Research Article
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Year 2020, Volume: 38 Issue: 3, 1527 - 1540, 05.10.2021

Abstract

References

  • [1] Bollington R. Reliability evaluation of power systems, New York: Plenum Press, 1984.
  • [2] Chowdhury A. Distribution system risk assessment based on historical reliability performance. IEEE 2005; 1-7.
  • [3] Balijepalli N. Advances in distribution system reliability assessment. Ph.D., Iowa State University, USA, 2002.
  • [4] Feng Z. Electric distribution system risk assessment using actual utility reliability data. MSc, University of Saskatchewan, Canada, 2006.
  • [5] Wallnerstrom C. J. On risk management of electrical distribution systems and the impact of regulations. BSc, KTH-Royal Institute of Technology, Stockholm, 2008.
  • [6] Chowdhury A. Distribution system risk assessment based on historical reliability performance. IEEE Transactions on Power Systems; 2004.
  • [7] Cadini F, Agliardi G. L, Zio E. A modeling and simulation framework for the reliability/availability assessment of a power transmission grid subject to cascading failures under extreme weather conditions. Applied Energy, 2016; 185: 267-279.
  • [8] Silva E. N, Rodrigues A. B, Silva M. Stochastic assessment of the impact of photovoltaic distributed generation on the power quality indices of distribution networks. Electric Power Systems Research; 2016; 135:59-67.
  • [9] Jirgl M, Stibor Z, Havlikova M. Reliability analysis of systems with a complex structure using Monte Carlo approach systems. In: 12th IFAC Conference on Programmable Devices and Embedded; 2013; Velke Karlovice, pp. 461-466.
  • [10] Ali D, Chowdhury A. Power distribution system reliability, practical methods, and applications, Canada: John Wiley & Sons, Inc., 2009.
  • [11] Ozay A. Design and implementation of a feeder automation system for distribution networks. In: PowerTech Budapest 99. International Conference; 29 Aug.- 2 Sep. 1999; Budapest.
  • [12] Suthapanun C, Jirapong P, Bunchoo P. reliability assessment tool for radial and loop distribution systems using DIgSILENT Power Factory. In: IEEE 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON); 24-27 June 2015; IEEE. pp. 1-6.
  • [13] Naggar R, Langheit C, Dallaire J. Distribution systems reliability assessment, a new approach for new planning requirements. In: 18th International Conference on Electricity Distribution; 6-9 June 2015; Turin: CIRED.
  • [14] Sagar E. Prasad P. Reliability improvement of radial distribution system with smart grid technology. In: Proceedings of the World Congress on Engineering and Computer Science, 23-25 October 2013; San Francisco, USA: WCECS.
  • [15] Altin M. Fault detection and service restoration in medium voltage distribution system. MSc, Middle East Technical University, Ankara, Turkey, 2009.
  • [16] Gucsav M. Distributed network architecture and protocol for distribution automation system, MSc, Middle East Technical, Ankara, Turkey, 1997.
  • [17] Yu H., Chang K., Hsu H., and Cuckler R. A Monte Carlo simulation-based decision support system for reliability analysis of Taiwan’s power system: Framework and empirical study, Energy Journal, 178:252-262 2019.
  • [18] Pradhan A., Kar S., shill P., and Dash P., Implementation of Monte Carlo Simulation to the Distribution Network for Its Reliability Assessment, Innovation in Electrical Power Engineering, Communication, and Computing Technology, 2020.
  • [19] Haifeng S. Parallel Monte Carlo simulation for reliability and cost evaluation of equipment and system. Electric Power Systems Research; 2014; 81:347-356.
  • [20] Haroonabadi H, Haghifam M. Generation reliability assessment in power markets using Monte Carlo simulation and soft computing. Applied Soft Computing 2011; 11: 5292-5298.
  • [21] M. Wadi, M. Baysal, A. Shobole, and M.R. Tur “Reliability Evaluation in Smart Grids via Modified Monte Carlo Simulation Method," 7th International Conference on Renewable Energy Research and Applications (ICRERA), pp. 841-845, Paris, France, 2018.
  • [22] M. Wadi, M. Baysal and A. Shobole "Comparison between Open-Ring and Closed-Ring Grids Reliability," 4th International Conference on Electrical and Electronics Engineering, Ankara, Turkey, 8-10 April 2017.
  • [23] M.R. Tur; A. Shobole; M. Wadi and Ramazan Bayindir, "Valuation of reliability assessment for power systems in terms of distribution system, A case study," IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA), San Diego, USA, 2017.
  • [24] M. Wadi and M. Baysal, “Reliability Assessment of Radial Networks Via Modified RBD Analytical Technique," Sigma Journal of Engineering and Natural Sciences, vol. 35, pp. 717-726, 2017.
  • [25] M Wadi, MR Tur, M Tanriöven, " Optimization of Distributed Generation Using Homer Software and Fuzzy Logic Control," 3rd European Conference on Renewable Energy Systems, Antalya, Turkey, 2015.
  • [26] Celli G, Ghiani E, Pilo F., Soma G. Reliability assessment in smart distribution networks. Electric Power Systems Research 2013; 104:164-175.
  • [27] Aryaa D, Choubeb C, Aryac R, Tiwarya A. Evaluation of reliability indices accounting omission of random repair time for distribution systems using Monte Carlo simulation. Electrical Power and Energy Systems 2012; 42:533-541.
  • [28] Moazzamia M, Hemmatia R, Haghighatdar F, Rafiee Radb S. Reliability evaluation for different power plant busbar layouts by using sequential Monte Carlo simulation. Electrical Power and Energy Systems; 53: 987-993, 2013.
  • [29] Chojnacki A. The use of extended Petri Nets in analyzing the reliability of MV / LV distribution transformer stations,” Elektronika ir Elektrotechnika 2012; 5:121-127.
  • [30] Shobole A., Baysal M., Wadi M., Tur M.R. Real-time active power control in smart grid. IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA), 585-590, 2017.

