TY - GEN
T1 - An Enhanced Probabilistic Power Flow Method for Correlation Mining of Voltages and Transmission Powers Considering Correlated Wind Sources
AU - Zhou, Baorong
AU - Lin, Chaofan
AU - Wang, Tong
AU - Wang, Haoyuan
AU - Wang, Tao
AU - Bie, Zhaohong
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - As increasing penetration of renewable energy, the unpredictable randomness and variability of generation pose challenges to power system planning and operation. Probabilistic power flow (PPF) is emerging as a valid method to deal with uncertainty of generation outputs. However, the conventional PPF methods considering correlated generations can only derive the probability distribution of single node voltage or transmission line power, failing to cover the correlation between multiple voltages and powers, which is also significant in power flow analysis. To address the problem, this paper proposed an enhanced cumulant-based probabilistic power flow method for correlation mining in order to obtain more detailed probability characteristics of node voltages and transmission powers. Test results showed that the proposed method performed better than common PPF methods in combined or conditional events analysis, thus is more practical for operation analysis and decision making.
AB - As increasing penetration of renewable energy, the unpredictable randomness and variability of generation pose challenges to power system planning and operation. Probabilistic power flow (PPF) is emerging as a valid method to deal with uncertainty of generation outputs. However, the conventional PPF methods considering correlated generations can only derive the probability distribution of single node voltage or transmission line power, failing to cover the correlation between multiple voltages and powers, which is also significant in power flow analysis. To address the problem, this paper proposed an enhanced cumulant-based probabilistic power flow method for correlation mining in order to obtain more detailed probability characteristics of node voltages and transmission powers. Test results showed that the proposed method performed better than common PPF methods in combined or conditional events analysis, thus is more practical for operation analysis and decision making.
KW - Copula function
KW - Correlation Mining
KW - Cumulant Method
KW - Probabilistic Power Flow
UR - https://www.scopus.com/pages/publications/85061700899
U2 - 10.1109/POWERCON.2018.8602180
DO - 10.1109/POWERCON.2018.8602180
M3 - 会议稿件
AN - SCOPUS:85061700899
T3 - 2018 International Conference on Power System Technology, POWERCON 2018 - Proceedings
SP - 2170
EP - 2176
BT - 2018 International Conference on Power System Technology, POWERCON 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 International Conference on Power System Technology, POWERCON 2018
Y2 - 6 November 2018 through 9 November 2018
ER -
