Input interaction and output fusion of adaptive interacting multiple load modeling. (May 2020)

• Record Type: Journal Article
• Authors: Bian, Shaorun; Wang, Zhenshu; Ji, Na; Chu, Xiaodong; Du, Zixuan; Yin, Qingqing
• Is Part Of: International journal of electrical power & energy systems. Volume 117(2020)
• Publication Date: 2020-05
• Subjects: Adaptive interacting multiple load modeling -- Load modeling -- Input interaction -- State estimation -- Output fusion; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2019.105674
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A framework of the AIMLM method is established in this paper. Input interaction is used to exchange information among optimal load models. Output fusion is used to generate a synthetic load model [1] . Abstract: Accurate load modeling with fluctuating loads has been one of the most challenging problems in power system. Input interaction and output fusion of the adaptive interacting multiple load modeling (AIMLM) method is introduced in this paper. Different load models switch through a Markov probability transfer matrix and filter in parallel through the extended Kalman filters (EKF). After the state estimation, model probabilities are updated according to the evaluated errors. Finally, load models are fused and output based on the probabilities, thus generating a synthetic load model. Simulation results show that interaction and output fusion of the AIMLM method are of high accuracy and can effectively solve the time-varying problem of load characteristics.