A Probabilistic Harmonic State Estimation Method for Distribution Network Connected by Wind Power

The classical harmonic state estimation model is no longer applicable in the wind power connected power system. On the one hand, the violent fluctuation characteristics of harmonics make it difficult to accurately estimate the harmonic. On the other hand, the estimated result at a single moment can not represent the level of violently fluctuating harmonics. A method employing both semi-invariant and the least squares method is proposed to estimate the harmonic under the condition of distributed wind power access to distribution network. Firstly, semi-invariant is used to convert the estimation of the harmonic current at each moment into the estimation of the semi-invariant of the harmonic current at a large number of moments. The least squares method is used to estimate the half-invariant of harmonic currents. The Gram-Charlier series are used to calculate the probability density and probabilistic characteristic quantities of harmonic currents based on the half-invariant. Simulation results on the IEEE 13-bus test system show that the probability harmonic state estimation method can adapt to the randomness and intermittency of the harmonics injected by the grid-connected wind farm, and effectively estimate the probability distribution and probability eigenvalue of the harmonic current.