Electricity distribution network for low and medium voltages based on evolutionary approach optimization

The optimum planning of distribution systems consists of the optimum placement and size of new substations, feeders, capacitors, distributed generation and other distribution components in order to satisfy the future power demand with minimum investment and operational costs and an acceptable level...

Full description

Saved in:

Bibliographic Details
Main Author:	Hasan, Ihsan Jabbar
Format:	Thesis
Language:	English English
Published:	2015
Subjects:	T Technology (General)
Online Access:	http://eprints.utem.edu.my/id/eprint/16765/1/Electricity%20Distribution%20Network%20For%20Low%20And%20Medium%20Voltages%20Based%20On%20Evolutionary%20Approach%20Optimization.pdf http://eprints.utem.edu.my/id/eprint/16765/2/Electricity%20distribution%20network%20for%20low%20and%20medium%20voltages%20based%20on%20evolutionary%20approach%20optimization.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utem-ep.16765
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Ab Ghani, Mohd Ruddin
topic	T Technology (General) T Technology (General)
spellingShingle	T Technology (General) T Technology (General) Hasan, Ihsan Jabbar Electricity distribution network for low and medium voltages based on evolutionary approach optimization
description	The optimum planning of distribution systems consists of the optimum placement and size of new substations, feeders, capacitors, distributed generation and other distribution components in order to satisfy the future power demand with minimum investment and operational costs and an acceptable level of reliability. This thesis deals with the optimization of distribution network planning to find the most affordable network design in terms of total power losses minimization and voltage profiles improvement. The planning and operation of distribution networks are driven by several important factors of network designing. The optimum placement and sizing of the capacitor banks into existing distribution networks is one of the major issues. The optimum placement and sizing of the new substations and distribution transformers with adequate feeder connections with minimum length and maximum functionality are vital for power system as well as optimum placement and sizing of the distributed generators into the existing grid. This thesis commonly investigated the impacts of these factors on voltage profile and total power losses of the networks and aims to reduce the capital cost and operational costs of the distribution networks in both LV and MV levels. Optimum capacitor installation has been utilized in terms of reactive power compensation to achieve power loss reduction, voltage regulation, and system capacity release. The Particle Swarm Optimization (PSO) is utilized to find the best possible capacitor placement and size. The OpenDSS engine is utilized to solve the power flow through MATLAB coding interface. To validate the functionality of the proposed method, the IEEE 13 node and IEEE 123 node test systems are implemented. The result shows that the proposed algorithm is more cost effective and has lower power losses compare to the IEEE standard case. In addition, the voltage profile has been improved. Optimum placement of distribution substations and determination of their sizing and feeder routing is another major issue of distribution network planning. This thesis proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified Minimum Spanning Tree (MST). The proposed algorithm has been evaluated on the two types of distribution network models which are the distribution network model with 500 customers that includes LV residential and commercial loads as well as MV distribution network, and 164 nodes in MV level. The test network is generated by fractal based distribution network generation model software tool. The results indicate that proposed algorithm has succeeded in finding a reasonable placement and sizing of distributed generation with adequate feeder path. Another sector of power system that is taken into account in this work is Distributed Generators (DGs). In power system, more especially in distribution networks, DGs are able to mitigate the total losses of the network which effectively has significant effects on environmental pollution. This thesis aims to investigate the best solution for an optimal operation of distribution networks by taking into consideration the DG. The PSO method has been used to solve the DG placement and sizing on the IEEE 34 and 123 nodes test systems, respectively. It has been utilized to demonstrate the effectiveness of the PSO method to improve the voltage profile and minimize the cost by mitigating the total losses of the network.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Hasan, Ihsan Jabbar
