Evaluation of radiality constraints for power distribution networks

Open Access

Issue		RAIRO-Oper. Res. Volume 59, Number 1, January-February 2025


Page(s)		595 - 608
DOI		https://doi.org/10.1051/ro/2025003
Published online		14 February 2025

D. Das, Electrical Power Systems. New Age International (2007). [Google Scholar]
A.A. Sallam and O.P. Malik, Electric Distribution Systems. Wiley (2018). [CrossRef] [Google Scholar]
A. Merlin and H. Back, Search for a minimal-loss operating spanning tree configuration in urban power distribution systems, in 5th Power Systems Computation Conference. Cambridge, UK (1975) 1–5. [Google Scholar]
A. Moura, J. Salvadorinho, B. Soares and J. Cordeiro, Comparative study of distribution networks reconfiguration problem approaches. RAIRO-Oper. Res. 55 (2021) S2083–S2124. [CrossRef] [EDP Sciences] [Google Scholar]
C. Cavellucci and C. Lyra, Minimization of energy losses in electric power distribution systems by intelligent search strategies. Int. Trans. Oper. Res. 4 (1997) 23–33. [CrossRef] [Google Scholar]
E. Bueno, C. Lyra and C. Cavellucci, Distribution network reconfiguration for loss reduction with variable demands, in 2004 IEEE/PES Transmision and Distribution Conference and Exposition: Latin America (IEEE Cat. No. 04EX956). IEEE (2004) 384–389. [Google Scholar]
M.A. Guimaraes and C.A. Castro, Reconfiguration of distribution systems for loss reduction using tabu search, in IEEE Power System Computation Conference (PSCC). Vol. 1 (2005) 1–6. [Google Scholar]
L.M. Queiroz and C. Lyra, Adaptive hybrid genetic algorithm for technical loss reduction in distribution networks under variable demands. IEEE Trans. Power Syst. 24 (2009) 445–453. [CrossRef] [Google Scholar]
J. Torres-Jimenez, J. Guardado, F. Rivas, S. Maximov and E. Melgoza, Reconfiguration of power distribution systems using genetic algorithms and spanning trees, in: 2010 IEEE Electronics, Robotics and Automotive Mechanics Conference. IEEE (2010) 779–784. [Google Scholar]
A.S. Reddy and D.M.D. Reddy, Network reconfiguration of distribution system for maximum loss reduction using sine cosine algorithm. Int. J. Eng. Res. App. (IJERA) 7 (2017) 34–39. [Google Scholar]
M.K. Singh, V. Kekatos, S. Taheri, K.P. Schneider and C.-C. Liu, Enforcing radiality constraints for der-aided power distribution grid reconfiguration. Preprint arXiv:1910.03020 (2019). [Google Scholar]
M.W. Padberg and L.A. Wolsey, Trees and cuts, in Combinatorial Mathematics. Vol. 75 of North-Holland Mathematics Studies, edited by C. Berge, D. Bresson, P. Camion, J. Maurras and F. Sterboul. North-Holland (1983) 511–517. [Google Scholar]
J.A. Taylor and F.S. Hover, Convex models of distribution system reconfiguration. IEEE Trans. Power Syst. 27 (2012) 1407–1413. [CrossRef] [Google Scholar]
R.A. Jabr, R. Singh and B.C. Pal, Minimum loss network reconfiguration using mixed-integer convex programming. IEEE Trans. Power Syst. 27 (2012) 1106–1115. [CrossRef] [Google Scholar]
H. Ahmadi and J.R. Martí, Mathematical representation of radiality constraint in distribution system reconfiguration problem. Int. J. Electr. Power Energy Syst. 64 (2015) 293–299. [CrossRef] [Google Scholar]
M.K. Singh, V. Kekatos and C.-C. Liu, Optimal distribution system restoration with microgrids and distributed generators, in 2019 IEEE Power Energy Society General Meeting (PESGM) (2019) 1–5. [Google Scholar]
S. Mishra, D. Das and S. Paul, A comprehensive review on power distribution network reconfiguration. Energy Syst. 8 (2017) 227–284. [CrossRef] [Google Scholar]
T. Cormen, C. Leiserson, L. Rivest and C. Stein, Algoritmos teoria e prática (2002). [Google Scholar]
R. Diestel, Graph Theory. Springer Graduate Texts in Mathematics, 5th edition. Springer-Verlag, © Reinhard Diestel (2017). [CrossRef] [Google Scholar]
L.R. Ford and D.R. Fulkerson, Maximal flow through a network. Can. J. Math. 8 (1956) 399–404. [CrossRef] [Google Scholar]
A. Gómez-Expósito, A.J. Conejo and C. Ca˜nizares, Electric Energy Systems: Analysis and Operation. CRC Press (2018). [Google Scholar]
M.E. Baran and F.F. Wu, Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Trans. Power Delivery 4 (1989) 1401–1407. [CrossRef] [Google Scholar]
H.R. Esmaeilian and R. Fadaeinedjad, Energy loss minimization in distribution systems utilizing an enhanced reconfiguration method integrating distributed generation. IEEE Syst. J. 9 (2015) 1430–1439. [CrossRef] [Google Scholar]
E.M. Cavalheiro, A.H. Vergílio and C. Lyra, Optimal configuration of power distribution networks with variable renewable energy resources. Comput. Oper. Res. 96 (2018) 272–280. [CrossRef] [Google Scholar]
A. Markana, G. Trivedi and P. Bhatt, Multi-objective optimization based optimal sizing & placement of multiple distributed generators for distribution network performance improvement. RAIRO-Oper. Res. 55 (2021) 899–919. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
Y. Tami, K. Sebaa, M. Lahdeb, O. Usta and H. Nouri, Extended mixed integer quadratic programming for simultaneous distributed generation location and network reconfiguration. Electr. Eng. Electromech. 2 (2023) 93–100. [CrossRef] [Google Scholar]
Y. Hase, Handbook of Power System Engineering. John Wiley & Sons (2007). [CrossRef] [Google Scholar]
T.L. Magnanti and L.A. Wolsey, Optimal trees. Handb. Oper. Res. Manage. Sci. 7 (1995) 503–615. [Google Scholar]
M. Lavorato, J.F. Franco, M.J. Rider and R. Romero, Imposing radiality constraints in distribution system optimization problems. IEEE Trans. Power Syst. 27 (2012) 172–180. [CrossRef] [Google Scholar]
J.C. Tiernan, An efficient search algorithm to find the elementary circuits of a graph. Commun. ACM 13 (1970) 722–726. [CrossRef] [Google Scholar]
A.V. Goldberg and R.E. Tarjan, A new approach to the maximum-flow problem. J. ACM (JACM) 35 (1988) 921–940. [CrossRef] [Google Scholar]
E.D. Dolan and J.J. Moré, Benchmarking optimization software with performance profiles. Math. Program. 91 (2002) 201–213. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.