسسته و پیوسته
محورهای موضوعی : مهندسی برق و کامپیوتر
محبوبه اعتمادی زاده
1
(دانشگاه بیرجند)
مریم رمضانی
2
(دانشگاه بیرجند)
حمید فلقی
3
(دانشگاه بیرجند)
کلید واژه: بانک‌های خازنی, پخش بار احتمالی, سیستم‌های ذخیره‌ساز انرژی, عدم قطعیت, مدیریت توان راکتیو, منابع تولید پراکنده,
چکیده مقاله :
سرعت افزایش سطح نفوذ منابع تولید پراکنده در شبکه قدرت و ماهیت تصادفی این منابع، نحوه بهره‌برداری و طراحی این شبکه‌ها را دستخوش تغییر کرده که مدیریت توان راکتیو در شبکه‌های توزیع از این دسته هستند. استفاده از این منابع در شبکه‌های توزیع بدون چالش نیست و عدم مدیریت بهینه توان راکتیو ممکن است که بهره‌وری‌های اقتصادی برای شبکه به همراه نداشته باشد. سیستم‌های ذخیره‌ساز انرژی، پتانسیل حل این مشکل را دارند؛ لذا در این مقاله، مدیریت توان راکتیو در یک ریزشبکه متصل به شبکه اصلی با درنظرگرفتن منابع تولید پراکنده (DG)، سیستم‌های ذخیره انرژی الکتریکی (BESS) و تجهیزات جبران‌کننده توان راکتیو گسسته شامل بانک‌های خازنی با درنظرگرفتن عدم قطعیت در بار شبکه و تولید توان نیروگاه بادی و خورشیدی انجام شده است. نهایتاً کارایی روش بیان‌شده با انجام مطالعات عددی بر روی شبکه‌های توزیع 33 و 69شینه IEEE و در محیط نرم‌افزار بهینه‌سازی GAMS پیاده‌سازی گردیده است.
The increasing rate of distributed generation resources expansion into power systems and the random nature of these resources have altered the operation and design of these networks, and reactive power management in distribution networks belongs to this category. The use of these resources in distribution networks is not without challenges and the lack of optimal management of reactive power may not bring economic efficiency for the network. Energy storage systems have the potential to solve this problem. Therefore, in this article, reactive power management in a microgrid connected to the main grid, taking into account distributed generation sources, energy storage systems and discrete reactive power compensating equipment, including capacitor banks, taking into account uncertainty in network load and Wind and solar power generation has been done. Finally, the efficiency of the method is demonstrated by numerical examinations on the distribution networks of 33 and 69 IEEE buses and in the GAMS optimization software.
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