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| An Error Prediction Method of Model Order Reduction for Multi-Time Scale Linear System |
| Kang Jun, Ma Fan, Hu Jian, Sun Wen, Xiong Youxing |
| National Key Laboratory of Science and Technology on Vessel Integrated Power System National University of Engineering Wuhan 430033 China |
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Abstract The conventional methods of order reduction model for linear system cannot predict the time domain error of dynamic behaviors of state variables between the original and reduced models, so the reduced models derived by conventional methods maybe not suitable for analyzing the system performances because of the large variation between the reduction model and origin model. To solve this problem, this paper has proposed a L2 norm-based error prediction method for error prediction which is based on the conventional singular perturbation model order reduction method. The relative error calculation formula of the dynamic characteristic of the system state variable is deduced which ignore the variation caused by fast dynamic and fixed slow dynamic reduction. Then, the multi-time scale mathematical models of an AC system powered by one generator and a model of a DC system powered by three generators are built. They are reduced and the consequent errors are predicted. The simulation results demonstrate the effectiveness and accuracy of the proposed method.
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Received: 06 January 2016
Published: 27 February 2017
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2017, Vol. 32 
