برنامه‌ریزی پیشگیرانه و امکانی- احتمالاتی ریزشبکه‌های الکتریکی در برابر حوادث طبیعی و در حضور خودروهای برقی
محورهای موضوعی : مهندسی برق و کامپیوترامیرحسین نثری 1 , امیر عبداللهی 2 * , مسعود رشیدی‌نژاد 3
1 - دانشگاه شهید باهنر کرمان
2 - دانشگاه شهید باهنر کرمان
3 - دانشگاه شهید باهنر کرمان
کلید واژه: برنامه‌ریزی امکانی- احتمالاتی ریزشبکهپارکینگ خودروهای برقیمنابع تجدیدپذیرZ-numberعدم قطعیت,
چکیده مقاله :
این مقاله ساختاری امکانی- احتمالاتی برای برنامه‌ریزی یک روز پیش ریزشبکه‌ها در حضور پارکینگ خودروهای برقی و منابع تولید پراکنده ارائه می‌دهد. برنامه‌ریزی ریزشبکه بر اساس عملکرد آن در حالت عادی و حالت جزیره به دلیل رخداد خطا در شبکه اصلی انجام می‌گردد. در این مطالعه ابتدا عدم قطعیت تعداد خودروهای موجود در پارکینگ در هر ساعت با روش Z-number تعیین می‌گردد. در گام بعد میزان توان تولیدی توربین بادی و پنل‌های فتوولتاییک، قیمت بازار و میزان بار به صورت احتمالاتی با استفاده از روش مونت‌کارلو مدل میگردند. همچنین رخداد حوادث در شبکه بالادست که جزیره‌شدن ریزشبکه را در پی دارد، به صورت سناریومحور و بر اساس زمان شروع رخداد و مدت‌زمان تأثیرگذاری آن در نظر گرفته می‌شود. علاوه بر این، در برنامه‌ریزی بهینه ریزشبکه، ساختاری مبتنی بر عدم قطعیت و شارژ و دشارژ خودروهای برقی برای بهره‌برداری از پارکینگ‌ها پیشنهاد شده است. در این مدل، هزینه بهره‌برداری ریزشبکه در شرایط عملکرد معمول و هزینه عدم تأمین بار و بهره‌برداری به صورت توأمان در حالت رخداد خطا به عنوان توابع هدف پیشنهادی در نظر گرفته شده‌اند. نتایج حاصل از اجرای ساختار پیشنهادی بر روی ریزشبکه اصلاح‌شده 33 باس IEEE، اهمیت این مدل را در بهبود وضعیت امنیت و بهره‌برداری ریزشبکه نشان می‌دهد.
This paper proposes a preventive and probabilistic–possibilistic framework for day-ahead scheduling of Electric Vehicles (EVs) parking lot and distributed generation in a microgrid. The suggested scheduling is performed in normal and emergency conditions when a natural phenomenon appears and the microgrid is disconnected from the upstream network. Furthermore, the uncertainty of EVs number in a parking lot is considered by Z-number as a probabilistic-possibilistic model. Moreover, the uncertainties of photovoltaic units generation, wind turbine output power, market price, and load demand are modeled by Monte Carlo as a probabilistic method. Furthermore, natural phenomena occurrences are modeled by considering multifarious scenarios according to when the phenomenon unfolds and how much it takes. In the suggested framework, the operation of parking lots is based on the uncertainty and EVs charging/discharging schedule. The operational cost in normal condition and load shedding cost in addition to operational cost are considered as the objective functions of the proposed structure. To evaluate the performance of the suggested structure, the modified 33-bus IEEE distribution network is employed.
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