author_facet	Hasan, Ihsan Jabbar
author_sort	Hasan, Ihsan Jabbar
title	Electricity distribution network for low and medium voltages based on evolutionary approach optimization
title_short	Electricity distribution network for low and medium voltages based on evolutionary approach optimization
title_full	Electricity distribution network for low and medium voltages based on evolutionary approach optimization
title_fullStr	Electricity distribution network for low and medium voltages based on evolutionary approach optimization
title_full_unstemmed	Electricity distribution network for low and medium voltages based on evolutionary approach optimization
title_sort	electricity distribution network for low and medium voltages based on evolutionary approach optimization
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Electrical Engineering
publishDate	2015
url	http://eprints.utem.edu.my/id/eprint/16765/1/Electricity%20Distribution%20Network%20For%20Low%20And%20Medium%20Voltages%20Based%20On%20Evolutionary%20Approach%20Optimization.pdf http://eprints.utem.edu.my/id/eprint/16765/2/Electricity%20distribution%20network%20for%20low%20and%20medium%20voltages%20based%20on%20evolutionary%20approach%20optimization.pdf
_version_	1747833890394865664
spelling	my-utem-ep.167652022-04-19T11:31:18Z Electricity distribution network for low and medium voltages based on evolutionary approach optimization 2015 Hasan, Ihsan Jabbar T Technology (General) TK Electrical engineering. Electronics Nuclear engineering The optimum planning of distribution systems consists of the optimum placement and size of new substations, feeders, capacitors, distributed generation and other distribution components in order to satisfy the future power demand with minimum investment and operational costs and an acceptable level of reliability. This thesis deals with the optimization of distribution network planning to find the most affordable network design in terms of total power losses minimization and voltage profiles improvement. The planning and operation of distribution networks are driven by several important factors of network designing. The optimum placement and sizing of the capacitor banks into existing distribution networks is one of the major issues. The optimum placement and sizing of the new substations and distribution transformers with adequate feeder connections with minimum length and maximum functionality are vital for power system as well as optimum placement and sizing of the distributed generators into the existing grid. This thesis commonly investigated the impacts of these factors on voltage profile and total power losses of the networks and aims to reduce the capital cost and operational costs of the distribution networks in both LV and MV levels. Optimum capacitor installation has been utilized in terms of reactive power compensation to achieve power loss reduction, voltage regulation, and system capacity release. The Particle Swarm Optimization (PSO) is utilized to find the best possible capacitor placement and size. The OpenDSS engine is utilized to solve the power flow through MATLAB coding interface. To validate the functionality of the proposed method, the IEEE 13 node and IEEE 123 node test systems are implemented. The result shows that the proposed algorithm is more cost effective and has lower power losses compare to the IEEE standard case. In addition, the voltage profile has been improved. Optimum placement of distribution substations and determination of their sizing and feeder routing is another major issue of distribution network planning. This thesis proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified Minimum Spanning Tree (MST). The proposed algorithm has been evaluated