کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
398263 1438720 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Short-term forecast of daily curves of electricity demand and price
ترجمه فارسی عنوان
پیش بینی کوتاه مدت منحنی روزانه تقاضای برق و قیمت
کلمات کلیدی
بار و قیمت، بازار برق، داده های عملکردی، پیش بینی سری سری های کاربردی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• Regression models with functional response are proposed to forecast daily curves of electricity demand and price.
• A comparative study, including results from models with functional or scalar response, is reported.
• The proposed models result very competitive.

The features of the electricity, as well as the rules of the competitive electricity markets, create the need of accurate predictions of electricity demand and price in order to anticipate decisions. Mainly, the prediction task in energy markets has been studied in the literature with the aim of obtaining scalar (hourly, daily, …) forecasts given scalar (and/or, less frequently, functional) historical data. This paper provides two methods to predict next-day electricity demand and price daily curves given information from past curves. They are based on using robust functional principal component analysis and nonparametric models with functional both response and covariate. In addition, the nonparametric proposal is extended to incorporate, in a linear way, exogenous scalar covariates. Results of these methods for the electricity market of mainland Spain, in year 2012, are reported. Their accuracy is compared with that of a naïve method as well as with the corresponding to combining forecasts. Scalar versions are also included in the comparative study. This work extends and complements the methods and results in Vilar et al. (2012), focused on scalar forecasts.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 80, September 2016, Pages 96–108
نویسندگان
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