Active Distribution Networks Restoration after Extreme Events

Document Type : Research paper

Authors

Department of Electrical Engineering, University of Isfahan, Isfahan, Iran

Abstract

After extreme events such as floods, thunderstorms, blizzards and hurricanes there will be devastating effects in the distribution networks which may cause a partial or complete blackout. Then, the major concern for the system operators is to restore the maximum critical loads as soon as possible by available generation units.  In order to solve this problem, this paper provides a restoration strategy by using Distributed Generations (DGs).  In this strategy, first, the shortest paths between DGs and critical loads are identified. Then, the best paths are determined by using a decision-making method, named PROMOTHEE-II to achieve the goals. The uncertainties for the output power of DGs are also considered in different scenarios. The IEEE 123-node distribution network is used to show the performance of the suggested method. The simulation results clearly show the efficiency of the proposed strategy for critical loads restoration in distribution networks.

Keywords

Main Subjects


[1]    Grid Resilience to Weather Outages”, Washington, DC: Executive Office of the President, 2013.
[2]    M. Panteli and P. Mancarella, “Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies”, Electr. Power Syst. Res., vol. 127, pp. 259-270, 2015.
[3]    X. Xu, E. Makram, T. Wang and R. Medeiros, “Customer-oriented planning of distributed generations in an active distribution system”, IEEE Power & Energy Soc. Gen. Meeting, pp. 1-5, 2005.
[4]    C. Chen, J. Wang, F. Qiu and D. Zhao, “Resilient distribution system by microgrids formation after natural disasters”, IEEE Trans. smart grid, vol. 7, no. 2, pp. 958-966, 2016.
[5]    S. Ghasemi, A. Khodabakhshian and R. Hooshmand, “New multi-stage restoration method for distribution networks with DGs”, IET Gener. Transm. Distrib., vol. 13, no. 1, pp. 55-63, 2018.
[6]    J. M. Solanki, S. Khushalani, and N. N. Schulz, “A multi-agent solution to distribution systems restoration”, IEEE Trans. Power Syst., vol. 22, no. 3, pp. 1026-1034, 2007.
[7]    S. I. Lim, S. J. Lee, M. S. Choi, D. J. Lim and B. N. Ha, “Service restoration methodology for multiple fault case in distribution systems”, IEEE Trans. Power Syst., vol. 21, no. 4, pp. 1638-1644, 2006.
[8]    C. P. Nguyen and A. J. Flueck, “Agent based restoration with distributed energy storage support in smart grids”, IEEE Trans. Smart Grid, vol. 3, no. 2, pp. 1029-1038, 2012.
[9]    A. Cuomo, R. Kauffman, J. Rhodes, A. Zibelman and J. Hauer, “Microgrids for critical facility resiliency in New York state”, Final report, New York State Energy Research Development Authority, 2014.
[10]    F. Wang et al., “A multi-stage restoration method for medium-voltage distribution system with DGs”, IEEE Trans. Smart Grid, vol. 8, no. 6, pp. 2627-2636, 2017.
[11]    R. Vargas, W. P. Mathias-Neto, L. G. da Silva and J. R. Mantovani, “Automatic restoration of active distribution networks based on tabu search specialized algorithm”, 2015 IEEE PES Innovative Smart Grid Technol. Latin America (ISGT LATAM), pp. 411-416, 2015.
[12]    H. Sekhavatmanesh and R. Cherkaoui, “Optimal infrastructure planning of active distribution networks complying with service restoration requirements”, IEEE Trans. Smart Grid, vol. 9, no. 6, pp. 6566-6577, 2018.
[13]    H. Jia, X. Jin, Y. Mu and X. Yu, “A multi-level service restoration strategy of distribution network considering microgrids and electric vehicles”, 2014 Inter. Conf. Intell. Green Building and Smart Grid (IGBSG), pp. 1-4, 2014.
[14]    A. Sharma, D. Srinivasan and A. Trivedi, “A decentralized multiagent system approach for service restoration using DG islanding”, IEEE Trans. Smart Grid, vol. 6, no. 6, pp. 2784-2793, 2015.
[15]    A. A. Hafez, W. A. Omran and Y. G. Hegazy, “A decentralized technique for autonomous service restoration in active radial distribution networks”, IEEE Trans. on Smart Grid, vol. 9, no. 3, pp. 1911-1919, 2018.