HISTORICAL AND MONTE CARLO SIMULATION-BASED RELIABILITY ASSESSMENT OF POWER DISTRIBUTION SYSTEMS

Year 2020, Volume: 38 Issue: 3, 1527 - 1540, 05.10.2021

Abstract

Historical reliability assessment, which is based on past real data, is vital for utilities since it reflects the system's operational behavior best. Therefore, most utilities prefer historical reliability assessment rather than a predictive assessment. This paper includes two major parts; the first part analyses the historical data for four feeders sector of the Bosporus Electricity Distribution Incorporated distribution grid based on their historical collected data, while, the second part of the paper uses the analyzed historical data as a reference input for the Monte Carlo simulation method to assess the future reliability analysis. The results show that the proposed reliability assessment methodology is a powerful tool for the future reliability assessment of power distribution grids.

References

  • [1] Bollington R. Reliability evaluation of power systems, New York: Plenum Press, 1984.
  • [2] Chowdhury A. Distribution system risk assessment based on historical reliability performance. IEEE 2005; 1-7.
  • [3] Balijepalli N. Advances in distribution system reliability assessment. Ph.D., Iowa State University, USA, 2002.
  • [4] Feng Z. Electric distribution system risk assessment using actual utility reliability data. MSc, University of Saskatchewan, Canada, 2006.
  • [5] Wallnerstrom C. J. On risk management of electrical distribution systems and the impact of regulations. BSc, KTH-Royal Institute of Technology, Stockholm, 2008.
  • [6] Chowdhury A. Distribution system risk assessment based on historical reliability performance. IEEE Transactions on Power Systems; 2004.
  • [7] Cadini F, Agliardi G. L, Zio E. A modeling and simulation framework for the reliability/availability assessment of a power transmission grid subject to cascading failures under extreme weather conditions. Applied Energy, 2016; 185: 267-279.
  • [8] Silva E. N, Rodrigues A. B, Silva M. Stochastic assessment of the impact of photovoltaic distributed generation on the power quality indices of distribution networks. Electric Power Systems Research; 2016; 135:59-67.
  • [9] Jirgl M, Stibor Z, Havlikova M. Reliability analysis of systems with a complex structure using Monte Carlo approach systems. In: 12th IFAC Conference on Programmable Devices and Embedded; 2013; Velke Karlovice, pp. 461-466.
  • [10] Ali D, Chowdhury A. Power distribution system reliability, practical methods, and applications, Canada: John Wiley & Sons, Inc., 2009.
  • [11] Ozay A. Design and implementation of a feeder automation system for distribution networks. In: PowerTech Budapest 99. International Conference; 29 Aug.- 2 Sep. 1999; Budapest.
  • [12] Suthapanun C, Jirapong P, Bunchoo P. reliability assessment tool for radial and loop distribution systems using DIgSILENT Power Factory. In: IEEE 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON); 24-27 June 2015; IEEE. pp. 1-6.
  • [13] Naggar R, Langheit C, Dallaire J. Distribution systems reliability assessment, a new approach for new planning requirements. In: 18th International Conference on Electricity Distribution; 6-9 June 2015; Turin: CIRED.
  • [14] Sagar E. Prasad P. Reliability improvement of radial distribution system with smart grid technology. In: Proceedings of the World Congress on Engineering and Computer Science, 23-25 October 2013; San Francisco, USA: WCECS.
  • [15] Altin M. Fault detection and service restoration in medium voltage distribution system. MSc, Middle East Technical University, Ankara, Turkey, 2009.
