Network Reconfiguration for an Electric Distribution System with Distributed Generators based on Symbiotic Organisms Search
Abstract
This paper proposes a method of network reconfiguration based on symbiotic organisms search (SOS) algorithm for reducing power loss of the electric distribution system. The SOS is a recent developed meta-heuristic algorithm inspired from the symbiotic interaction strategies of organisms for surviving and propagating in the ecosystem. Compared to other algorithms, SOS does not need any control parameters during the searching process. The advantages of the proposed SOS method have been validated in two electric distribution systems. Three network cases have been considered for each system, consisting of performing network reconfiguration on the system without distributed generator (DG) placement, the system installed type-P DGs and the system installed type-PQ DGs. The comparison results with particle swarm optimization and other previous methods show that the proposed SOS can be a promising technique for the problem of electric network reconfiguration.
Keywords:
symbiotic organisms search, electric distribution system, network reconfiguration, active power lossDownloads
References
W. L. Theo, J. S. Lim, W. S. Ho, H. Hashim, C. T. Lee, “Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods”, Renewable and Sustainable Energy Reviews, Vol. 67, pp. 531–573, 2017 DOI: https://doi.org/10.1016/j.rser.2016.09.063
Y. Mobarak, A. Hemeida, A. El-Bahnasawy, M. Hamada, “Reactive power compensation on Egypt Electricity Network for optimal energy saving”, Engineering, Technology & Applied Science Research, Vol. 9, No. 1, pp. 3699–3704, 2019 DOI: https://doi.org/10.48084/etasr.2451
P. Balamurugan, “Optimal allocation of DSTATCOM in distribution network using hale Optimization Algorithm”, Engineering, Technology & Applied Science Research, Vol. 8, No. 5, pp. 3445–3449, 2018 DOI: https://doi.org/10.48084/etasr.2302
Z. Masomi Zohrabad, “Application of Hybrid HS and Tabu Search Algorithm for optimal location of FACTS devices to reduce power losses in power systems”, Engineering, Technology & Applied Science Research, Vol. 6, No. 6, pp. 1217–1220, 2016 DOI: https://doi.org/10.48084/etasr.725
A. Merlin, H. Back, “Search for a minimal loss operating spanning tree configuration in an urban power distribution system”, 5th Power System Computation Conference, Cambridge, UK, September 1-5, 1975
D. Shirmohammadi, H. W. Hong, “Reconfiguration of electric distribution networks for resistive line losses reduction”, IEEE Transactions on Power Delivery, Vol. 4, No. 2, pp. 1492–1498, 1989 DOI: https://doi.org/10.1109/61.25637
S. Civanlar, J. J. Grainger, H. Yin, S. S. H. Lee, “Distribution feeder reconfiguration for loss reduction”, IEEE Transactions on Power Delivery, Vol. 3, No. 3, pp. 1217–1223, 1988 DOI: https://doi.org/10.1109/61.193906
D. L. Duan, X. D. Ling, X. Y. Wu, B. Zhong, “Reconfiguration of distribution network for loss reduction and reliability improvement based on an enhanced genetic algorithm”, International Journal of Electrical Power and Energy Systems, Vol. 64, pp. 88–95, 2015 DOI: https://doi.org/10.1016/j.ijepes.2014.07.036
K. K. Kumar, N. Venkata, S. Kamakshaiah, “FDR particle swarm algorithm for network reconfiguration of distribution systems”, Journal of Theoretical and Applied Information Technology, Vol. 36, No. 2, pp. 174–181, 2012
T. M. Khalil, A. V Gorpinich, “Reconfiguration for loss reduction of distribution systems using selective Particle Swarm Optimization”, International Journal of Multidisciplinary Sciences and Engineering, Vol. 3, No. 6, pp. 16–21, 2012
A. Y. Abdelaziz, S. F. Mekhamer, F. M. Mohammed, M. A. L. Badr, “A modified Particle Swarm technique for distribution systems reconfiguration”, The Online Journal on Electronics and Electrical Engineering, Vol. 1, No. 1, pp. 121–129, 2009
E. Mahboubi-Moghaddam, M. R. Narimani, M. H. Khooban, A. Azizivahed, M. Javid Sharifi, “Multi-objective distribution feeder reconfiguration to improve transient stability, and minimize power loss and operation cost using an enhanced evolutionary algorithm at the presence of distributed generations”, International Journal of Electrical Power & Energy Systems, Vol. 76, pp. 35–43, 2016 DOI: https://doi.org/10.1016/j.ijepes.2015.09.007
A. Mohamed Imran, M. Kowsalya, “A new power system reconfiguration scheme for power loss minimization and voltage profile enhancement using fireworks algorithm”, International Journal of Electrical Power & Energy Systems, Vol. 62, pp. 312–322, 2014 DOI: https://doi.org/10.1016/j.ijepes.2014.04.034
T. T. Nguyen, T. T. Nguyen, A. V. Truong, Q. T. Nguyen, T. A. Phung, “Multi-objective electric distribution network reconfiguration solution using runner-root algorithm”, Applied Soft Computing, Vol. 52, pp. 93–108, 2017 DOI: https://doi.org/10.1016/j.asoc.2016.12.018
