Valuation of Distribution System Lines to Improve the Restoration Process and Enhance the Resilience Index with Considering DGs

Document Type : Original Article

Authors

Energy Systems Department, Faculty of New Technologies, Iran University of Science and Technology, Tehran, Iran

Abstract

In order to increase the resilience of distribution system against natural disaster and human attacks, before the events, the value of the monitored system assets should be identified according to different factors so that during the crisis, restoring of lost loads be done faster and qualitatively better. This paper is based on price-based modeling in which load value, to consider the importance of demand side; failure rate, line availability; intrinsic value of lines, to consider investment cost, as well as topology factor, to emphasize The configuration of grid was taken into consideration. In order to observe the impact of DG on the grid lines evaluation, it was investigated in two states: with and without DGs. The results, in addition to demonstrating the network sensitivity to the influential factors, show that distributed generation has a potential to change ranking of valuation and to help improve the process of restoring the distribution system.

Keywords

Main Subjects


[1]     Billinton, R.; Wu.; Singh,G. “Extreme adverse weather modeling in transmission and distribution system reliability evaluation”; Power Syst. Comput. Conf.(PSCC), Spain. 2002, 65, p. 66.##
[2]     Haimes, Y. Y. “On the definition of resilience in systems”; Risk Anal. An Int. J. 2009, 29, 498-501.##
[3]     Hosseini, S. ;Barker.K.; Ramirez-Marquez, J. E. “A review of definitions and measures of system resilience”; Reliab. Eng. Syst. Saf. 2016, 145, 47-61.##
[4]     Francis, R.; Bekera,B. “A metric and frameworks for resilience analysis of engineered and infrastructure systems”; Reliab. Eng. Syst. Saf. 2014, 121, 90-103.##
[5]     Righi, A. W.; Saurin, T. A.; Wachs, P. “A systematic literature review of resilience engineering: Research areas and a research agenda proposal”; Reliab. Eng. Syst. Saf. 2015, 141, 142-152.##
[6]     Maliszewski, P. J.; Perrings, C. “Factors in the resilience of electrical power distribution infrastructures”;Appl. Geogr. 2012, 32, 668-679.##
[7]     Nan, C.; Sansavini, G. “A quantitative method for assessing resilience of interdependent infrastructures”; Reliab. Eng. Syst. Saf. 2017, 157, 35-53.##
[8]     Ouyang, M.; Duenas-Osorio, L. “Multi-dimensional hurricane resilience assessment of electric power systems”; Struct. Saf. 2014, 48, 15-24.##
[9]     Cadini, F.; Agliardi, G. L.; E. Zio. “A modeling and simulation framework for the reliability/availability assessment of a power transmission grid subject to cascading failures under extreme weather conditions”; Appl. Energy. 2017, 185, 267-279.##
[10]  Figueroa-Candia, M.; Felder, F. A.; Coit, D. W. “Resiliency-based optimization of restoration policies for electric power distribution systems”; Electr. Power Syst. Res. 2018, 161, 188-198.##
[11]  Walsh, T.; Layton, T.; Wanik, D.; Mellor, J. “Agent based model to estimate time to restoration of storm-induced power outages”. Infrastructures. 2018, 3, p. 33.##
[12]  Zhang, H.; Bie, Z.; Yan, C.; Li, G. “Post-disaster Power System Resilience Enhancement Considering Repair Process”; 2018 China Int. Conf. Electr. Distrib., 2018, 1550-1554.##
[13]  Alizade, M.; Khosravi, M. “Provide a practical approach in planning and placement of distributed generation sources based on multi-objective genetic algorithms” .Adv. Defence Sci & Technol, pp. 267-277, 2019.##
Volume 11, Issue 4 - Serial Number 42
January 2021
Pages 383-389
  • Receive Date: 21 July 2019
  • Revise Date: 07 February 2020
  • Accept Date: 09 March 2020
  • Publish Date: 21 December 2020