Measurement of synchronous machine parameters using Kalman filter based fuzzy logic estimator H.M. Al-Hamadi a,⇑ , K.M. EL-Naggar b a Information Science Department, CFW, Kuwait University, Odyliyah Campus, PO Box 5969, Safat 13060, Kuwait b Electrical Engineering Department, College of Technological Studies, PO Box 42325, Shuwaikh 70654, Kuwait article info Article history: Received 6 November 2009 Received in revised form 11 April 2010 Accepted 23 July 2010 Available online 1 August 2010 Keywords: Estimation Kalman filter Fuzzy logic Synchronous machine parameters Short circuit test abstract This paper presents a new Kalman filter/fuzzy logic approach for estimating synchronous machine parameters from short circuit tests. The technique uses on-line noisy measure- ments of the short circuit current for estimating direct axis reactances, and time constant synchronous machine parameters. The approach is based on expressing short circuit cur- rent as a discrete time linear dynamic system model suitable for the Kalman filter to esti- mate the parameters. Fuzzy rule-based logic is used to tune-up measurement noise levels by adjusting the covariance matrix. The results show a better convergence using fuzzy logic than those solely using the Kalman filter. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction Synchronous machines play a very important role in the stability of power systems. A proper model for synchro- nous machines is essential for a valid analysis of stability and dynamic performance. The subject of estimating syn- chronous machine parameters is still a challenging and attractive research topic. Various studies on the ever- increasing size and complexity of power systems show the need for more accurate model parameters of synchro- nous machines. Therefore, it is very important to have fast and accurate algorithms for the identification of synchro- nous machine parameters. Many traditional methods have been proposed and implemented to estimate synchronous machine parameters. Some of these techniques are based on data obtained from frequency tests [1]; others are based on time domain data obtained from short circuit tests [2]. However, most of these techniques are constructed under off-line conditions. Ref. [3], presents an off-line method based on the least er- ror squares estimation technique to estimate the parame- ters of an in lab small synchronous machine using the responses of three-phase short circuit transients. The least squares error technique has many advantages over other methods, but its results have poor accuracy when the mea- surement set is contaminated with bad data. Many researchers have addressed the issues and problems associ- ated with off-line parameter measurements; this has in- creased the interest and need for on-line estimation of synchronous generator parameters in recent years. On-line methods of obtaining machine parameters are the most attractive due to a minimal site/system impact and because they do not involve service interruption. Furthermore, this class of methods represents a way to taking parameter devi- ation due to changes in load levels, saturation, and machine aging into account. On-line methods have been studied by many researchers [4–13]. Most of these studies are con- ducted mainly on conventional frame of reference models of synchronous generators. On-line methods are also sug- gested in many references. In 1981, Mainba used the Kalman filter to estimate the transfer function of an on-line synchro- nous machine in a local power network [4]. Refs. [5,6] 0263-2241/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.measurement.2010.07.012 ⇑ Corresponding author. Tel.: +965 97471047. E-mail addresses: helal3113@hotmail.com (H.M. Al-Hamadi), knag- gar@ieee.orgm (K.M. EL-Naggar). Measurement 43 (2010) 1327–1335 Contents lists available at ScienceDirect Measurement journal homepage: www.elsevier.com/locate/measurement