on the two types of distribution network models which are the distribution network model with 500 customers that includes LV residential and commercial loads as well as MV distribution network, and 164 nodes in MV level. The test network is generated by fractal based distribution network generation model software tool. The results indicate that proposed algorithm has succeeded in finding a reasonable placement and sizing of distributed generation with adequate feeder path. Another sector of power system that is taken into account in this work is Distributed Generators (DGs). In power system, more especially in distribution networks, DGs are able to mitigate the total losses of the network which effectively has significant effects on environmental pollution. This thesis aims to investigate the best solution for an optimal operation of distribution networks by taking into consideration the DG. The PSO method has been used to solve the DG placement and sizing on the IEEE 34 and 123 nodes test systems, respectively. It has been utilized to demonstrate the effectiveness of the PSO method to improve the voltage profile and minimize the cost by mitigating the total losses of the network. 2015 Thesis http://eprints.utem.edu.my/id/eprint/16765/ http://eprints.utem.edu.my/id/eprint/16765/1/Electricity%20Distribution%20Network%20For%20Low%20And%20Medium%20Voltages%20Based%20On%20Evolutionary%20Approach%20Optimization.pdf text en public http://eprints.utem.edu.my/id/eprint/16765/2/Electricity%20distribution%20network%20for%20low%20and%20medium%20voltages%20based%20on%20evolutionary%20approach%20optimization.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96187 phd doctoral Universiti Teknikal Malaysia Melaka Faculty of Electrical Engineering Ab Ghani, Mohd Ruddin 1. Acharya, N., Mahat, P. and Mithulananthan, N., 2006. An analytical approach for DG allocation in primary distribution network. International Journal of Electrical Power & Energy Systems, 28(10), pp.669–678. 2. Ahmad, M.N., 2006. Transmission Grid Planning. In Tenaga Nasional Berhad. Malaysia. 3. AlRashidi, M.R. and El-Hawary, M.E., 2009. A survey of particle swarm optimization applications in electric power systems. Evolutionary Computation, IEEE Transactions on, 13(4), pp.913–918. 4. Augugliaro, A., Dusonchet, L. and Sanseverino, E.R., 2002. An evolutionary parallel tabu search approach for distribution systems reinforcement planning. Advanced Engineering Informatics, 16(3), pp.205–215. 5. Azim, S. and Swarup, K.S., 2005. Optimal capacitor allocation in radial distribution systems under APDRP. In INDICON, 2005 Annual IEEE. IEEE, pp. 614–618. 6. Baghzouz, Y. and Ertem, S., 1990. Shunt capacitor sizing for radial distribution feeders with distorted substation voltages. IEEE Transactions on Power Delivery, 5(2), pp.650–657. 7. Barker, P.P. and de Mello, R.W., 2000. Determining the impact of distributed generation on power systems. I. Radial distribution systems. In Power Engineering Society Summer Meeting, 2000. IEEE. IEEE, pp. 1645–1656. 8. Berge, C. and Ghouila-Houri, A., 1965. Programming, games and transportation networks. 9. Bianchi, L., Dorigo, M., Gambardella, L. and Gutjahr, W., 2009. A survey on metaheuristics for stochastic combinatorial optimization. Natural Computing, 8(2), pp.239–287. Available at: http://dx.doi.org/10.1007/s11047-008-9098-4. 10. Billinton, R. and Wang, P., 1998. Distribution system reliability cost/worth analysis using analytical and sequential simulation techniques. Power Systems, IEEE Transactions on, 13(4), pp.1245–1250. 11. Blum, C., Roli, A. and Sampels, M., 2008. Hybrid metaheuristics: an emerging approach to optimization, Springer Science & Business Media. 12. Borges, C.L.T. and Falcao, D.M., 2006. Optimal distributed generation allocation for reliability, losses, and voltage improvement. International Journal of Electrical Power & Energy Systems, 28(6), pp.413–420. 13. Bouchard, D.E., Salama, M.M.A. and Chikhani, A.Y., 1994. Optimal distribution feeder routing and optimal substation sizing and placement using evolutionary strategies. In Electrical and Computer Engineering, 1994. Conference Proceedings. 1994 Canadian Conference on. IEEE, pp. 661–664. 