[16]    T. Ding, Y. Lin, Z. Bie and C. Chen, “A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration”, Appl. Energy, vol. 199, pp. 205-216, 2017.
[17]    B. Chen, C. Chen, J. Wang and K. L. Butler-Purry, “Sequential service restoration for unbalanced distribution systems and microgrids”, IEEE Trans. Power Syst., vol. 33, no. 2, pp. 1507-1520, 2018.
[18]    N. Anuranj, R. K. Mathew, S. Ashok and S. Kumaravel, “Resiliency based power restoration in distribution systems using microgrids”, IEEE 6th Inter. Conf. Power Syst., pp. 1-5, 2016.
[19]    M. Khederzadeh and S. Zandi, “Enhancement of Distribution System Restoration Capability in Single/Multiple Faults by Using Microgrids as a Resiliency Resource”, IEEE Syst. J., vol. 13, pp. 1796 - 1803, 2019.
[20]    M. Zadsar, M. R. Haghifam and S. M. M. Larimi, “Approach for self-healing resilient operation of active distribution network with microgrid”, IET Gener. Transm. Distrib., vol. 11, no. 18, pp. 4633-4643, 2017.
[21]    Y. Xu et al., “DGs for service restoration to critical loads in a secondary network”, IEEE Trans. Smart Grid, vol. 10, pp. 435 - 447,2017.
[22]    Z. Wang, J. Wang and C. Chen, “A three-phase microgrid restoration model considering unbalanced operation of distributed generation”, IEEE Trans. Smart Grid, vol. 9, no. 4, pp. 3594-3604, 2016.
[23]    M. Figueroa-Candia, F. A. Felder and D. W. Coit, “Resiliency-based optimization of restoration policies for electric power distribution systems”, Electr. Power Syst. Res., vol. 161, pp. 188-198, 2018.
[24]    N. Zendehdel, “Robust agent based distribution system restoration with uncertainty in loads in smart grids”, J. Oper. Autom. Power Eng., vol. 3, no. 1, pp. 1-22, 2015.
[25]    S. Dimitrijevic and N. Rajakovic, “Service Restoration of Distribution Networks Considering Switching Operation Costs and Actual Status of the Switching Equipment”, IEEE Trans. Smart Grid, vol. 6, no. 3, pp. 1227-1232, 2015.
[26]    Y. Xu, C. C. Liu, K. P. Schneider and D. T. Ton, “Placement of remote-controlled switches to enhance distribution system restoration capability”, IEEE Trans. Power Syst., vol. 31, no. 2, pp. 1139-1150, 2016.
[27]    J. C. López, J. F. Franco and M. J. Rider, “Optimisation-based switch allocation to improve energy losses and service restoration in radial electrical distribution systems”, IET Gener. Transm. Distrib., vol. 10, no. 11, pp. 2792-2801, 2016.
[28]    H. Gao, Y. Chen, Y. Xu and C. C. Liu, “Resilience-oriented critical load restoration using microgrids in distribution systems”, IEEE Trans. Smart Grid, vol. 7, no. 6, pp. 2837-2848, 2016.
[29]    Y. Xu, C. C. Liu, K. P. Schneider, F. K. Tuffner and D. T. Ton, “Microgrids for service restoration to critical load in a resilient distribution system”, IEEE Trans. Smart Grid, vol. 9, no. 1, pp. 426-437, 2018.
[30]    R. Romero, J. F. Franco, F. B. Leão, M. J. Rider and E. S. De Souza, “A new mathematical model for the restoration problem in balanced radial distribution systems”, IEEE Trans. Power Syst., vol. 31, no. 2, pp. 1259-1268, 2016.
[31]    R. Bellman, “On a routing problem”, Q. appl. Math., vol. 16, no. 1, pp. 87-90, 1958.
[32]    R. Singh, S. Mehfuz and P. Kumar, “Intelligent decision support algorithm for distribution system restoration”, Springer Plus, vol. 5, no. 1, pp. 1175, 2016.
[33]    W. H. Chen, “Quantitative decision-making model for distribution system restoration”, IEEE Trans. Power Syst., vol. 25, no. 1, pp. 313-321, 2010.
[34]    J. P. Brans and P. Vincke, “Note - A preference ranking organisation method: (the PROMETHEE method for multiple criteria decision-making)”, Manage. Sci., vol. 31, no. 6, pp. 647-656, 1985.
[35]    S. Poudel and A. Dubey, “critical load restoration using distributed energy resources for resilient power distribution system”, IEEE Trans. Power Syst., vol. 34, no. 1, pp. 52-63, 2019.
[36]    C. Chen, J. Wang, F. Qiu and D. Zhao, “Resilient distribution system by microgrids formation after natural disasters”, IEEE Trans. smart grid, vol. 7, no. 2, pp. 958-966, 2016.