Data-Driven Approach for SVC Location Finding using FVSI in Distribution Network Configuration Environment

doi:10.23940/ijpe.23.12.p4.797806

Abstract

Abstract: Voltage instability and power losses is a key problem in the power system that increases the cost of operation of electric utilities and later increases the cost of electricity. One approach to solving the issue is to reconfigure the distribution network. By using a FACTS device, such as SVC (Static VAR Compensator) in a reconfigured network the loss can be reduced, and the voltage stability margin can be preserved. The primary challenge is locating the ideal system position for SVC connections. In this study, the machine learning technique is utilized to forecast the FVSI (Fast Voltage Stability Index) values of the lines for the preferred network placement of SVC. The ML algorithms are trained and predicated using the estimated FVSI values for various network reconfigurations. The proposed work has been tested using the IEEE 14 bus system.

Key words: distribution network, network reconfiguration, voltage stability, SVC, FVSI, machine learning

Deblina Bhowmick, Dipu Sarkar, and Etesola Imchen. Data-Driven Approach for SVC Location Finding using FVSI in Distribution Network Configuration Environment [J]. Int J Performability Eng, 2023, 19(12): 797-806.

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References

[1] Zamani-Gargari, M., Kalavani, F., and Zare, K. Review of Impacts of Static Var Compensator Allocation on Radial Distribution Networks. IETE Journal of Research, vol. 65, no. 1, pp. 120-127, 2019.
[2] Bekri, O.L. and Fellah, M.K.The Static VAR Compensator (SVC) Device in the Power Systems using MATLAB/SimPowerSystems. InInternational Conference on Electrical Engineering and its Applications, 2008.
[3] Baghaee H.R., Jannati M., Vahidi B., Hosseinian S.H., andRastegar H.Improvement of Voltage Stability and Reduce Power System Losses by Optimal GA-Based Allocation of Multi-Type FACTS Devices. In2008 11th International Conference on Optimization of Electrical and Electronic Equipment, IEEE, pp. 209-214, 2008.
[4] Al-Mahroqi, Y., Metwally, I.A., Al-Hinai, A., and Al-Badi, A. Reduction of Power Losses in Distribution Systems. International Journal of Computer and Systems Engineering, vol. 6, no. 3, pp. 315-322, 2012.
[5] Jazebi S., Hosseinian S.H., andVahidi B.DSTATCOM Allocation in Distribution Networks Considering Reconfiguration using Differential Evolution Algorithm. Energy conversion and Management, vol. 52, no. 7, pp. 2777-2783, 2011.
[6] Zhang P., Li W., andWang S.Reliability-Oriented Distribution Network Reconfiguration Considering Uncertainties of Data by Interval Analysis. International Journal of Electrical Power & Energy Systems, vol. 34, no. 1, pp. 138-144, 2012.
[7] Taleski, R. and Rajicic, D.Distribution Network Reconfiguration for Energy Loss Reduction. IEEE Transactions on Power Systems, vol. 12, no. 1, pp. 398-406, 1997.
[8] Rao, R.S., Narasimham, S.V.L., and Ramalingaraju, M. Optimization of Distribution Network Configuration for Loss Reduction using Artificial Bee Colony Algorithm. International Journal of Electrical Power and Energy Systems Engineering, vol. 1, no. 2
pp. 116-122, 2008.
[9] Sarfi, R.J., Salama, M.M.A., and Chikhani, A.Y. A Survey of the State of the Art in Distribution System Reconfiguration for System Loss Reduction. Electric Power Systems Research, vol. 31, no. 1, pp. 61-70, 1994.
