An Analytical Method for Probabilistic Modeling of the Steady-State Behavior of Secondary Residential System

作者：Ding Tianyu^*; Liang Hao; Xu Wilsun

来源：IEEE Transactions on Smart Grid, 2017, 8(6): 2575-2584.

DOI：10.1109/TSG.2016.2530630

• Probabilistic modeling
• residential loads
• semiMarkov process
• unscented transformation

Effective modeling of secondary residential system is critical for numerous demand side innovations in smart grid, such as distributed generation and energy storage integration, residential micro-grid operation, and demand response programs. Traditionally, Monte Carlo simulation (MCS) method is used to establish the model by capturing the random usage patterns of home appliances. Yet, the computational effort is tremendous, especially for a large group of residential loads. To address this issue, an analytical method is proposed in this paper. The result is a time varying probabilistic steady-state equivalent circuit model whose parameters are characterized by means and covariance matrices. The proposed method consists of three main components with regard to the derivation of state probability distributions for individual appliances, modeling of aggregated secondary feeder with all appliances, and unscented transformation to combine the aggregated secondary feeder model and service transformer model. The effectiveness and efficiency of the proposed method are evaluated based on extensive numerical results and by comparing the results with that obtained by MCS method.

• 出版日期2017-11