Short-term photovoltaic prediction by using H∞ filtering and clustering

Yasuhiko Hosoda, Toru Namerikawa
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引用次数: 16

Abstract

This paper deals with prediction algorithm applying for photovoltaic (PV) systems in smart grid. This prediction is aim to predict the amount of the next day of generation using the previous data and the weather forecast which get from Japan Meteorological Agency. The procedure of prediction consists of two steps, the data processing and the unknown parameters estimation. In the data processing, our proposed method considers the characteristics of PV generation using cluster ensemble. We propose the cluster ensemble based on k-means to choose the groups with a correlation with previous data. In the unknown parameters estimation, we provide the regression model for PV generation and the unknown parameters are estimated via H∞ filtering. The effectiveness of the proposed prediction method is demonstrated through numerical simulations.
基于H∞滤波和聚类的光伏短期预测
本文研究了智能电网中光伏系统的预测算法。本次预报的目的是利用日本气象厅提供的前期数据和天气预报来预测第二天的发电量。预测过程包括数据处理和未知参数估计两个步骤。在数据处理中,我们提出的方法考虑了使用集群集成的光伏发电的特点。我们提出了基于k-means的聚类集成来选择与先前数据相关的组。在未知参数估计中,我们给出了PV发电的回归模型,并通过H∞滤波估计未知参数。通过数值模拟验证了该预测方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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