  • [16] Gucsav M. Distributed network architecture and protocol for distribution automation system, MSc, Middle East Technical, Ankara, Turkey, 1997.
  • [17] Yu H., Chang K., Hsu H., and Cuckler R. A Monte Carlo simulation-based decision support system for reliability analysis of Taiwan’s power system: Framework and empirical study, Energy Journal, 178:252-262 2019.
  • [18] Pradhan A., Kar S., shill P., and Dash P., Implementation of Monte Carlo Simulation to the Distribution Network for Its Reliability Assessment, Innovation in Electrical Power Engineering, Communication, and Computing Technology, 2020.
  • [19] Haifeng S. Parallel Monte Carlo simulation for reliability and cost evaluation of equipment and system. Electric Power Systems Research; 2014; 81:347-356.
  • [20] Haroonabadi H, Haghifam M. Generation reliability assessment in power markets using Monte Carlo simulation and soft computing. Applied Soft Computing 2011; 11: 5292-5298.
  • [21] M. Wadi, M. Baysal, A. Shobole, and M.R. Tur “Reliability Evaluation in Smart Grids via Modified Monte Carlo Simulation Method," 7th International Conference on Renewable Energy Research and Applications (ICRERA), pp. 841-845, Paris, France, 2018.
  • [22] M. Wadi, M. Baysal and A. Shobole "Comparison between Open-Ring and Closed-Ring Grids Reliability," 4th International Conference on Electrical and Electronics Engineering, Ankara, Turkey, 8-10 April 2017.
  • [23] M.R. Tur; A. Shobole; M. Wadi and Ramazan Bayindir, "Valuation of reliability assessment for power systems in terms of distribution system, A case study," IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA), San Diego, USA, 2017.
  • [24] M. Wadi and M. Baysal, “Reliability Assessment of Radial Networks Via Modified RBD Analytical Technique," Sigma Journal of Engineering and Natural Sciences, vol. 35, pp. 717-726, 2017.
  • [25] M Wadi, MR Tur, M Tanriöven, " Optimization of Distributed Generation Using Homer Software and Fuzzy Logic Control," 3rd European Conference on Renewable Energy Systems, Antalya, Turkey, 2015.
  • [26] Celli G, Ghiani E, Pilo F., Soma G. Reliability assessment in smart distribution networks. Electric Power Systems Research 2013; 104:164-175.
  • [27] Aryaa D, Choubeb C, Aryac R, Tiwarya A. Evaluation of reliability indices accounting omission of random repair time for distribution systems using Monte Carlo simulation. Electrical Power and Energy Systems 2012; 42:533-541.
  • [28] Moazzamia M, Hemmatia R, Haghighatdar F, Rafiee Radb S. Reliability evaluation for different power plant busbar layouts by using sequential Monte Carlo simulation. Electrical Power and Energy Systems; 53: 987-993, 2013.
  • [29] Chojnacki A. The use of extended Petri Nets in analyzing the reliability of MV / LV distribution transformer stations,” Elektronika ir Elektrotechnika 2012; 5:121-127.
  • [30] Shobole A., Baysal M., Wadi M., Tur M.R. Real-time active power control in smart grid. IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA), 585-590, 2017.
There are 30 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Mohammed Wadı This is me 0000-0001-8928-3729

Mustafa Baysal This is me 0000-0002-6298-918X

Abdulfetah Shobole This is me 0000-0002-3180-6504

Mehmet Rida X Mehmet Rida Tur This is me 0000-0001-5688-4624

Publication Date October 5, 2021
Submission Date October 26, 2019
Published in Issue Year 2020 Volume: 38 Issue: 3

Cite

Vancouver Wadı M, Baysal M, Shobole A, Mehmet Rida Tur MRX. HISTORICAL AND MONTE CARLO SIMULATION-BASED RELIABILITY ASSESSMENT OF POWER DISTRIBUTION SYSTEMS. SIGMA. 2021;38(3):1527-40.

IMPORTANT NOTE: JOURNAL SUBMISSION LINK https://eds.yildiz.edu.tr/sigma/