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Mathematical Problems in Engineering
Volume 2018, Article ID 9049215, 9 pages
https://doi.org/10.1155/2018/9049215
Research Article

An Evaluation Method of the Photovoltaic Power Prediction Quality

School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China

Correspondence should be addressed to Mao Yang; moc.361@028oamgnay

Received 22 August 2017; Revised 29 December 2017; Accepted 13 February 2018; Published 15 March 2018

Academic Editor: Emilio Turco

Copyright © 2018 Mao Yang and Xin Huang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Photovoltaic (PV) output power has regularity, volatility, and randomness. First of all, this paper carried on a metrological analysis to PV system data. Then, this paper analyzed the relationship between PV historical data, PV power forecasting model, and forecast error. By spectrum analysis of PV power, the PV power is decomposed into periodic components, low frequency residual components, and high frequency residual components. Making a specific analysis of these three components determines the minimum modeling error value, which reflects the unpredictable part of the PV power. Determining the minimum modeling error for PV forecasting not only objectively evaluates the quality of the PV forecasting model but also can determine the prediction accuracy standard according to different PV power generation targets. The examples given in this paper illustrate the effectiveness of the method.