Research on Adaptive Interactive Multi-model Load Modeling Algorithm Based on Improved Transition Probability

• Published in: 2019 IEEE Sustainable Power and Energy Conference (iSPEC) pp. 1118 - 1122
• Main Authors: Sun, Tiantian, Wang, Zhenshu, Yin, Qingqing, Li, Wenqiao, Chong, Fayu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2019
• Subjects: Adaptive Interacting Multiple Model algorithm; Load modeling; Markov transition probability matrix; tracking accuracy
• DOI: 10.1109/iSPEC48194.2019.8975296

Power load is an important part of the power system and plays an important role in the safe and stable operation of the power system. However, with the continuous development of the power grid, the power load is subject to time-varying, complexity and distribution problems in actual operation. At the same time, when the load is subject to large disturbance or characteristic fluctuation, the modeling algorithm based on the fixed transition probability matrix will further lead to slow model switching and reduced tracking accuracy.In order to solve this problem, this paper applies the adaptive transition probability algorithm in the target tracking domain to load modeling, and an adaptive interactive multimodel load modeling algorithm based on improved Markov transition probability is established and verified by Matlab simulation. The improved algorithm improves the tracking accuracy of the traditional load modeling algorithm and can accurately describe the characteristics of the load model, which provides a new direction for the research of load modeling.