یک روش ترکیبی پیش بینی احتمالاتی بلندمدت بار خالص شبکه با در نظر گرفتن اثر توان تولید‌شده توسط منابع انرژی تجدیدپذیر در شبكه‌هاي هوشمند
الموضوعات :
محسن جهان تیغ
1
(دانشگاه آزاد اسلامی واحد نجف آباد)
مجيد معظمي
2
(دانشگاه آزاد اسلامي واحد نجف آباد)
الکلمات المفتاحية: پیش بینی احتمالاتی بلندمدت بار, تحلیل اجزای همسایگی, سیستم استنتاج عصبی- فازی, شبکه هوشمند, تولید بادی, تولید فوتوولتائیک,
ملخص المقالة :
امروزه با توجه به رشد گسترده و نفوذ استفاده از منابع توليد پراكنده در شبكه‌هاي هوشمند، پيش‌بيني بار خالص شبكه با در نظر گرفتن اثر توليدات پراكنده اهميت قابل توجهي پيدا كرده است. در اين مقاله يك روش بهينه‌سازي تركيبي به منظور پیش‌بینی احتمالاتي بلندمدت بار خالص شبكه با استفاده از روش تحلیل اجزای همسایگی و حل مسأله رگرسیون به روش mini-batch-LBFGS و ترکیب پیش‌بینی‌های به دست آمده با استفاده از سیستم استنتاج عصبی- فازی تطبیقی ارائه شده است. اين ساختار شامل تركيب چندين پيش‌بيني بلندمدت از جمله پیش‌بینی بار، توان يك ايستگاه خورشيدي و توان یک مزرعه بادی با توربینهای بادی مجهز به ژنراتور القایی دوسوتغذیه است. پیش‌بینی بار خالص و بررسی وابستگی موجود بین خطاهای پیش‌بینی بار و توانهای خورشیدی و بادی نیز در این مقاله مورد مطالعه قرار گرفته است. نتايج شبيهسازي روش پيشنهادي و مقایسه آن با مدلهای تائو و رگرسیون چندکی نشان می‌دهد که درصد میانگین مطلق خطا برای پیش‌بینی‌های بار و توانهای خروجی ایستگاه خورشیدی و مزرعه بادی به ترتیب به میزان 947/0%، 3079/0% و 0042/0% بهبود یافته است که کاهش خطای کلی پیش‌بینی را سبب می‌شود.
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