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Optimum placement of multi type DG units for loss reduction in a radial distribution system considering the distributed generation

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Języki publikacji
EN
Abstrakty
EN
Due to the increasing need for electricity, insertion of distributed generation (DG) into a distribution system attracts the attention of the deregulated power market. Placing DG in the distribution system inherently reduces the power loss and improves the system voltage profile. The choice of DG, proper placement and sizing of DG all play a vital role. This paper presents an effective methodology to identify the optimum location of multi type DG in the distribution system. The particle swarm optimization (PSO) algorithm and differential evolution (DE) are applied to identify the proper location and size of DG using the distributed generation suitability index (DGSI). The optimum location of DG is identified through DGSI and optimum sizing is done by means of the power loss minimization technique using evolutionary algorithms. The effective power loss reduction and improved system voltage profile are evaluated using sixteen combinations of different types of DGs with the standard IEEE 33-bus test system. The results reveal that power loss reduction and voltage profile improvement are effectively addressed by the DE algorithm.
Rocznik
Strony
345--354
Opis fizyczny
Bibliogr. 25 poz., rys., wykr., tab.
Twórcy
  • Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai, Tamilnadu – 600062, India
autor
  • Vardhaman College of Engineering, Shamshabad, Hyderabad, Telangana – 501218, India
  • CMR College of Engineering & Technology, Kandlakoya, Telangana – 501401, India
  • SSN College of Engineering, Kalavakkam, Chennai, Tamilnadu – 603110, India
Bibliografia
  • [1] C. Lucia, T. Borges, and V. Ferreira, “Multistage expansion planning for active distribution networks under demand and distributed generation”, International Journal of Electrical Power and Energy Systems 36 (1), 107‒116 (2011).
  • [2] N. Karuppiah, V. Malathi, and G. Selvalakshmi, “Optimal placement and sizing of multi-type facts devices using PSO and HSA”, International Conference on Swarm, Evolutionary, and Memetic Computing, 292‒303 (2014).
  • [3] S. Saha and V. Mukherjee, “Optimal placement and sizing of DGs in RDS using chaos embedded SOS algorithm”, IET Generation, Transmission and Distribution 10 (14), 3671–3680 (2016).
  • [4] A.K. Bohre, G. Agnihotri, and M. Dubey, “Optimal sizing and sitting of DG with load models using soft computing techniques in practical distribution system”, IET Generation, Transmission and Distribution 10 (11), 2606–2621 (2016).
  • [5] M.M. Aman, G.B. Jasmon, H. Mokhlis, and Ab Halim Abu Bakar, “Optimum tie switches allocation and DG placement based on maximization of system load ability using discrete artificial bee colony algorithm”, IET Generation, Transmission and Distribution, 10 (10), 2277–2284 (2016).
  • [6] A. Heidari and V. G. Agelidis, “Considerations of sectionalizing switches in distribution networks with distributed generation”, IEEE Transactions on Power Delivery, 30 (3), 1401 – 1409 (2015).
  • [7] S. Naik, G. Naik, D. K. Khatod, and M. P. Sharma, “Analytical approach for optimal siting and sizing of distributed generation in radial distribution networks”, IET Generation, Transmission and Distribution 9 (3), 209–220 (2015).
  • [8] H.B. Tolab, M.H. Ali, and M. Rizwan “Simultaneous reconfiguration, optimal placement of DSTATCOM, and photovoltaic array in a distribution system based on fuzzy-ACO approach”, IEEE Transactions on Sustainable Energy 6 (1), 210‒218 (2015).
  • [9] Al Abri RS, El-Saadany Ehab F, and Atwa Yasser M. “Optimal placement and sizing method to improve the voltage stability margin in a distribution system using distributed generation”, IEEE Transactions on Power Systems 28 (1), 326–34 (2013).
