Research on Prediction of Distributed Photovoltaic Output Considering Spatial Relevance

doi:10.3969/j.issn.1000－7229.2020.03.006

Abstract

Abstract: With the increasing proportion of distributed photovoltaic （DPV） power in distribution network， the fluctuation of its power output will become a non-negligible uncertain factor in power grid dispatch and operation. On the basis of the correlation of photovoltaic power generation in one region， a prediction method for distributed photovoltaic output is proposed on the basis of spatial correlation. Firstly， the historical data of centralized and distributed photovoltaic output in the same region are normalized to uncovered coefficient which represents the randomness of photovoltaic output. Then， the weather conditions are classified by K-means clustering. According to Copula theory， the correlation model of photovoltaic output under various weather conditions is established. Finally， the distributed photovoltaic output is predicted according to the information of centralized photovoltaic output. The validity of the proposed method is verified by using an example of a photovoltaic power station in a city of northern China.

Key words: distributed photovoltaic, output prediction, spatial relevance, Copula

CLC Number:

TM 615

ZHANG Jiaan， WANG Kunyue， CHEN Jian， GUO Lingxu， HUANG Xiaoxiao,FAN Ruiqing， LI Zhijun. Research on Prediction of Distributed Photovoltaic Output Considering Spatial Relevance[J]. Electric Power Construction, 2020, 41(3): 47-53.

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