کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6883548 1444175 2018 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Smart grid load forecasting using online support vector regression
ترجمه فارسی عنوان
پیش بینی بار شبکه هوشمند با استفاده از رگرسیون بردار آنلاین پشتیبانی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
Smart grid, an integral part of a smart city, provides new opportunities for efficient energy management, possibly leading to big cost savings and a great contribution to the environment. Grid innovations and liberalization of the electricity market have significantly changed the character of data analysis in power engineering. Online processing of large amounts of data continuously generated by the smart grid can deliver timely and precise power load forecasts - an important input for interactions on the market where the energy can be contracted even minutes ahead of its consumption to minimize the grid imbalances. We demonstrate the suitability of online support vector regression (SVR) method to short term power load forecasting and thoroughly explore its pros and cons. We present a comparison of ten state-of-the-art forecasting methods in terms of accuracy on public Irish CER dataset. Online SVR achieved accuracy of complex tree-based ensemble methods and advanced online methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Electrical Engineering - Volume 65, January 2018, Pages 102-117
نویسندگان
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