Abstract
This paper proposes two techniques for the identification of critical buses in a power system. The technique of Network Structural Theory Participation Factor (NSTPF) depends on the network structural interconnection of buses as captured by the admittance matrix of the system and is formulated based on the fundamental circuit theory law using eigenvalue decomposition method. Another power flow based technique which depends on the system maximum loadability, the system step size among other factors is also proposed. Traditional power flow based techniques are used as benchmarks to determine the significance of the proposed methods. To ensure voltage stability enhancement, STATCOM FACTS device is installed at the selected weak load buses of the practical Nigerian 24 bus and IEEE 30 bus test systems. The results of the simulation obtained show that, the suggested approach of NSTPF is more suitable in the identification of weak buses that are liable to voltage instability in power systems as it requires less computational burden and also saves time compared to techniques based on power flow solutions.
References
[1] Chen K, Hussein A, Bradley ME, Wan H. A performance-index guided continuation method for fast computation of saddle-node bifurcation in power systems. IEEE Trans Power Syst. 2003;18(2):753–60.10.1109/TPWRS.2003.811203Search in Google Scholar
[2] Cañizares CA, De AC, Souza Z, Quintana VH. Comparison of performance indices for detection of proximity to voltage collapse. IEEE Trans Power Syst. 1996;11(3):1441–50.10.1109/59.535685Search in Google Scholar
[3] Nguyen TV, Nguyen YM, Yoon YT. A new method for static voltage stability assessment based on the local loadability boundary. Int J Emerging Electr Power Syst. 2012;13(4):1–14. Article 2.10.1515/1553-779X.2994Search in Google Scholar
[4] Damodhar SS, Krishna S. A novel load shedding scheme for voltage stability. Int J Emerg Electr Power Syst. 2016;17(6):649–61.10.1515/ijeeps-2015-0159Search in Google Scholar
[5] Ajjarapu V, Lee B. Bibliograph on voltage stability. IEEE Trans Power Syst. 1998;13(1):115–25.10.1109/59.651622Search in Google Scholar
[6] FERC. Principles for efficient and reliable reactive power supply and consumption. Docket No. AD05-1-000. USA: FERC Staff Reports, 2005.Search in Google Scholar
[7] Moger T, Dhadbanjan T. A novel index for identification of weak nodes for reactive compensation to improve voltage stability. IET Gener Transm Distrib. 2015;9(14):1826–34.10.1049/iet-gtd.2015.0054Search in Google Scholar
[8] Aumuller CA, Saha TK. Determination of power system coherent bus groups by novel sensitivity-based method for voltage stability assessment. IEEE Trans Power Syst. 2003;18(3):1157–64.10.1109/TPWRS.2003.814886Search in Google Scholar
[9] Konar S, Chatterjee D, Patra S. V–Q sensitivity-based index for assessment of dynamic voltage stability of power systems. IET Gener Transm Distrib. 2015;9(7):677–85.10.1049/iet-gtd.2014.0710Search in Google Scholar
[10] Ajjarapu V, Christy C. The continuation power flow: a tool for steady state voltage stability analysis. IEEE Trans Power Syst. 1992;7(1):416–23.10.1109/59.141737Search in Google Scholar
[11] Azadani EN, Hosseinian SH, Hasanpor P. Optimal placement of multiple STATCOM for voltage stability margin enhancement using particle swarm optimization. Electr Eng. 2008;90(7):503–10.10.1007/s00202-008-0101-ySearch in Google Scholar
[12] Allaoua B, Laoufi A. Optimal power flow solution using ant manners for electrical network. Adv Electr Comput Eng. 2009;9(1):34–40.10.4316/aece.2009.01006Search in Google Scholar
[13] Gao B, Morison GK, Kundur P. Voltage stability evaluation using modal analysis. IEEE Trans Power Syst. 1992;7(4):1529–42.10.1109/59.207377Search in Google Scholar
[14] Lof PA, Andersson G, Hill D. Voltage stability indices for stressed power systems. IEEE Trans Power Syst. 1993;8(1):326–35.10.1109/59.221224Search in Google Scholar
[15] Taylor CW. Power system voltage stability. New York, NY: McGraw-Hill, 1994.Search in Google Scholar
