Optimal Placement and Sizing of Distributed Generation for Minimize Losses in Unbalance Radial Distribution Systems Using Quantum Genetic Algorithm
This work exploits Quantum Genetic Algorithm (QGA) to optimize the placement and sizing of Distributed Generators (DGs) in unbalance radial distribution systems. The goal is to minimize losses and at the same time still maintain acceptable voltage profiles. DGs may be placed at any load buses. The proposed method determines which load buses are to have DGs and of what sizes they are respectively. In the method, QGA randomly generates initial population, find network losses and bus voltages of each population member by means of power flow calculations, keep the member with the best configuration as a reference and re-generate the new population for the next iteration based on the current population and based on the reference. Observations were performed based on a modified IEEE Standard 399-1997. All loads in the standard are increased gradually until the point where at least one bus voltage trips below 0.95 pu. Finally, the network with DGs installed as suggested by the proposed method is then compared to this network.
Copyright © 2014 Praise Worthy Prize - All rights reserved.
T. Gözel, M.H. Hocaoglu, U. Eminoglu, A.Balikci, An analytical method for the sizing and siting of distributed generatorsin radial systems, Electric Power Systems Research 79 (2009) 912–918
H. L. Willis, Analytical Methods and Rules of Thumb for Modelling DG-Distribution Interaction, IEEE PES Summer Meeting, vol. 3, Seattle, WA, July 2000, pp. 1643–1644
T. Griffin, K. Tomsovic, D. Secrest, and A. Law, Placement of Dispersed Generation Systems for Reduced Losses, 33rd Annu. Hawaii Int. Conf. Systems Sciences, Maui, HI, 2000, pp.1-9
C. Wang, M. H. Nehrir, Analytical Approaches for Optimal Placement of DG Sources in Power Systems, IEEE Trans. on Power Syst., Vol. 19, No.4, November 2004, pp. 2068–2076
T. Gözel, M.H. Hocaoglu, U. Eminoglu, A.Balikci, Optimal Placement and Sizing of Distributed Generation on Radial Feeder with Different Static Load Models, Future Power Systems, 2005 International Conference, Amsterdam, 16-18 Nov. 2005
Sudipta Ghosh, S.P. Ghoshal, Saradindu Ghosh, Optimal sizing and placement of distributed generation in a network system, ELSEVIER, Electrical Power and Energy Systems 32 (2010) 849–85
G.N.Koutroiumpezis, A.S.Safigianni, Optimimum allocation of the maximum possible distributed generation penetration in a distribution network. ELSEVIER Electric Power System Research 80(2010) 1421-1427, June 2010
Nara K, Hayashi Y, Ikeda K, Ashizawa T. Application of tabu search to optimal placement of distributed generators. IEEE PES Winter Meet 2001:918–23.
Falaghi and Haghifam, ACO Based Algorithm for Distributed Generation Sources Allocation and Sizing in Distribution Systems, Power Tech, 2007 IEEE Lausanne
A. Jahanbani Ardakani, A. Kashefi Kavyani, S.A. Pourmousavi, S.H. Hosseinian, M.Abedi, Siting and Sizing of Distributed Generation for Loss Reduction, International Carnivorous Plant Society
T. N. Shukla , S.P. Singh, K. B. Naik, Allocation of optimal distributed generation using GA for minimum system losses in radial distribution networks. International Journal of Engineering, Science and Technology Vol. 2, No. 3, 2010, pp. 94-106
M.Sedighizadeh, A.Rezazadeh, Using Genetic Algorithm for Distributed Generation Allocation to Reduce Losses and Improve Voltage Profile. World Academy of Science, Engineering and Technology 37 2008
Carmen L.T.Borges, Djalma M.Falcao, Optimal distributed generation for reliability, losses and voltage improvement. ELSEVIER Electrical Power and Energy System28(1006) 4130-420, February 2006.
Sattianadan, D., Sudhakaran, M., Dash, S.S., Vijayakumar, K., Cost / loss minimization by the placement of DG in distribution system using ga and PSO - A comparative analysis, (2013) International Review of Electrical Engineering (IREE), 8 (2), pp. 769-775.
Celli G, Ghiani E, Mocci S, Pilo F. A multiobjective evolutionary algorithm for the sizing and siting of distributed generation. IEEE Trans Power Syst 2005;20(2):750–7.
Cheng and Shirmohammadi,A three-phase power flow method for real-time distribution system analysis, Power Systems, IEEE Transactions on (Volume:10 , Issue: 2 )
Sarika Khushalani and Noel Schulz, Unbalanced Distribution Power Flow with Distributed Generation, IEEE PES Transmission and Distribution Conference and Exhibition, 301-306.
J. B. V. Subrahmanyam, C. Radhakrishna, Distributed Generator Placement and Sizing in Unbalanced Radial Distribution System, International Journal of Electrical and Electronics Engineering 3:12 2009
John G. Vlachogiannis, Jacob Østergaard, Reactive power and voltage control based on general quantum genetic algorithms, ELSEVIER , Expert Systems with Applications 36 (2009) 6118–6126.
Han, K.-H., & Kim, J.-H. (2000). Genetic quantum algorithm and its application to combinatorial optimization problem. Proceedings of Congress on Evolutionary Computation, 1354–1360.
Hey, T. (1999). Quantum computing: An introduction. Computing and Control Engineering Journal, 10(3), 105–112.
Mamdouh Abdel-Akher, Khalid Mohamed Nor, and Abdul Halim Abdul Rashid, Improved Three-Phase Power-Flow Methods Using Sequence Components, IEEE Transaction on Power Systems, Vol. 20, No. 3, August 2005
Hadi Saadat, Power System Analysis, McGraw-Hill, International Editions 1999.
F. Katiraei, M. R. Iravani, P. W. Lehn, Micro-Grid autonomous operation during and subsequent to islanding process, IEEE Transactions on Power Delivery, vol. 20, no. 1, pp. 248-257, 2005.
Muthukumar, K., Jayalalitha, S., Karthika, R., Unbalanced radial distribution system power loss reduction by optimal distributed generator sizing and location using differential evolution technique, (2013) International Review on Modelling and Simulations (IREMOS), 6 (4), pp. 1176-1182.
Vijayabaskar, S., Manigandan, T., Analysis of TCSC placement in radial distribution system through self adaptive hybrid differential evolution algorithm, (2013) International Review on Modelling and Simulations (IREMOS), 6 (3), pp. 872-878.
Anari, R.G., Niknafs, S., Nasab, M.R.T., A new Fuzzy-Genetic algorithm for optimal capacitor placement and sizing in radial distribution systems, (2012) International Review on Modelling and Simulations (IREMOS), 5 (1), pp. 69-73.
Saidian, A., Heidari, M., Mirabbasi, D., Gharibreza, E., Improvement of voltage unbalance and voltage sag in radial distribution systems using DG, (2011) International Review on Modelling and Simulations (IREMOS), 4 (1), pp. 74-78.
- There are currently no refbacks.
Please send any question about this web site to firstname.lastname@example.org
Copyright © 2005-2018 Praise Worthy Prize