[10] de Oliveira, L.W., Carneiro Jr, S., De Oliveira, E.J., Pereira, J.L.R., Silva Jr, I.C., and Costa, J.S. Optimal Reconfiguration and Capacitor Allocation in Radial Distribution Systems for Energy Losses Minimization. International Journal of Electrical Power & Energy Systems, vol. 32, no. 8, pp. 840-848, 2010.
[11] Chakraborty K., Saha B., andDas S.A Method for Improving Voltage Stability of a Multi-Bus Power System using Network Reconfiguration Method. International Journal of Electrical Engineering, vol. 8, no. 1, pp. 91-102, 2015.
[12] Sahoo, N.C. and Prasad, K.A Fuzzy Genetic Approach for Network Reconfiguration to Enhance Voltage Stability in Radial Distribution Systems. Energy conversion and management, vol.47, no. 18-19, pp. 3288-3306, 2006.
[13] Sarkar D., De A., Chandaand C.K., andGoswami S.ANN Based Online Voltage Stability Monitoring for Distribution Feeder Reconfiguration. International Journal of Electrical Engineering, vol. 3, no. 1, pp. 231-240, 2010.
[14] Sarkar D., Goswami S., De A., Chanda C.K., andMukhopadhyay K.Improvement of Voltage Stability Margin in a Reconfigured Radial Power Network using Graph Theory. Canadian Electrical Engineering Journal, vol. 2, no. 9, pp. 454-462, 2011.
[15] Sarkar D., De A., Chanda C.K., andGoswami S.Kruskal's Maximal Spanning Tree Algorithm for Optimizing Distribution Network Topology to Improve Voltage Stability. Electric Power Components and Systems, vol. 43, no. 17, pp. 1921-1930, 2015.
[16] Otuo-Acheampong,D., Rashed, G.I., Akwasi, A.M., and Haider, H. Application of Optimal Network Reconfiguration for Loss Minimization and Voltage Profile Enhancement of Distribution System using Heap-Based Optimizer. International Transactions on Electrical Energy Systems, vol. 2023, 2023.
[17] Chiou J.P., Chang C.F., andSu C.T.Variable Scaling Hybrid Differential Evolution for Solving Network Reconfiguration of Distribution Systems. IEEE transactions on power systems, vol. 20, no. 2, pp. 668-674, 2005.
[18] Choudekar P., Sinha S.K., andSiddiqui A.Optimal Location of SVC for Improvement in Voltage Stability of a Power System under Normal and Contingency Condition. International Journal of System Assurance Engineering and Management, vol. 8, pp. 1312-1318, 2017.
[19] Selvaraj, G. and Rajangam, K.Multi‐Objective Grey Wolf Optimizer Algorithm for Combination of Network Reconfiguration and D-STATCOM Allocation in Distribution System. International Transactions on Electrical Energy Systems, vol. 29, no. 11, pp. e12100, 2019.
[20] Boudjelia H., Gherbi F.Z., andLakdja F.Modelling and Simulation of Static Var Compensator (SVC) in Power System Studies by MATLAB, 2008.
[21] Bekri, O.L. and Fellah, M.K.The Static VAR Compensator (SVC) Device in the Power Systems using MATLAB/SimPowerSystems. InInternational Conference on Electrical Engineering and its Applications, 2008.
[22] Ramasamy A., Verayiah R., Abidin H.Z., andMusirin I.A Study on FVSI Index as an Indicator for under Voltage Load Shedding (UVLS). In2009 3rd International Conference on Energy and Environment (ICEE), IEEE, pp. 84-88, 2009.
[23] Musirin, I. and Rahman, T.A.Novel Fast Voltage Stability Index (FVSI) for Voltage Stability Analysis in Power Transmission System. InStudent conference on research and development, IEEE, pp. 265-268, 2002.
[24] Ray S.A Quick Review of Machine Learning Algorithms. In2019 International conference on machine learning, big data, cloud and parallel computing (COMITCon), IEEE, pp. 35-39, 2019.
[25] Touzani S., Granderson J., andFernandes S.Gradient Boosting Machine for Modeling the Energy Consumption of Commercial Buildings. Energy and Buildings, vol. 158, pp. 1533-1543, 2018.