A Probabilistic Load Flow Method based on Improved Point Estimate and Maximum Entropy

New devices such as wind turbine and photovoltaic connecting to the power grid brings uncertain features to the modern power system. The uncertain factors have a significant impact on the operating state and harmonic level of power system. To analyze the influence of the uncertain factors, a novel probabilistic power flow method combined the improved point estimate and maximum entropy theory is proposed in this paper. To relieve the calculation burden, the estimated points are first calculated in the standard normal distribution space. Through the transformation from standard normal probability distribution space to the original probability distribution space, the raw moments can be easily calculated. Then according to the raw moments of output variables, the probability distribution of output variables can be reconstructed through maximum entropy theory. The proposed method can effectively analyze the fundamental and harmonic state of the power system. The superiority of the proposed method is validated by the simulation with the IEEE 33 bus distribution system.