Dynamic Simulation of Eastern Regional Grid of India using Power System Simulator for Engineering PSS®E
-
Kamaljyoti Gogoi
and
Saibal Chatterjee
Abstract
Eastern Regional (ER) grid of India is one of the five regional grids consisting of voltage level 765 kV, 400 kV, 220 kV and numerous buses at lower voltage range. ER grid is the backbone of the Indian Grid as it is one of the main power generating hubs. Stability of the Indian Grid depends a lot on ER grid as it is the core of the generation and transmission system. For performing stability studies and to determine the weak area of the grid generally L-Index method is used. For detailed analysis like computation of voltage recovery time, maximum frequency deviation and critical clearing time of the buses of the system L-Index method is not suitable. Hence dynamic simulation is performed as it provides options to compute various parameters of ER Grid. The system has been studied using 197 buses of voltage levels 220 kV and above and transmission lines running over a length of 23,693 km. In this paper the power flow modelling, simulation and analysis of the Eastern Grid of India is performed. L-Index algorithm along with dynamic simulation provides the scope of computation of voltage recovery time, maximum frequency deviation and critical clearing time (by introducing an initial transient disturbance) along with the prediction of weak area of the system which gives a complete picture of transient stability of ER Grid.
Funding source: DST FIST
Award Identifier / Grant number: ETI-211_2007
Funding source: NERIST TEQIP-II Project
Acknowledgment
This work has been supported by DST FIST Program project number ETI-211_2007, dated 28-04-2008 and NERIST TEQIP-II Project.
Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: This research was funded by DST FIST under project number ETI-211_2007 and NERIST TEQIP-II Project.
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
Appendix A Supplementary material
The online version of this article offers supplementary material (https://doi.org/10.1515/ijeeps-2019-0209).
References
1. Hines, P, Apt, J, Talukdar, S. Large blackouts in North America: Historical trends and policy implications. Energy Pol 2009;37:5249–59. https://doi.org/10.1016/j.enpol.2009.07.049.Search in Google Scholar
2. Kim, J, Bucklew, JA, Dobson, I. Splitting method for speedy simulation of cascading blackouts. IEEE Trans Power Syst Aug 2013;28:3010–7. https://doi.org/10.1109/tpwrs.2012.2231887.Search in Google Scholar
3. Dobson, I, Carreras, BA, Newman, DE. How many occurrences of rare blackout events are needed to estimate event probability?. IEEE Trans Power Syst Aug 2013;28:3509–10. https://doi.org/10.1109/tpwrs.2013.2242700.Search in Google Scholar
4. Padiyar, KR. HVDC power transmission systems – technology and system interactions. New Delhi: John Wiley & Sons; 1990.Search in Google Scholar
5. Alqueres, JL, Praca, JC. The Brazilian power system and the challenge of the Amazon transmission. In: Proceedings of the 1991 IEEE power engineering society transmission and distribution conference; 1991:315–20 pp.10.1109/TDC.1991.169526Search in Google Scholar
6. Saadat, H. Power system analysis, 13th ed. New Delhi: Tata McGraw Hill Publications; 1999:200–2, 450–60 pp.Search in Google Scholar
7. Kothari, DP, Nagrath, IJ. Modern power system analysis, 4th ed. New Delhi: Tata McGraw Hill Publication:426–9 pp.Search in Google Scholar
8. Kundur, P. Power system stability and control. New York: McGraw-Hill; 1994.Search in Google Scholar
9. Rampurkar, V, Pentayya, P, Mangalvedekar, HV, Kazi, F. Cascading failure for Indian power grid. IEEE Trans Smart Grid 2016;7. https://doi.org/10.1109/tsg.2016.2530679.Search in Google Scholar
10. Hain, Y, Schweitzer, I. Analysis of the power blackout of June 8, 1995 in the Israel electric corporation. IEEE Trans Power Syst Nov 1997;12:1752–8. https://doi.org/10.1109/59.627887.Search in Google Scholar
11. Kosterev, DN, Taylor, CW, Mittelstadt, WA. Model validation for the August 10, 1996 WSCC system outage. IEEE Trans Power SystAug 1999;14:967–79. https://doi.org/10.1109/59.780909.Search in Google Scholar
12. Venkatasubramanian, V, Li, Y. Analysis of 1996 Western American electric blackouts. In: Proc. Bulk power system dynamics and control-VI, Cortina d’Ampezzo, Italy Aug; 2004:685–721 pp.Search in Google Scholar
