DOI:10.1007/s40565-016-0263-y |
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Wind power forecasting errors modelling approach consideringtemporal and spatial dependence |
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Net amount: 1566 |
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Author:
Wei HU1
, Yong MIN1
, Yifan ZHOU1
, Qiuyu LU2
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Author Affiliation:
1.The State Key Lab of Power Systems, Department of
Electrical Engineering, Tsinghua University, Beijing, China
2 Power Dispatch Control Centre of Guangdong Power Grid
Corporation, Guangzhou, China
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Foundation: |
This work was supported by China’s National
High Technology Research and Development Program (No.
2012AA050207), China’s National Nature Science Foundation (No.
51190101) and Science and Technology Projects of the State Grid
Corporation of China (No. SGHN0000DKJS130022). |
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Abstract: |
The uncertainty of wind power forecasting significantly
influences power systems with high percentage
of wind power generation. Despite the wind power forecasting
error causation, the temporal and spatial dependence
of prediction errors has done great influence in
specific applications, such as multistage scheduling and
aggregated wind power integration. In this paper, PairCopula
theory has been introduced to construct a multivariate
model which can fully considers the margin distribution
and stochastic dependence characteristics of wind
power forecasting errors. The characteristics of temporal
and spatial dependence have been modelled, and their
influences on wind power integrations have been analyzed.
Model comparisons indicate that the proposed model can
reveal the essential relationships of wind power forecasting
uncertainty, and describe the various dependences more
accurately. |
Keywords: |
Pair-Copula, Wind power forecasting,
Temporal dependence, Spatial dependence, Wind power
integrations |
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Online Time:2017/05/09 |
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