Probability analysis method for low-voltage distribution network line loss considering the randomness of electric power and quantity

The probabilistic analysis method for theoretical line loss rates can reflect the impact of random changes in source and load power on the line loss rates. However, current research primarily focuses on three-phase symmetric transmission grids and medium-voltage distribution networks, whereas the random quantities and disturbance characteristics of low-voltage distribution networks exhibit significant differences. Therefore, a probabilistic analysis method for low-voltage distribution network line loss that considers the randomness of electric power and quantity has been proposed. Firstly, the three-phase daily power curves for the source and load over several months are normalized and clustered to form expected curves and random variables for prediction errors. Secondly, the Spearman correlation coefficient for the daily electricity consumption of the source and load is calculated. Following that, a probability distribution model for the daily electricity consumption, power prediction errors, and the three-phase voltages on the low-voltage side at various times for the distribution transformer is established based on the diffusion kernel density estimation method. Then, considering the correlation of disturbances among random variables, the Latin hypercube sampling method is utilized to efficiently sample the random variables. Finally, by simulating random samples, applying a daily power curve shape correction strategy, and performing three-phase power flow calculations, an efficient assessment of the probability distribution of the daily theoretical line loss rates for the low-voltage distribution network is achieved. The effectiveness of the proposed method has been verified through simulation analysis.