14. Bouchard, D.E., Salama, M.M.A. and Chikhani, A.Y., 1995. Optimal feeder routing and optimal substation sizing and placement using guided evolutionary simulated annealing. In Electrical and Computer Engineering, 1995. Canadian Conference on. IEEE, pp. 688–691. 15. Boulaxis, N. and Papadopoulos, M., 2002. Optimal feeder routing in distribution system planning using dynamic programming technique and GIS facilities. IEEE Transactions on Power Delivery, 17(1), pp.242–247. 16. Bull, S.R., 2001. Renewable energy today and tomorrow. Proceedings of the IEEE, 89(8), pp.1216–1226. 17. Carrano, E.G., Soares, L.A.E., Takahashi, R.H.C., Saldanha, R.R. and Neto, O.M., 2006. Electric distribution network multiobjective design using a problem-specific genetic algorithm. Power Delivery, IEEE Transactions on, 21(2), pp.995–1005. 18. Celli, G., Ghiani, E., Loddo, M. and Pilo, F., 2005. An heuristic technique for the optimal planning of meshed MV distribution network. In Power Tech, 2005 IEEE Russia. IEEE, pp. 1–7. 19. Celli, G., Mocci, S., Pilo, F., BERTINI, D., CICORIA, R. and CORTI, S., 2007. Multi-year optimal planning of active distribution networks. In 19th International Conference on Electricity Distribution, Vienna. 20. Celli, G., Pilo, F., Pisano, G., Allegranza, V., Cicoria, R. and Iaria, A., 2004. Meshed vs. radial MV distribution network in presence of large amount of DG. In Power Systems Conference and Exposition, 2004. IEEE PES. IEEE, pp. 709–714. 21. Chang, G.W., Aganagic, M., Waight, J.G., Medina, J., Burton, T., Reeves, S. and Christoforidis, M., 2001. Experiences with mixed integer linear programming based approaches on short-term hydro scheduling. Power Systems, IEEE Transactions on, 16(4), pp.743–749. 22. Chang, H.-C. and Kuo, C.-C., 1994. Network reconfiguration in distribution systems using simulated annealing. Electric Power Systems Research, 29(3), pp.227–238. 23. Chiradeja, P., 2005. Benefit of Distributed Generation: A Line Loss Reduction Analysis. 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific, pp.1–5. 24. Chiradeja, P. and Ramakumar, R., 2004. An approach to quantify the technical benefits of distributed generation. Energy Conversion, IEEE Transactions on, 19(4), pp.764–773. 25. Clark, S.W., 2014. Improvement of step-voltage regulating transformer efficiency through tap changer control modification. T&D Conference and Exposition, 2014 IEEE PES, pp.1–5. 26. Cossi, A.M., Romero, R. and Mantovani, J.R.S., 2009. Planning and projects of secondary electric power distribution systems. Power Systems, IEEE Transactions on, 24(3), pp.1599–1608. 27. Cottrill, J.E.J., 1980. Economic assessment of the renewable energy sources. IEE Proceedings A (Physical Science, Measurement and Instrumentation, Management and Education, Reviews), 127(5), pp.279–288. 28. Dehkordi, B.M., Optimal Capacitor Placement and Sizing in TABRIZ Distribution System Using Loss Sensitivity Factors and Particle Swarm Optimization (PSO). , pp.1–6. 29. Delfino, B., 2002. Modeling of the integration of distributed generation into the electrical system. In Power Engineering Society Summer Meeting, 2002 IEEE. IEEE, pp. 170–175. 30. Dorigo, M., Maniezzo, V. and Colorni, A., 1996. Ant system: optimization by a colony of cooperating agents. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 26(1), pp.29–41. 31. Dugan, R.C., 2012. The Open Distribution System Simulator ( OpenDSS ), California. 32. Eajal, A. and El-Hawary, M., 2010. Optimal capacitor placement and sizing in distorted radial distribution systems part III: Numerical results. In 4th International Conference on Harmonics and Quality of Power (ICHQP). pp. 1 – 8. 33. Eajal, A. and El-Hawary, M.E., 2010. Optimal capacitor placement and sizing in unbalanced distribution systems with harmonics consideration using particle swarm optimization. Power Delivery, IEEE Transactions on, 25(3), pp.1734–1741. 34. El-Fouly, T.H.M., Zeineldin, H.H., El-Saadany, E.F. and Salama, M.M.A., 2008. A new optimization model for distribution substation siting, sizing, and timing. International Journal of Electrical Power & Energy Systems, 30(5), pp.308–315. 35. El-Khattam, W., Hegazy, Y.G. and Salama, M.M.A., 2005. An integrated distributed generation optimization model for distribution system planning. Power Systems, IEEE Transactions on, 20(2), pp.1158–1165. 