A. V. Truong, T. N. Ton, T. T. Nguyen, T. L. Duong, “Two states for optimal position and capacity of distributed generators considering network reconfiguration for power loss minimization based on runner root algorithm”, Energies, Vol. 12, No. 1, Article ID 106, 2019 DOI: https://doi.org/10.3390/en12010106
T. T. Nguyen, A. V. Truong, “Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm”, International Journal of Electrical Power & Energy Systems, Vol. 68, pp. 233–242, 2015 DOI: https://doi.org/10.1016/j.ijepes.2014.12.075
T. T. Nguyen, A. V. Truong, T. A. Phung, “A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network”, International Journal of Electrical Power & Energy Systems, Vol. 78, pp. 801–815, 2016 DOI: https://doi.org/10.1016/j.ijepes.2015.12.030
M. Y. Cheng, D. Prayogo, “Symbiotic Organisms Search: A new metaheuristic optimization algorithm”, Computers and Structures, Vol. 139, pp. 98–112, 2014 DOI: https://doi.org/10.1016/j.compstruc.2014.03.007
A. E. Ezugwu, D. Prayogo, “Symbiotic Organisms Search Algorithm: theory, recent advances and applications”, Expert Systems with Applications, Vol. 119, pp. 184–209, 2019 DOI: https://doi.org/10.1016/j.eswa.2018.10.045
S. Saha, V. Mukherjee, “Optimal placement and sizing of DGs in RDS using chaos embedded SOS algorithm”, IET Generation, Transmission & Distribution, Vol. 10, No. 14, pp. 3671–3680, 2016 DOI: https://doi.org/10.1049/iet-gtd.2016.0151
T. P. Nguyen, V. N. Dieu, P. Vasant, “Symbiotic Organism Search Algorithm for optimal size and siting of distributed generators in distribution systems”, International Journal of Energy Optimization and Engineering, Vol. 6, No. 3, pp. 1–28, 2017 DOI: https://doi.org/10.4018/IJEOE.2017070101
P. Balachennaiah, M. Suryakalavathi, “Real power loss minimization using symbiotic organisms search algorithm”, 2015 Annual IEEE India Conference, New Delhi, India, December 17-20, 2015 DOI: https://doi.org/10.1109/INDICON.2015.7443589
M. P. Lalitha, P. S. Babu, B. Adivesh, “Optimal distributed generation and capacitor placement for loss minimization and voltage profile improvement using Symbiotic Organisms Search Algorithm”, International Journal of Electrical Engineering, Vol. 9, No. 3, pp. 249–261, 2016
M. Kenan Dosoglu, U. Guvenc, S. Duman, Y. Sonmez, H. Tolga Kahraman, “Symbiotic organisms search optimization algorithm for economic/emission dispatch problem in power systems”, Neural Computing and Applications, Vol. 29, No. 3, pp. 721–737, 2018 DOI: https://doi.org/10.1007/s00521-016-2481-7
D. Prasad, V. Mukherjee, “A novel symbiotic organisms search algorithm for optimal power flow of power system with FACTS devices”, Engineering Science and Technology, an International Journal, Vol. 19, No. 1, pp. 79–89, 2016 DOI: https://doi.org/10.1016/j.jestch.2015.06.005
A. T. Boum, P. R. Ndjependa, J. N. Bisse, “Optimal reconfiguration of power distribution systems based on Symbiotic Organism Search algorithm”, Journal of Power and Energy Engineering, Vol. 5, No. 11, 2017 DOI: https://doi.org/10.4236/jpee.2017.511001
A. Y. Abdelaziz, F. M. Mohamed, S. F. Mekhamer, M. A. L. Badr, “Distribution system reconfiguration using a modified Tabu Search algorithm”, Electric Power Systems Research, Vol. 80, No. 8, pp. 943–953, 2010 DOI: https://doi.org/10.1016/j.epsr.2010.01.001
M. E. Baran, F. F. Wu, “Network reconfiguration in distribution systems for loss reduction and load balancing”, IEEE Transactions on Power Delivery, Vol. 4, No. 2. pp. 1401–1407, 1989 DOI: https://doi.org/10.1109/61.25627
R. Pegado, Z. Naupari, Y. Molina, C. Castillo, “Radial distribution network reconfiguration for power losses reduction based on improved selective BPSO”, Electric Power Systems Research, Vol. 169, pp. 206–213, 2019 DOI: https://doi.org/10.1016/j.epsr.2018.12.030
M. F. Abd El-salam, E. Beshr, M. B. Eteiba, “A new hybrid technique for minimizing power losses in a distribution system by optimal sizing and siting of distributed generators with network reconfiguration”, Energies, Vol. 11, No. 12, Article ID 3351, 2018 DOI: https://doi.org/10.3390/en11123351
H. D. Chiang, R. Jean-Jumeau, “Optimal network reconfigurations in distribution systems: Part 2: Solution algorithms and numerical results”, IEEE Transactions on Power Delivery, Vol. 5, No. 3, pp. 1568–1574, 1990 DOI: https://doi.org/10.1109/61.58002
A. Mohamed Imran, M. Kowsalya, D. P. Kothari, “A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks”, International Journal of Electrical Power and Energy Systems, Vol. 63, pp. 461–472, 2014 DOI: https://doi.org/10.1016/j.ijepes.2014.06.011
A. Onlam, D. Yodphet, R. Chatthaworn, C. Surawanitkun, A. Siritaratiwat, P. Khunkitti, “Power loss minimization and voltage stability improvement in electrical distribution system via network reconfiguration and distributed generation placement using novel adaptive Shuffled Frogs Leaping Algorithm”, Energies, Vol. 12, No. 3, Article ID 553, 2019 DOI: https://doi.org/10.3390/en12030553
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