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논문 기본 정보

자료유형
학술저널
저자정보
Zhouyang Ren (Chongqing University) Wei Yan (Chongqing University) Xia Zhao (Chongqing University) Xueqian Zhao (Beijing Electric Power Research Institute) Juan Yu (Chongqing University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.9 No.2
발행연도
2014.3
수록면
461 - 470 (10page)

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초록· 키워드

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This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

목차

Abstract
1. Introduction
2. Probabilistic Model of PV Generation Considering Correlation
3. Probabilistic Model of Load
4. Probabilistic Power Flow method considering the correlation of PV generation
5. Case Studies
6. Conclusions
References

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UCI(KEPA) : I410-ECN-0101-2015-500-001097187