[16] Acharjee P. Identification of voltage collapse points and weak buses under security constraints using hybrid particle swarm optimization technique. Int Trans Electr Energy Syst. 2013;23:230–48.10.1002/etep.657Search in Google Scholar
[17] Kessel P, Glavitsch H. Estimating the voltage stability of a power system. IEEE Trans Power Deliv. 1986;1(3):346–54.10.1109/TPWRD.1986.4308013Search in Google Scholar
[18] Balamourougan V, Sidhu TS, Sachdev MS. Technique for online prediction of voltage collapse. IEE Proc Gener Transm Distrib. 2004;151(4):453–60.10.1049/ip-gtd:20040612Search in Google Scholar
[19] Musirin I, Rahman TK. Novel Fast Voltage Stability Index (FVSI) for voltage stability analysis in power transmission system. Student confence on Research and Development Proceedings, Shan Alam, Malaysia, 2002.10.1109/SCORED.2002.1033108Search in Google Scholar
[20] Acharya NV, Rao PS. A new voltage stability index based on the tangent vector of the power flow jacobian. 2013 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), Bangalore, 2013:1–6.10.1109/ISGT-Asia.2013.6698776Search in Google Scholar
[21] Laughton MA, El-Iskandarani MA 1978. On the inherent network structure. In Proceedings 6th Power System Computation Conference (PSCC), 178–89.Search in Google Scholar
[22] Caramia P, Russo A, Varilone P. The inherent structure theory of network for power quality issues. Proc IEEE Power Eng Soc Winter Meeting. 2001;1:176–85.10.1109/PESW.2001.917029Search in Google Scholar
[23] Carpinelli G, Russo A, Russo M, Verde P. Inherent structure thory of networks for power system harmonics. IEEE Proc Gener Transm Distrib. 1998;145(2):123–32.10.1049/ip-gtd:19981663Search in Google Scholar
[24] Thukaram D, Vyjayanthi C. Evaluation of suitable locations for generation expansion in restructured power systems: A novel concept of t-index. Int J Emerging Electr Power Syst. 2009;10(1):1–24. article 4.10.2202/1553-779X.2023Search in Google Scholar
[25] Sikiru TH, Jimoh AA, Agee JT. Inherent structural characteristic indices of power system networks. Int J Electr Power Energy Syst. 2013;47:218 –24.10.1016/j.ijepes.2012.11.011Search in Google Scholar
[26] Sikiru TH, Jimoh AA, Agee JT. Optimal location of network devices using a novel inherent network topology based technique. IEEE Proc AFRICON, 2011, Livingstone, 2011:1–4.10.1109/AFRCON.2011.6071982Search in Google Scholar
[27] Adebayo IG, Jimoh AA, Yusuff A. Voltage stability assessment and identification of important nodes in power transmission network through network response structural characteristics. IET Gener Transm Distrib. 2017;11(6):1398–408.10.1049/iet-gtd.2016.0745Search in Google Scholar
[28] Sen KK. STATCOM-static synchronous compensator theory, modelling and applications. IEEE PES Winter Meeting. 1999;2:1177–83.Search in Google Scholar
[29] Hingorani NG, Gyugyi L. Index. In: Understanding FACTS:concepts and technology of flexible AC transmission systems. vol. 1. United States: Wiley-IEEE Press, 2000:425–29.Search in Google Scholar
[30] Wei X, Chow JH, Fardanesh B, Edris AA. A common modelling framework of voltage sourced converters for power flow, sensitivity, and dispatch analysis. IEEE Trans Power Syst. 2004;19:934–41.10.1109/TPWRS.2004.826753Search in Google Scholar
[31] Acha E, Fuerte-Esquivel CR, Ambriz-Perez H, Angeles-Camacho C. FACTS modelling and simulation in power networks. Chichester: John Wiley & Sons; 2004.10.1002/0470020164Search in Google Scholar
[32] Adebayo IG, Adejumobi IA, Adepoju GA. Application of Load-Tap Changing Transformer (LTCT) to the optimal economic dispatch of generation of the Nigerian 330kV grid system. Int J Emerging Technol Sci Eng. 2012;5(3):40–50.Search in Google Scholar
[33] Onohaebi OS. Reduction of the high technical power losses associated with the Nigerian 330kV transmission network. Int J Electr Power Eng. 2007;1(4):421–31.Search in Google Scholar
Bus data of the Nigerian 330kV grid power system.
