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2019 | 28 | 3 |
Tytuł artykułu

Elman-based forecaster integrated by Adaboost algorithm in 15 min and 24 h ahead power output prediction using PM 2.5 values, PV module temperature, hours of sunshine, and meteorological data

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Nowadays, with the depletion of fossil energy and deterioration of environmental quality, solar energy is perceived to be a renewable and clean energy. While developing rapidly all over the world, solar energy is also faced with many challenges resulting from its inherent properties. In order to reduce the impact on the grid and facilitate scheduling, it is a growing problem to build a feasible model to forecast PV power with high precision. Therefore, this paper proposes an Elman-based forecaster integrated by Adaboost algorithm, namely Adaboost + Elman. Before forecasting, input variables containing PM 2.5 values, temperature of the PV module, sunshine hours, and meteorological data are made using correlation, clustering, and discriminate analysis to avoid information redundancy and improve the generalization ability of the model. To verify the developed model’s application to short-term PV forecasting in two different time scales, data of Huangsi in 2016 are used for model construction and verification. An additional 7 models are introduced to make comparison. Experimental results prove that the proposed model is effective and practicable for two different scales of short-term PV power prediction.
Słowa kluczowe
Wydawca
-
Rocznik
Tom
28
Numer
3
Opis fizyczny
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Twórcy
autor
  • Department of Economics and Management, North China Electric Power University, Baoding, China
autor
  • Department of Economics and Management, North China Electric Power University, Baoding, China
autor
  • Department of Economics and Management, North China Electric Power University, Baoding, China
autor
  • Department of Economics and Management, North China Electric Power University, Baoding, China
autor
  • Dezhou Power Supply Company, Dezhou City, Shandong Province, China
autor
  • Spic Ningjin Thermoelectricity Co., Ning Jin County, China
Bibliografia
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
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