کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5477076 1521433 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Novel grey prediction model with nonlinear optimized time response method for forecasting of electricity consumption in China
ترجمه فارسی عنوان
مدل پیش بینی خاکستری رمان با روش پاسخ غیر زمان بار بهینه شده برای پیش بینی مصرف برق در چین
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
چکیده انگلیسی
Forecasting of electricity energy consumption (EEC) has been always playing a vital role in China's power system management, and requires promising prediction techniques. This paper proposed an optimized hybrid GM(1,1) model to improve prediction accuracy of EEC in short term. GM(1,1) model, in spite of successful employing in various fields, sometimes gives rise to inaccurate solution in practical applications. Time response function (TRF) is an important factor deeply influencing modeling precision. Aiming to enhance forecasting performance, this paper proposed a novel grey model with optimal time response function, referred to as IRGM(1,1) model. As of unknown variables in TRF, a nonlinear optimization method, based on particle swarm algorithm, is constructed to obtain optimal values, for shrinking simulation errors and improving adaptability to characteristics of raw data. The forecasting performance has been confirmed by electricity consumption data of China, comparing with three alternative grey models. Application demonstrates that the proposed method can significantly promote modeling accuracy.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 118, 1 January 2017, Pages 473-480
نویسندگان
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