  • [10] M. Vatani, D.S. Alkaran, M.J. Sanjari, and G.B. Gharehpetian, “Multiple distributed generation units allocation in distribution network for loss reduction based on a combination of analytical and genetic algorithm methods”, IET Generation, Transmission and Distribution 10 (1), 66–72 (2016).
  • [11] S.R. Tuladhar and J.G.S. Weerakorn Ongsakul, “Multi-objective approach for distribution network reconfiguration with optimal DG power factor using NSPSO”, IET Generation, Transmission and Distribution 10 (12), 2842–285 (2016).
  • [12] R. Srinivasa Rao, K. Ravindra, K. Satish, and S.V.L. Narasimham, “Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation”, IEEE Transactions On Power Systems 28 (1), 317-325 (2013).
  • [13] A. Heidari, V.G. Agelidis, M.K.J. Pou, J. Aghaei, and M. Shafie-Khah, J. P. S. Catalão, “Reliability optimization of automated distribution networks with probability customer interruption cost model in the presence of DG units”, IEEE Transactions on Smart Grid 8 (1), 305‒315 (2017).
  • [14] W. Sheng, K.-Y. Liu, Y. Liu, X. Meng, and Y. Li, “Optimal placement and sizing of distributed generation via an improved non dominated sorting genetic algorithm II”, IEEE Transactions on Power Delivery (to be published), doi: 10.1109/ TPWRD.2014.2325938.
  • [15] F.M.F. Flaih, L. Xiangning, I.M. Dawoud, and M.A. Mohammed, “Distribution system reconfiguration for power loss minimization and voltage profile improvement using modified particle swarm optimization”, IEEE PES Asia-Pacific Power and Energy Conference (2016).
  • [16] M. Nafar, “PSO based optimal placement of DGs in distribution systems considering voltage stability and short circuit level improvement”, Journal of Basic and Applied Scientific Research 2 (1), 703–709 (2012).
  • [17] M.M. Aman, G.B. Jasmon, and H. Mokhlis, et al. “Optimal placement and sizing of a DG based on a new power stability index and line losses”, International Journal of Electrical Power & Energy Systems 43 (1), 1296–1304 (2012).
  • [18] S. Muthubalaji and V. Malathi, “A hybrid MACO and BFOA algorithm for power loss minimization and total cost reduction in distribution systems”, Turkish Journal of Electrical Engineering and Computer Sciences 25 (1,) 337‒351 (2017).
  • [19] S. Muthubalaji and V. Malathi, “Multi-objective distribution feeder reconfiguration by considering energy not supplied with distributed generation”, Technicki Vjesnik – Technical Gazette 22 (6), 1539‒1545 (2015).
  • [20] M. Gandomkar, M. Vakilian, and M. Ehsan, “A combination of genetic algorithm and simulated annealing for optimal DG allocation in distribution networks”, Proceedings of Canadian Conference on Electrical and Computer Engineering, Saskatoon, 645–648 (2005).
  • [21] R. Sivasangari and N. Kamaraj, “Optimum allocation of renewable DG sources and synchronous capacitor simultaneously using PSO”, International Journal of Applied Engineering Research 11, 2781‒2785 (2016).
  • [22] F. Ugranli and E. Karatepe, “Multiple distributed generation planning under load uncertainty and different penetration levels”, Electric Power and Energy Systems 46, 132‒144 (2013).
  • [23] N. Karuppiah and V. Malathi, “Damping of power system oscillations by tuning of PSS and SVC using particle swarm optimization”, Technical Gazette 23 (1), 221‒227 (2016).
  • [24] D.S.K. Kanth et al., “Siting and sizing of DG for power loss and THD reduction, voltage improvement using PSO and sensitivity analysis”, International Journal of Engineering Research and Development 9 (6), 1‒7 (2013).
  • [25] R. Ravi and H. Sangwan, “Optimal positioning and sizing of DG units using differential evolution algorithm”, International Journal of Innovative Research in Science, Engineering and Technology 5 (9), 17178‒17185 (2016).
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2117c317-0dd3-41bf-aa76-7ff543e478d7
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