Performance comparison of static and dynamic state estimators for electric distribution systems

Ahmad, Fiaz and Rashid, Muhammad and Rasool, Akhtar and Özsoy, Emre and Şabanoviç, Asif and Elitaş, Meltem (2017) Performance comparison of static and dynamic state estimators for electric distribution systems. International Journal of Emerging Electric Power Systems, 18 (3). ISSN 1553-779X

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Official URL: http://dx.doi.org/10.1515/ijeeps-2016-0299


State estimation is an integral component of energy management systems used for the monitoring and control of operation of transmission networks worldwide. However, it has so far not yet been widely adopted in the distribution networks due to their passive nature with no active generation. But this scenario is challenged by the integration of distributed generators (DGs) at this level. Various static and dynamic state estimators have been researched for the transmission systems. These cannot be directly applied to the distribution systems due to their different philosophy of operation. Thus the performance of these estimators need to be re-evaluated for the distribution systems. This paper presents a computational and statistical performance of famous static estimator such as weighted least squares (WLS) and dynamic state estimators such as extended Kalman filter (EKF) and unscented Kalman filter (UKF) for electric distribution system. Additionally, an improved-UKF (IUKF) is also proposed which enhances the robustness and numerical stability of the existing UKF algorithm. All the estimators are tested for load variation and bad data for IEEE-30, 33 and 69 bus radial distribution networks using statistical performance metrics such as Maximum Absolute Deviation (MAD), Maximum Absolute Percent Error (MAPE), Root Mean Square Error (RMSE) and Overall Performance index (J). Based on these metrics, IUKF outperforms other estimators under the simulated noisy measurement conditions.

Item Type:Article
Uncontrolled Keywords:distribution system state estimation; static state estimation and dynamic state estimation; weighted least squares; Extended Kalman filter; unscented Kalman filter and improved unscented Kalman filter
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1-4661 Electrical engineering. Electronics Nuclear engineering
ID Code:32542
Deposited By:Asif Şabanoviç
Deposited On:04 Aug 2017 11:01
Last Modified:04 Aug 2017 11:01

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