Probabilistic Power Flow Prediction of Microgrid Comprising Wind and Photovoltaic Generation

DOI

10.2991/ceis-16.2016.110How to use a DOI?

Keywords

micro-grid; probabilistic power flow; conditional joint probability prediction; probabilistic interval

Abstract

The power flow of micro-grid containing wind-light complementary system shows greater uncertainty due to it is affected by wind speed and irradiance. Therefore the prediction of probabilistic power flow is of great significance for micro-grid energy management. In the paper, on the basis of wind power and photovoltaic power prediction, a conditional joint probability prediction technique is put forward to predict probabilistic power flow considering the correlation between wind and irradiance. The prediction technique is not only consider the affection that wind speed and irradiance put on the power flow, but also consider the co-constrains between wind speed intervals and irradiance intervals at the prediction moment. The simulation results show that the probabilistic intervals achieved by the proposed prediction methods are narrower than unconditional joint probability prediction technique and of more reference value.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Song-Lin Zhou
AU  - Zeng-Liang Liu
PY  - 2016/11
DA  - 2016/11
TI  - Probabilistic Power Flow Prediction of Microgrid Comprising Wind and Photovoltaic Generation
BT  - Proceedings of the 2016 International Conference on Computer Engineering and Information Systems
PB  - Atlantis Press
SP  - 539
EP  - 544
SN  - 2352-538X
UR  - https://doi.org/10.2991/ceis-16.2016.110
DO  - 10.2991/ceis-16.2016.110
ID  - Zhou2016/11
ER  -