A hybrid forecasting method for wind power ramp based on Orthogonal Test and Support Vector Machine (OT-SVM)
Liu, Yonqian and Sun, Ying and Infield, David and Zhao, Yu and Han, Shuang and Yan, Jie (2017) A hybrid forecasting method for wind power ramp based on Orthogonal Test and Support Vector Machine (OT-SVM). IEEE Transactions on Sustainable Energy, 8 (2). pp. 451-457. ISSN 1949-3037 (https://doi.org/10.1109/TSTE.2016.2604852)
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Abstract
In an electric power system with a high penetration of wind power, incoming power ramps pose a serious threat to the power system. To adopt suitable response strategies for wind power ramps, it is important to predict them accurately and in a timely manner. Since power ramps are caused by various factors, their occurrence have irregular characteristics and vary by location, bringing great difficulty in forecasting. To solve this problem, a hybrid forecasting model OT-SVM (Orthogonal Test and Support Vector Machine) was developed in this paper, which combines an orthogonal test with a support vector machine. A novel factor analysis method was established based on the theory of the orthogonal test (OT), and applied to determine the optimal inputs of a support vector machine (SVM). The effectiveness of OT-SVM was tested with three wind farms in China, while comparing the results with other related methods. The results show that the proposed OT-SVM has the highest accuracy covering different input numbers and time resolutions. In addition, a novel evaluation index MAI (Mean Accuracy Index) was proposed, considering both the missed ramps and false ramps, which can be used as a supplementary index for CSI.
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Item type: Article ID code: 57940 Dates: DateEventApril 2017Published31 August 2016Published Online30 August 2016AcceptedNotes: (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Technology > Engineering (General). Civil engineering (General) > Environmental engineeringDepartment: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 27 Sep 2016 08:55 Last modified: 18 Nov 2024 18:38 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/57940