| Bus No | Bus Type | Voltage Mag.(p.u) | Angle | Pd (Mw) | Qd (MVar) | Pg (Mw) | Qg (MVar) | Qmin (MVar) | Qmax (MVar) |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 1.05 | 0 | 68.9 | 51.7 | 0 | 0 | −1006 | 1006 |
| 2 | 2 | 1.05 | 0 | 0.0 | 0 | 670.0 | 0 | −1030 | 1000 |
| 3 | 0 | 1 | 0 | 274.4 | 205.8 | 0 | 0 | 0 | 0 |
| 4 | 0 | 1 | 0 | 344.7 | 258.5 | 0 | 0 | 0 | 0 |
| 5 | 0 | 1 | 0 | 633.2 | 474.9 | 0 | 0 | 0 | 0 |
| 6 | 0 | 1 | 0 | 13.8 | 10.3 | 0 | 0 | 0 | 0 |
| 7 | 0 | 1 | 0 | 96.5 | 72.4 | 0 | 0 | 0 | 0 |
| 8 | 0 | 1 | 0 | 383.3 | 287.5 | 0 | 0 | 0 | 0 |
| 9 | 0 | 1 | 0 | 275.8 | 206.8 | 0 | 0 | 0 | 0 |
| 10 | 0 | 1 | 0 | 201.2 | 150.9 | 0 | 0 | 0 | 0 |
| 11 | 2 | 1.05 | 0 | 52.5 | 39.4 | 431.0 | 0 | −1000 | 1000 |
| 12 | 0 | 1 | 0 | 427.0 | 320.2 | 0 | 0 | 0 | 0 |
| 13 | 0 | 1 | 0 | 177.9 | 133.4 | 0 | 0 | 0 | 0 |
| 14 | 0 | 1 | 0 | 184.6 | 138.4 | 0 | 0 | 0 | 0 |
| 15 | 0 | 1 | 0 | 114.5 | 85.9 | 0 | 0 | 0 | 0 |
| 16 | 0 | 1 | 0 | 130.6 | 97.9 | 0 | 0 | 0 | 0 |
| 17 | 0 | 1 | 0 | 11.0 | 8.2 | 0 | 0 | 0 | 0 |
| 18 | 2 | 1.05 | 0 | 0.0 | 0.0 | 495.0 | 0 | −1050 | 1050 |
| 19 | 0 | 1 | 0 | 70.3 | 52.7 | 0 | 0 | 0 | 0 |
| 20 | 0 | 1 | 0 | 193.0 | 144.7 | 0 | 0 | 0 | 0 |
| 21 | 2 | 1.05 | 0 | 7.0 | 5.2 | 624.7 | 0 | −1010 | 1010 |
| 22 | 0 | 1 | 0 | 199.8 | 149.9 | 0 | 0 | 0 | 0 |
| 23 | 2 | 1.05 | 0 | 320.1 | 256.1 | 388.9 | 0 | −1000 | 1000 |
| 24 | 2 | 1.05 | 0 | 20.6 | 15.4 | 190.3 | 0 | −1000 | 1000 |
Line data of the Nigerian 330Kv grid power system.
