Hybrid solar irradiance now-casting by fusing Kalman filter and regressor

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/106863

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106863

Title:	Hybrid solar irradiance now-casting by fusing Kalman filter and regressor
Authors:	鄭旭詠;Cheng, Hsu-Yung
Contributors:	資訊電機學院資訊工程學系
Keywords:	data collection;Fuses;Irradiance;Kalman filter;Kalman filters;Mathematical analysis;Mathematical models;Mean square values;Prediction;Regression;Renewable energy;renewable energy sources;Roots;Solar irradiance;solar radiation
Date:	2016-06-01
Issue Date:	2026-04-23 13:47:00 (UTC+8)
Publisher:	Elsevier BV;Elsevier Ltd
Abstract:	摘要： In this work, a hybrid solar irradiance now-casting mechanism is proposed. The proposed hybrid predictor fuses the results from both Kalman filter predictor and regressor predictor to benefit from the advantages of both techniques. A time-varying adaptive system function for Kalman filter is designed to deal with ramp-down events for more accurate prediction. Three fusion alternatives based on local root mean square error computation are proposed and compared. The experimental results have validated the effectiveness of the proposed method on a challenging dataset. •The proposed hybrid predictor fuses a Kalman filter predictor and a regressor predictor.•A time-varying adaptive system function for Kalman filter is designed.•Two fusion alternatives based on local root mean square error are proposed and compared.•When the local RMSE of Kalman filter is larger than a threshold, the prediction result from the regressor predictor is chosen. 出版者： Elsevier Ltd 出版日期： 2016-06-01 出處： Renewable Energy, 2016-06, Vol.91, p.434-441 版權： 2016 Elsevier Ltd 識別號： ISSN: 0960-1481 識別號： EISSN: 1879-0682 識別號： DOI: 10.1016/j.renene.2016.01.077
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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