13. Andersson, G, Donalek, P, Farmer, R, Hatziargyriou, N, Kamwa, I, Kundur, P, et al. Causes of the 2003 major grid blackouts in North America and Europe, and recommended means to improve system dynamic performance. IEEE Trans Power Syst Nov 2005;20:1922–8.10.1109/TPWRS.2005.857942Search in Google Scholar
14. Taylor, CW, Erickson, DC. Recording and analyzing the July 2 cascading outage. IEEE Comput Appl Power Jan 1997;10:26–30. https://doi.org/10.1109/67.560830.Search in Google Scholar
15. Hiskens, IA, Akke, M. Analysis of the Nordel power grid disturbance of January 1, 1997 using trajectory sensitivities. IEEE Trans Power Syst Aug 1999;14:987–94. https://doi.org/10.1109/59.780911.Search in Google Scholar
16. Vournas, CD, Nikolaidis, VC, Tassoulis, AA. Postmortem analysis and data validation in the wake of the 2004 Athens blackout. IEEE Trans Power Syst Aug 2006;21:1331–9. https://doi.org/10.1109/tpwrs.2006.879252.Search in Google Scholar
17. Pourbeik, P, Kundur, PS, Taylor, CW. The anatomy of a power grid blackout—root causes and dynamics of recent major blackouts. IEEE Power Energy Mag Sep/Oct 2006;4:22–9. https://doi.org/10.1109/mpae.2006.1687814.Search in Google Scholar
18. Wong, JJ, Su, CT, Liu, CS, Chang, CL. Study on the 729 blackout in the Taiwan power system. Elsevier J Electr Power Energy Syst 2007;29:589–99. https://doi.org/10.1016/j.ijepes.2007.02.001.Search in Google Scholar
19. Rosas-Casals, M, Solé, R. Analysis of major failures in Europe’s power grid. Elsevier J Electr Power Energy Syst Nov 2010;33:805–8. https://doi.org/10.1016/j.ijepes.2010.11.014.Search in Google Scholar
20. Chaitanya, VVRV, Mohanta, DK, Jaya Bharata Reddy, M. Topological analysis of eastern region of Indian power grid. In: 10th International conference on environment and electrical engineering Rome, Italy 8th–11th May; 2011confproc.10.1109/EEEIC.2011.5874651Search in Google Scholar
21. Liao, H, Abdelrahman, S, Guo, Y, Milanovic, JV. Identification of weak areas of network based on exposure to voltage sags—part ii: assessment of network performance using sag severity index. IEEE Trans Power Deliv Oct 2014;30:2401–9. https://doi.org/10.1109/tpwrd.2014.2362957.Search in Google Scholar
22. Liao, H, Abdelrahman, S, Guo, Y, Milanovic, JV. Identification of weak areas of power network based on exposure to voltage sags—part i: development of sag severity index for single-event characterization. IEEE Trans Power Deliv Oct 2014;30:2392–400. https://doi.org/10.1109/tpwrd.2014.2362965.Search in Google Scholar
23. He, T, Kolluri, S, Mandal, S, Galvan, F, Rasigoufard, P. Identification of weak locations in bulk transmission systems using voltage stability margin index. In: IEEE power engineering society general meeting, Denver, CO, USA, 6th–10th June; 2004confproc.10.1109/PES.2004.1373193Search in Google Scholar
24. Shankar, G, Mukherjee, V, Debnath, S, Gogoi, K. Study of different ANN algorithms for weak area identification of power systems. In: 1st International conference on power and energy in NERIST, 28th–29th Dec; 2012confproc.10.1109/ICPEN.2012.6492342Search in Google Scholar
25. Gogoi, K, Misra, D, Debnath, N, Chatterjee, S. Modelling and study of steady state analysis and fault parameters in 400 kV and 220 kV buses of Indian North Eastern Regional Grid. In: International conference on energy, power and enviroment, Shillong 12th–13th June; 2015.10.1109/EPETSG.2015.7510139Search in Google Scholar
26. Eastern region grid map. Available from: http://www.erldc.org.Search in Google Scholar
27. Central Electricity Authority 2017. [Online]. Available from: http://www.cea.nic.in [Accessed 29 Jun 2017].Search in Google Scholar
28. Maiti, T, Gogoi, K, Chatterjee, S. Modelling and study of Indian Eastern Regional Grid using PSS®E. In: 12th IEEE India international conference INDICON-2015, 17th–20th December 2015, Jamia Millia Islamia, New Delhi; 2015confproc.10.1109/INDICON.2015.7443758Search in Google Scholar
29. PSS®E Lab manual of Colorado state University. www.engr.colostate.edu.Search in Google Scholar
30. PSS®E 33.3 Program application guide.Volume I. http://home.engineering.iastate.edu.Search in Google Scholar
31. PSS®E documentation. Available from: http://w3.siemens.com/smartgrid/-global/en/products-systems-solutions/software-solutions/planningdatam-anagement-software/planning-imulation/pages/psse.aspx.Search in Google Scholar