| From | To | R (p.u) | X (p.u) | 1/2B | Tap ratio |
|---|---|---|---|---|---|
| 3 | 1 | 0.0006 | 0.0044 | 0.0295 | 1 |
| 3 | 1 | 0.0006 | 0.0044 | 0.0295 | 1 |
| 4 | 5 | 0.0007 | 0.0050 | 0.0333 | 1 |
| 4 | 5 | 0.0007 | 0.0050 | 0.0333 | 1 |
| 1 | 5 | 0.0023 | 0.0176 | 0.1176 | 1 |
| 1 | 5 | 0.0023 | 0.0176 | 0.1176 | 1 |
| 5 | 8 | 0.0110 | 0.0828 | 0.5500 | 1 |
| 5 | 8 | 0.0110 | 0.0828 | 0.5500 | 1 |
| 5 | 9 | 0.0054 | 0.0405 | 0.2669 | 1 |
| 5 | 10 | 0.0099 | 0.0745 | 0.4949 | 1 |
| 6 | 8 | 0.0077 | 0.0576 | 0.3830 | 1 |
| 6 | 8 | 0.0077 | 0.0576 | 0.3830 | 1 |
| 2 | 8 | 0.0043 | 0.0317 | 0.2101 | 1 |
| 2 | 7 | 0.0012 | 0.0089 | 0.0589 | 1 |
| 7 | 24 | 0.0025 | 0.0186 | 0.1237 | 1 |
| 8 | 14 | 0.0054 | 0.0405 | 0.2691 | 1 |
| 8 | 10 | 0.0098 | 0.0742 | 0.4930 | 1 |
| 8 | 24 | 0.0020 | 0.0148 | 0.0982 | 1 |
| 8 | 24 | 0.0020 | 0.0148 | 0.0982 | 1 |
| 9 | 10 | 0.0045 | 0.0340 | 0.2257 | 1 |
| 15 | 21 | 0.0122 | 0.0916 | 0.6089 | 1 |
| 15 | 21 | 0.0122 | 0.0916 | 0.6089 | 1 |
| 10 | 17 | 0.0061 | 0.0461 | 0.3064 | 1 |
| 10 | 17 | 0.0061 | 0.0461 | 0.3064 | 1 |
| 10 | 17 | 0.0061 | 0.0461 | 0.3064 | 1 |
| 11 | 12 | 0.0010 | 0.0074 | 0.0491 | 1 |
| 11 | 12 | 0.0010 | 0.0074 | 0.0491 | 1 |
| 12 | 14 | 0.0060 | 0.0455 | 0.3025 | 1 |
| 13 | 14 | 0.0036 | 0.0272 | 0.1807 | 1 |
| 13 | 14 | 0.0036 | 0.0272 | 0.1807 | 1 |
| 16 | 19 | 0.0118 | 0.0887 | 0.5892 | 1 |
| 16 | 19 | 0.0118 | 0.0887 | 0.5892 | 1 |
| 17 | 18 | 0.0002 | 0.0020 | 0.0098 | 1 |
| 17 | 18 | 0.0002 | 0.0020 | 0.0098 | 1 |
| 17 | 23 | 0.0096 | 0.0721 | 0.4793 | 1 |
| 17 | 23 | 0.0096 | 0.0721 | 0.4793 | 1 |
| 17 | 21 | 0.0032 | 0.0239 | 0.1589 | 1 |
| 17 | 21 | 0.0032 | 0.0239 | 0.1589 | 1 |
| 19 | 20 | 0.0081 | 0.0609 | 0.4046 | 1 |
| 20 | 22 | 0.0090 | 0.0680 | 0.4516 | 1 |
| 20 | 23 | 0.0038 | 0.0284 | 0.1886 | 1 |
| 20 | 23 | 0.0038 | 0.0284 | 0.1886 | 1 |
© 2018 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Microgrid Architecture Evaluation for Small and Medium Size Industries
- Application of V2G and G2V Coordination of Aggregated Electric Vehicle Resource in Load Levelling
- Design of Filter based Wide Area Damping Controllers in Power System
- A Study of Efficient MPPT Techniques for Photovoltaic System Using Boost Converter
- Estimation of Battery Soc for Hybrid Electric Vehicle using Coulomb Counting Method
- Combined Frequency Equivalent Model for Power Transmission Network Dynamic Behavior Analysis
- Generator Coherency Using Zolotarev Polynomial Based Filter Bank and Principal Component Analysis
- Techniques for the Identification of Critical Nodes Leading to Voltage Collapse in a Power System
- Computational Studies of Voltage Regulation Provided by Wind Farms Through Reactive Power Control
- Energy Scheduling of Smart Appliances at Home under the Effect of Dynamic Pricing Schemes and Small Renewable Energy Source
- High Rate Pulse Discharge of Lithium Battery in Electromagnetic Launch System
- A Balanced Operation of Static VAR Compensator for Voltage Stability Improvement and Harmonic Minimization