Recloser based energy exposure assessment of a distribution network

The optimised placement of reclosers on a distribution network is known to improve the reliability of a power system. Furthermore, the protection settings on distribution systems rely heavily on the number and placement of such reclosers. This study examined the effect of using protection settings methodology with the placement of reclosers to ameliorate the damage sustained during faults on a distribution network. The aim of the study was to determine whether this ‘damage control factor’ should be a future consideration for recloser placement. It has been found that the determination of the number and placement of reclosers, which are the function of the energy exposure of feeder, helped to optimise the operation and reliability of a distribution network. This could benefit both energy users and energy suppliers, who often face different challenges during the fault levels on the network.

[1]  Said Salhi,et al.  The location of protection devices on electrical tree networks: a heuristic approach , 2000, J. Oper. Res. Soc..

[2]  Xiaoyu Wang,et al.  Automatic analysis of pole mounted auto-recloser data for fault prognosis to mitigate customer supply interruptions , 2014, 2014 49th International Universities Power Engineering Conference (UPEC).

[3]  Istvan Vokony,et al.  Recloser application possibilities and the related benefits at a Hungarian MV network , 2015, 2015 IEEE Eindhoven PowerTech.

[4]  Jose Roberto Sanches Mantovani,et al.  Optimised placement of control and protective devices in electric distribution systems through reactive tabu search algorithm , 2008 .

[5]  Ramesh C. Bansal,et al.  Optimisation of grid connected hybrid photovoltaic–wind–battery system using model predictive control design , 2017 .

[6]  Pragasen Pillay,et al.  An adaptive method of symmetrical component estimation , 2018 .

[7]  Raj Naidoo,et al.  Smart SISO-MPC based energy management system for commercial buildings: Technology trends , 2016, 2016 Future Technologies Conference (FTC).

[8]  Ramesh C. Bansal Power System Protection in Smart Grid Environment , 2018 .

[9]  D. Rerkpreedapong,et al.  Multiobjective optimal placement of switches and protective devices in electric power distribution systems using ant colony optimization , 2009 .

[10]  Ramesh C. Bansal,et al.  Renewable distributed generation: The hidden challenges – A review from the protection perspective , 2016 .

[11]  Miroslav Begovic,et al.  Placement of distributed generators and reclosers for distribution network security and reliability , 2005 .

[12]  Yihui Zheng,et al.  Data-driven approach for spatiotemporal distribution prediction of fault events in power transmission systems , 2019 .

[13]  C. R. Mason,et al.  The Art and Science of Protective Relaying , 1956 .

[14]  Ramesh C. Bansal,et al.  An optimal energy management system for a commercial building with renewable energy generation under real-time electricity prices , 2018, Sustainable Cities and Society.

[15]  Duong Minh Bui,et al.  FLISR Approach for Smart Distribution Networks Using E-Terra Software—A Case Study , 2018, Energies.

[16]  Ramesh C. Bansal,et al.  Application of let‐through energy to back‐up over‐current protection on high‐voltage feeders , 2018, IET Generation, Transmission & Distribution.

[17]  Ramesh C. Bansal,et al.  Evaluating Phase Over-current Protection Philosophies for Medium-voltage Feeders Applying Let-through Energy and Voltage Dip Minimization , 2016 .

[18]  Ramesh C. Bansal,et al.  Discriminatory Protection Analysis of Three-Phase Asynchronous Motors During Power Disturbances , 2019 .

[19]  Michael Costa,et al.  Fault Hunting Using Three-Phase Reclosers , 2015, 2015 IEEE Rural Electric Power Conference.

[20]  Mihai Sanduleac,et al.  Syncretic Use of Smart Meters for Power Quality Monitoring in Emerging Networks , 2017, IEEE Transactions on Smart Grid.

[21]  M. M. Morcos,et al.  Voltage Sag Mitigation Using Overcurrent Protection Devices , 2001 .

[22]  Kevin Tomsovic,et al.  Optimized distribution protection using binary programming , 1998 .

[23]  G. Parise,et al.  Conductor protection against short circuit current: available I*2t evaluation , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[24]  C. N. Lu,et al.  Feeder Switch Relocation for Customer Interruption Costs Minimization , 2001, IEEE Power Engineering Review.

[25]  M. Tartaglia,et al.  An Analytical Evaluation of the Factor $k^{2}$ for Protective Conductors , 2012, IEEE Transactions on Industry Applications.

[26]  M. Michael,et al.  Elongation of overhead line conductors under combined mechanical and thermal Stress , 2008, 2008 International Conference on Condition Monitoring and Diagnosis.

[27]  Rinu S.M. Thomas OPTIMISING THE NUMBER AND POSITION OF RECLOSERS ON A MEDIUM VOLTAGE DISTRIBUTION LINE TO MINIMISE DAMAGE ON EQUIPMENT , 2015 .

[28]  Ahmad Reza Malekpour,et al.  Optimal Allocation of Distributed Generations and Remote Controllable Switches to Improve the Network Performance Considering Operation Strategy of Distributed Generations , 2011 .

[29]  Ramesh C. Bansal,et al.  Real-time Electricity Pricing: TOU-MPC Based Energy Management for Commercial Buildings , 2017 .

[30]  Helder Leite,et al.  Reclosers to Self-Healing schemes in distribution networks: A techno-economic assessment , 2016, 2016 IEEE International Energy Conference (ENERGYCON).

[31]  Roy Billinton,et al.  Optimal switching device placement in radial distribution systems , 1996 .

[32]  Juan Rivier Abbad,et al.  Optimized Allocation of Control and Protective Devices in Electric Distribution Systems , 2009 .

[33]  P. Chandhra Sekhar,et al.  Evaluation and improvement of reliability indices of electrical power distribution system , 2016, 2016 National Power Systems Conference (NPSC).