光伏发电数据挖掘中的跨度选取

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Abstract Particle size and span are two important indicators when analyzing photovoltaic plant’s active power output characteristic. Particle size determines the sampling interval and span determines the time length of data. Under a certain particle size, small span make information be of scarcity and distortion while big span make information be of redundancy and repeatability. Therefore, determining the data span is of great significance to analysis of photovoltaic plant’s output characteristic. In this paper, statistical characteristics of photovoltaic plant’s output is analyzed firstly, autocorrelation analysis gives a preliminary conclusion of determining the data span. With a cluster analysis of output data based on weather features, we use probability and statistics principles to take an optimum sample size estimating for photovoltaic plant’s output data. The data span needed required for analysis of photovoltaic plant’s output data is determined and relation between energy storage system capacity demand and data span is studied. The result shows that photovoltaic plant’s output data span required for deploying energy storage system capacity demand is 31days.

Key words： Data span cluster analysis optimum sample size estimating energy storage system capacity demand

Received: 10 August 2014 Published: 08 September 2015

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TM615

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	Li Jianlin
	Ji Tianming
	Kong Lingda
	Han Xiaojuan

Cite this article:

Li Jianlin,Ji Tianming,Kong Lingda等. Span Determining of Photovoltaic Generation Data Mining[J]. Transactions of China Electrotechnical Society, 2015, 30(14): 450-456.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2015/V30/I14/450

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