32. Kessel, P, Glavitsch, H. Estimating the voltage stability of a power system. IEEE-Trans PWRD July 1986;1:346–54. https://doi.org/10.1109/tpwrd.1986.4308013.Search in Google Scholar
33. Huang, Z, Jin, S, Diao, R. Predictive dynamic simulation for large-scale power systems through high-performance computing. In: Proc. High Performance Computing, Networking, Storage and Analysis; 2012:347–54 pp.10.1109/SC.Companion.2012.54Search in Google Scholar
34. Mohamad, AM, Hashim, N, Hamzah, N, Nik Ismail, NF, Abdul Latip, MF. Transient stability analysis on Sarawak’s grid using power system simulator power system simulator for engineering (PSS/E). In: IEEE symposium on industrial electronics and applications (ISIEA), Sept. 25–28, 2011, Langkawi, Malaysia; 2011confproc.10.1109/ISIEA.2011.6108766Search in Google Scholar
35. Yang, JP, Cheng, GH, Xu, Z. Dynamic reduction of large power system in PSS/E. In: IEEE/PES transmission and distriution conference & exhibition: Asia and Pacific Dalian, China; 2005confproc.10.1109/TDC.2005.1546815Search in Google Scholar
36. Yorino, N, Priyadi, A, Kakui, H, Takeshita, M. A new method for obtaining critical clearing time for transient stability. IEEE Trans Power Syst Aug 2010;25. https://doi.org/10.1109/tpwrs.2009.2040003.Search in Google Scholar
37. Roberts, LGW, Champneys, AR, Bell, KRW, di Bernardo, M. Analytical approximations of critical clearing time for parametric analysis of power system transient stability. IEEE J Emerg Sel Top Circuits Syst Aug 2015;5:465–76. https://doi.org/10.1109/jetcas.2015.2467111.Search in Google Scholar
38. IEC 60909. First Edition 2001–07. International Standards. https://www.iec.ch/standardsdev/publications/ts.htm.Search in Google Scholar
© 2020 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Review
- Power quality problem and key improvement technology for regional power grids
- Research Articles
- Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles
- Analysis between graph-based and Power Transfer Distribution Factors (PTDF)-based model reduction methods in Electric Power Systems
- Experimental control of photovoltaic system using neuro – Kalman filter maximum power point tracking (MPPT) technique
- Data compression techniques for Phasor Measurement Unit (PMU) applications in smart transmission grid
- Influence of inter-turn short circuit on the performance of 10 kV, 1000 kW induction motor
- Detection of coherent groups using measured signals, in an inter-area mode, for creating controlled islands to protect the power system from blackout
- Multi-objective optimization of optimal capacitor allocation in radial distribution systems
- A novel approach of closeness centrality measure for voltage stability analysis in an electric power grid
- Dynamic Simulation of Eastern Regional Grid of India using Power System Simulator for Engineering PSS®E
- Optimal total harmonic distortion minimization in multilevel inverter using improved whale optimization algorithm
- A cost effective accumulator management system for electric vehicles
Articles in the same Issue
- Review
- Power quality problem and key improvement technology for regional power grids
- Research Articles
- Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles
- Analysis between graph-based and Power Transfer Distribution Factors (PTDF)-based model reduction methods in Electric Power Systems
- Experimental control of photovoltaic system using neuro – Kalman filter maximum power point tracking (MPPT) technique
- Data compression techniques for Phasor Measurement Unit (PMU) applications in smart transmission grid
- Influence of inter-turn short circuit on the performance of 10 kV, 1000 kW induction motor
- Detection of coherent groups using measured signals, in an inter-area mode, for creating controlled islands to protect the power system from blackout
- Multi-objective optimization of optimal capacitor allocation in radial distribution systems
- A novel approach of closeness centrality measure for voltage stability analysis in an electric power grid
- Dynamic Simulation of Eastern Regional Grid of India using Power System Simulator for Engineering PSS®E
- Optimal total harmonic distortion minimization in multilevel inverter using improved whale optimization algorithm
- A cost effective accumulator management system for electric vehicles
