Optimal number and location of measurement instruments in distributed systems for Harmonic State Estimation

• Autorzy: Muscas C. , Pilo F. , Pisano G. , Sulis S.
• Języki publikacji: EN

Abstrakty

EN

The recent studies about the attribution of the responsibilities for harmonic distortion in electric distribution systems show that the most promising approaches are based on measurement data acquired simultaneously in different nodes of the network. Therefore, distributed measurement systems are needed. For economic reasons, only a small part of network nodes can be equipped with measurement instruments, whereas the information about the overall status of the electric system has to be evaluated by means of suitable Harmonic State Estimation (HSE) techniques. This paper deals with the problem of choosing the optimal number and position of measurement devices, in order to ensure that the HSE algorithms can provide, at the lowest possible cost, results having a prefixed level of accuracy. An optimization algorithm based on the techniques of the dynamic programming is proposed and the way to take into account the uncertainty introduced by all the elements of the measurement system is discussed. Simulation results on a benchmark distribution network show the validity of the proposed approach.

• Wydawca: AGH University of Science and Technology ; Lodz University of Technology
• Czasopismo: Electrical Power Quality and Utilisation. Journal
• Rocznik: 2007
• Tom: Vol. 13, nr 1
• Strony: 75--81
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Muscas C.

autor

Pilo F.

autor

Pisano G.

autor

Sulis S.

• Dipartimento di Ingegneria Elettrica ed Elettronica, University of Cagliari, Italy,

Bibliografia

• 1. R e n s A . P . J . , S w a r t P . H . : On techniques for the localization of multiple distortion sources in three-phase networks: time-domain verification. ETEP, Vol. 11, No. 5, 2001, pp. 317-322.
• 2. Mu s c a s C . : Assessment of electric power quality: indices for identifying disturbing loads. ETEP European Transactions on Electrical Power, vol. 8, n.4, 1998, pp. 287-292.
• 3. D a v i s E . J . , E m a n u e l A . E . , P i l e g g i D . J . : Harmonic pollution metering: theoretical considerations. IEEE Transactions on Power Delivery, vol. 15, n. 1, 2000, pp. 19-23.
• 4. C a s t a l d o D. , Te s t a A. , F e r r e r o A. , S a l i c o n e S . : An Index for Assessing the Responsibility for Injecting Periodic Disturbances. L’Energia Elettrica, Volume 81, Supplement to N. 5-6 September/December 2004, pp. 134-143.
• 5. L o c c i N . , M u s c a s C . , S u l i s S .: Multi-point measurement techniques for harmonic pollution monitoring: a comparative analysis. L’Energia Elettrica, Volume 81, Supplement to N. 5-6 September/December 2004, pp. 129-133.
• 6. L o c c i N . , Mu s c a s C . , S u l i s S . : Investigation on the accuracy of harmonic pollution metering techniques. IEEE Transactions on Instrumentation and Measurement, Vol. 53, No. 4, August 2004, pp. 1140-1145.
• 7. Me l i o p o u l o s A . P. S . , F a n Z h a n g , Z e l i n g h e r S . : Power system harmonic state estimation. IEEE Transactions on Power Delivery, Vol. 9, N. 3, July 1994, pp. 1701-1709.
• 8. Wa t s o n N . R . , A r r i l l a g a J . , D u Z . P.: Modified symbolic observability for harmonic state estimation. IEE Proceedings on Generation, Transmission and Distribution, Vol. 147, N. 2, March 2000, pp. 105-111.
• 9. Ma t a i r S . S . , Wa t s o n N . R . , Wo n g K . P. , P h a m V. L . , A r r i l l a g a J . : Harmonic state estimation: a metod for remote harmonic assessment in a deregulated utility network. DRPT 2000 - International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, 4-7 April 2000, pp. 41-46.
• 10. Yu K . K . C . , Wa t s o n N . R . : Three-phase harmonic state estimation using SVD for partially observable systems. PowerCon 2004 - International Conference on Power System Technology, 21-24 November 2004, Vol. 1, pp. 29-34.
• 11. M a d t h a r a d C . , P r e m r u d e e p r e e c h a c h a r n S . , Wa t s o n N . R . , R a t c h a i S a e n g - U d o m : An optima measurement placement method for power system harmonic state estimation. IEEE Transactions on Power Delivery, Vol. 20, N. 2, Part 2, April 2005, pp. 1514-1521.
• 12. L a r s o n R . E . , C o s t i J . L . : Principles of Dynamic Programming. M. Decker, New York, 1978-1982.
• 13. Guide to the expression of uncertainty in measurement, ISO, 1995.
• 14. ISO Guide to the expression of uncertainty in measurement - Supplement 1 – Numerical methods for the propagation of distributions. Draft document, 2004.
• 15. G h i a n i E . , L o c c i N . , M u s c a s C . : Evaluation of uncertainty in measurements based on digitized data. Measurement, Volume 32, N. 4, December 2002, pp. 265-272.
• 16. S a s d e l l i R. , Mu s c a s C. , P e r e t t o L . , T i n a r e l l i R. : On the characterization of voltage and current transducers In steady-state distorted conditions. ETEP European Transactions on Electrical Power, vol. 11, n. 6, November/December 2001.
• 17. G h i a n i E . , L o c c i N . , M u s c a s C . , S u l i s S .: Uncertainty estimation for DSP-based power quality measurements. COMPEL (The International Journal for Computation and Mathematics in Electrical and Electronic Engineering), Vol. 23 No. 1, 2004, pp. 92-103.
• 18. Mu s c a s C . , P i l o F. , P i s a n o G . , S u l i s S . : Optimal Placement of Measurement Devices in Electric Distribution Systems. IEEE IMTC/2006, Sorrento (Italy), 24-27 Aprile 2006, pp. 1873-1878.
• 19. G r a d y W. M . , S a m o t y j M . J . , N o y o l a A . H .: Minimizing network harmonic voltage distortion with an active power line conditioner. IEEE Transactions on Power Delivery, Vol. 6, N. 4, October 1991, pp. 1690-1697.
• 20. C a r p i n e l l i G . , R u s s o A . , R u s s o M. , Ve r d e P.: Inherent structure theory of networks and power system harmonics. IEE Proceedings on Generation, Transmission and Distribution, Vol. 145, N 2, March 1998, pp. 123-132.
• 21. C e l l i G . , P i l o F . , P i s a n o G . : Meshed Distribution Networks to increase the maximum allowable Distributed Generation capacity. In Proc. of Symposium CIGRE on „Power Systems with Dispersed Generation”, Athens (Greece), 13-16 April, 2005.