A methodology for equivalent modeling of distribution system based on nonlinear model reduction. (December 2016)

• Record Type: Journal Article
• Authors: Zhang, Gang; Du, Zhengchun; Li, Chongtao; Ni, Yu; Wang, Cong
• Is Part Of: International journal of electrical power & energy systems. Volume 83(2016:Dec.)
• Page Start: 203
• Page End: 212
• Publication Date: 2016-12
• Subjects: Load modeling -- Distribution system -- Nonlinear model reduction -- Covariance matrix -- Dynamic model; 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.2016.04.015
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: The lower-order equivalent model is obtained based on the dynamic model of distribution system. The distribution network is directly considered. Covariance matrix based nonlinear model reduction technique is adopted to obtain the lower-order equivalent model. The computation procedure only requires matrix computations. Abstract: This paper presents a new method to construct the low-order equivalent model for distribution system, which is very essential in large power system simulations. The distribution system connected to a substation is seen from the transmission power system as a nonlinear input–output system. In order to cope with the computation complexity, nonlinear model reduction technique based on covariance matrix is employed to obtain a new low-order dynamic system, which can closely represent the dynamic characteristics of the detailed system. The absence of drastic simplifications, direct consideration of the distribution network and the proper preservation of the input–output behavior of the detailed distribution system allow the equivalent model to attain good accuracy. Simulations and analysis are carried out on WSCC system to verify the validity of the proposed method. The simulation results show that this new method could attain high accuracy of simulation of distribution system under various operating conditions, thus improving the precision of power system stability analysis.