[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Social Network Membership
Linkedin
Researchgate
..
Indexing Databases
..
DOI
کلیک کنید
..
ِDOR
..
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 12, Issue 4 (12-2023) ::
ieijqp 2023, 12(4): 28-36 Back to browse issues page
Inertia Constant and damping coefficient estimation in multi-area interconnected power systems
Aref Doroudi * 1, Yaser Erfaghi
1- Shahed Univversity
Abstract:   (640 Views)

The inertia constant, a key parameter that makes power systems robust to disturbances and disruptions, has today been changed by factors such as the influence of renewable generation units and the reduction of traditional synchronous generators. Changes in the inertia of a power network play an important role in its performance, and a lack of knowledge of its status will have severe consequences for the network's online protection and control systems. Hence, knowledge of its online changes is essential for transmission system operators. This paper presents an online inertia estimation method that is based on inter-area electromechanical oscillations and simultaneously estimates the network inertia constant and the system damping coefficient. Unlike the previous methods that have used the flow of active power between two areas, the oscillation parameters are extracted from the voltage angle of the buses, improving the accuracy of the estimate. For this purpose and based on the classical swing equation, the relationship between the inertia constant of the system and the electromechanical oscillation parameters is first determined by the Prony technique. Then, the network equivalent inertia and damping coefficient are estimated. The efficiency and accuracy of the proposed method are verified by DigiSilent and MATLAB software and in several scenarios implemented on the IEEE 39-bus standard network. The simulation results show the appropriate accuracy of the proposed method. It is shown that the results of estimating the inertia and damping coefficient based on the active power signal have an average error percentage of 10 and 17.32, respectively. After using the voltage angle signal, the results are improved to 9.03 and 11.94, respectively. Due to the simplicity and small burden of calculations, the presented method can be easily used by network operators.
 

Keywords: Inertia constant, Power system reduction, Damping coefficient, Electromechanical oscillations. Prony method
Full-Text [PDF 1552 kb]   (231 Downloads)    
Type of Study: Research |
Received: 2022/12/17 | Accepted: 2023/12/11 | Published: 2023/12/23
References
1. [1] D. Linaro, F. Bizzarri, D. del Giudice, C. Pisani, G. M. Giannuzzi, S. Grillo, and A. M. Brambilla, "Continuous estimation of power system inertia using convolutional neural networks", Nature Communications, 14 (1), 2023. [DOI:10.1038/s41467-023-40192-2]
2. [2] Y. Bian, H. Wyman-Pain, F. Li, R. Bhakar, S. Mishra, and N. P. Padhy, "Demand side contributions for system inertia in the GB power system," IEEE Trans. Power Syst., vol. 33, no. 4, pp. 3521-3530, 2017. [DOI:10.1109/TPWRS.2017.2773531]
3. [3] D. Linaro, et.al, "Continuous estimation of power system inertia using convolutional neural networks", Nature Communications, 14 (1), 2023. [DOI:10.1038/s41467-023-40192-2]
4. [4] B. Wang, D. Yang, G. Cai, J. Ma, Z. Chen, and L. Wang, "Online inertia estimation using electromechanical oscillation modal extracted from synchronized ambient data," J. Mod. Power Syst. Clean Energy, 2020.
5. [5] R. K. Panda, A. Mohapatra, and S. C. Srivastava, "Online estimation of system inertia in a power network utilizing synchrophasor measurements," IEEE Trans. Power Syst., vol. 35, no. 4, pp. 3122-3132, 2019. [DOI:10.1109/TPWRS.2019.2958603]
6. [6] K. Tuttelberg, J. Kilter, D. Wilson, and K. Uhlen, "Estimation of power system inertia from ambient wide area measurements," IEEE Trans. Power Syst., vol. 33, no. 6, pp. 7249-7257, 2018. [DOI:10.1109/TPWRS.2018.2843381]
7. [7] R. K. Panda, A. Mohapatra, and S. C. Srivastava, "Application of indirect adaptive control philosophy for inertia estimation," in 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia), pp. 478-483, 2019. [DOI:10.1109/GTDAsia.2019.8715940]
8. [8] P. Du and J. Matevosyan, "Forecast system inertia condition and its impact to integrate more renewables," IEEE Trans. Smart Grid, vol. 9, no. 2, pp. 1531-1533, 2017. [DOI:10.1109/TSG.2017.2662318]
9. [9] J. Schiffer, P. Aristidou, and R. Ortega, "Online estimation of power system inertia using dynamic regressor extension and mixing," IEEE Trans. Power Syst., vol. 34, no. 6, pp. 4993-5001, 2019. [DOI:10.1109/TPWRS.2019.2915249]
10. [10] K. Prabhakar, S. K. Jain and P. K. Padhy,"Inertia estimation in modern power system: A comprehensive review", Electric Power Systems Research, Volume 211, October 2022. [DOI:10.1016/j.epsr.2022.108222]
11. [11] P. S. Kundur and O. P. Malik, Power system stability and control. McGraw-Hill Education, 2022.
12. [12] M. Jan-E-Alam, "A Study on the Presence of Inter-Area Oscillation Mode in Bangladesh Power System Network," J. Electr. Eng., vol. 36, no. 2, pp. 16-21, 2009.
13. [13] L. Mariotto, H. Pinheiro, G. Cardoso, A. P. Morais, and M. R. Muraro, "Power systems transient stability indices: an algorithm based on equivalent clusters of coherent generators," IET Gener. Transm. Distrib., vol. 4, no. 11, pp. 1223-1235, 2010. [DOI:10.1049/iet-gtd.2009.0647]
14. [14] T. L. Baldwin, L. Mili, and A. G. Phadke, "Dynamic ward equivalents for transient stability analysis," IEEE Trans. Power Syst., vol. 9, no. 1, pp. 59-67, 1994. [DOI:10.1109/59.317557]
15. [15] J.F. Hauer, C.J. Demeure, and L.L. Scharf, Comparison of Prony and eigenvalues analysis for power system control design, IEEE Trans. Power Systems 8 (3), p.p. 964- 971, 1993. [DOI:10.1109/59.260905]
16. [16] T. Mohamed, M. M. Kezunovic, Z. Obradovic, Y. Hu and Z. Cheng, "Application of Machine Learning to Oscillation Detection using PMU Data based on Prony Analysis", IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Serbia, 2022. [DOI:10.1109/ISGT-Europe54678.2022.9960589]
17. [17] P. Ray, "Power system low frequency oscillation mode estimation using wide area measurement systems," Eng. Sci. Technol. an Int. J., vol. 20, no. 2, pp. 598-615, 2017. [DOI:10.1016/j.jestch.2016.11.019]
18. [18] G. Cai, B. Wang, D. Yang, Z. Sun, and L. Wang, "Inertia estimation based on observed electromechanical oscillation response for power systems," IEEE Trans. Power Syst., vol. 34, no. 6, pp. 4291-4299, 2019. [DOI:10.1109/TPWRS.2019.2914356]


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Doroudi A, Erfaghi Y. Inertia Constant and damping coefficient estimation in multi-area interconnected power systems. ieijqp 2023; 12 (4) :28-36
URL: http://ieijqp.ir/article-1-944-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 12, Issue 4 (12-2023) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
Persian site map - English site map - Created in 0.06 seconds with 40 queries by YEKTAWEB 4660