Ranking the Radial Configurations for Minimum Losses Distribution System Reconfiguration. Part 2: Intra-day Time-domain Assessment

This paper applies the approach indicated in the companion paper (Part 1) to study the persistence of the optimal configurations in distribution systems with time- dependent generation and load patterns. The solution ranking is carried out at each time step, then a comparison among the solutions is made in the perspective of dividing the time period during the day to apply intra-day reconfiguration separately for the daylight and the night periods. The related savings in the energy losses with respect to maintaining the same globally optimal configuration during the day are illustrated and discussed on a test network example. Three performance indices are defined to obtain and compare the corresponding ranking of the configurations during the time period considered

[1]  C. Cavellucci,et al.  Distribution network reconfiguration for loss reduction with variable demands , 2004, 2004 IEEE/PES Transmision and Distribution Conference and Exposition: Latin America (IEEE Cat. No. 04EX956).

[2]  D. Falabretti,et al.  Mv networks reconfiguration for losses reduction , 2012, 2012 IEEE International Energy Conference and Exhibition (ENERGYCON).

[3]  Xiong Ning,et al.  Gradual Approaching Method for Distribution Network Dynamic Reconfiguration , 2008, 2008 Workshop on Power Electronics and Intelligent Transportation System.

[4]  G. Chicco,et al.  Ranking the Radial Configurations for Minimum Losses Distribution System Reconfiguration. Part 1: Benchmark Results , 2014 .

[5]  Gianfranco Chicco,et al.  Determination of the Relevant Time Periods for Intra-Day Distribution System Minimum Loss Reconfiguration , 2015 .

[6]  Jizhong Zhu.  Optimal Reconfiguration of Electrical Distribution Network , 2015 .

[7]  J. J. Grainger,et al.  Distribution feeder reconfiguration for loss reduction , 1988 .

[8]  C. Lyra,et al.  Adaptive Hybrid Genetic Algorithm for Technical Loss Reduction in Distribution Networks Under Variable Demands , 2009, IEEE Transactions on Power Systems.

[9]  M. Haghifam,et al.  Duration based reconfiguration of electric distribution networks using dynamic programming and harmony search algorithm , 2012 .

[10]  Chan-Nan Lu,et al.  Distribution Feeder Scheduling Considering Variable Load Profile and Outage Costs , 2009, IEEE Transactions on Power Systems.

[11]  Armin Ebrahimi Milani,et al.  An evolutionary approach for optimal time interval determination in distribution network reconfiguration under variable load , 2013, Math. Comput. Model..

[12]  Ehab F. El-Saadany,et al.  Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation , 2013 .

[13]  Enrico Carpaneto,et al.  Cogeneration planning under uncertainty. Part II: Decision theory-based assessment of planning alternatives , 2011 .

[14]  Gianfranco Chicco,et al.  Distribution system optimisation with intra-day network reconfiguration and demand reduction procurement , 2013 .

[15]  George J. Anders,et al.  Probability Concepts in Electric Power Systems , 1990 .

[16]  Kun Yu,et al.  A novel approach for dynamic reconfiguration of the distribution network via multi-agent system , 2008, 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies.

[17]  P. Bastard,et al.  Online reconfiguration considering variability demand: applications to real networks , 2004, IEEE Transactions on Power Systems.