An Enhanced Probabilistic Power Flow Method for Correlation Mining of Voltages and Transmission Powers Considering Correlated Wind Sources

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.