36. Falaghi, H. and Haghifam, M., 2007. ACO based algorithm for distributed generation sources allocation and sizing in distribution systems. In Power Tech, 2007 IEEE Lausanne. IEEE, pp. 555–560. 37. Farghal, S.A. and Abdel Aziz, M.R., 1988. Generation expansion planning including the renewable energy sources. Power Systems, IEEE Transactions on, 3(3), pp.816–822. 38. Favuzza, S., Graditi, G., Ippolito, M.G. and Sanseverino, E.R., 2007. Optimal electrical distribution systems reinforcement planning using gas micro turbines by dynamic ant colony search algorithm. Power Systems, IEEE Transactions on, 22(2), pp.580–587. 39. Fletcher, R.H. and Strunz, K., 2007. Optimal distribution system horizon planning–part I: formulation. Power Systems, IEEE Transactions on, 22(2), pp.791–799. 40. Fletcher, R.H. and Strunz, K., 2007. Optimal distribution system horizon planning–Part II: application. Power Systems, IEEE Transactions on, 22(2), pp.862–870. 41. Franco, J.F., Rider, M.J., Lavorato, M. and Romero, R., 2013. A mixed-integer LP model for the optimal allocation of voltage regulators and capacitors in radial distribution systems. International Journal of Electrical Power & Energy Systems, 48, pp.123–130. 42. Gan, C. k., 2011. Strategies for design of future distribution networks. Imperial College London, PhD Thesis. 43. Gan, C.K., Mancarella, P., Pudjianto, D. and Strbac, G., 2011. Statistical appraisal of economic design strategies of LV distribution networks. Electric Power Systems Research, 81(7), pp.1363–1372. 44. Ganguly, S., Sahoo, N.C. and Das, D., 2013. Multi-objective planning of electrical distribution systems using dynamic programming. International Journal of Electrical Power & Energy Systems, 46, pp.65–78. 45. Ganguly, S., Sahoo, N.C. and Das, D., 2009. Multi-objective planning of electrical distribution systems using particle swarm optimization. In Electric Power and Energy Conversion Systems, 2009. EPECS’09. International Conference on. IEEE, pp. 1–6. 46. García, J.A.M. and Mena, A.J.G., 2013. Optimal distributed generation location and size using a modified teaching–learning based optimization algorithm. International journal of electrical power & energy systems, 50, pp.65–75. 47. Ghadimi, A.A. and Rastegar, H., 2009. Optimal control and management of distributed generation units in an islanded microgrid. In Integration of Wide-Scale Renewable Resources Into the Power Delivery System, 2009 CIGRE/IEEE PES Joint Symposium. IEEE, pp. 1-7. 48. Glover, F., 1989. Tabu search-part I. ORSA Journal on computing, 1(3), pp.190–206. 49. Glover, F., 1990. Tabu search—part II. ORSA Journal on computing, 2(1), pp.4–32. 50. Glover, F., Kelly, J.P. and Laguna, M., 1995. Genetic algorithms and tabu search: hybrids for optimization. Computers & Operations Research, 22(1), pp.111–134. 51. Glover, F. and Taillard, E., 1993. A user’s guide to tabu search. Annals of operations research, 41(1), pp.1–28. 52. Golberg, D.E., 1989. Genetic algorithms in search, optimization, and machine learning. Addion wesley. 53. Gomez, J.F., Khodr, H.M., De Oliveira, P.M., Ocque, L., Yusta, J.M., Villasana, R. and Urdaneta, A.J., 2004. Ant colony system algorithm for the planning of primary distribution circuits. Power Systems, IEEE Transactions on, 19(2), pp.996–1004. 54. Gönen, T. and Foote, B.L., 1981. Distribution-system planning using mixed-integer programming. In IEE Proceedings C (Generation, Transmission and Distribution). IET, pp. 70–79. 55. González-Sotres, L., Mateo Domingo, C., Sánchez-Miralles, Á. and Alvar Miro, M., 2013. Large-scale MV/LV transformer substation planning considering network costs and flexible area decomposition. Power Delivery, IEEE Transactions on, 28(4), pp.2245-2253. 56. Gopiya Naik, S., Khatod, D.K. and Sharma, M.P., 2013. Optimal allocation of combined DG and capacitor for real power loss minimization in distribution networks. International Journal of Electrical Power and Energy Systems, 53, pp.967–973. Available at: http://dx.doi.org/10.1016/j.ijepes.2013.06.008. 57. Gozel, T., Hocaoglu, M.H., Eminoglu, U. and Balikci, A., 2005. Optimal placement and sizing of distributed generation on radial feeder with different static load models. In Future Power Systems, 2005 International Conference on. IEEE, pp. 2–pp. 58. Grainger, J.J. and Lee, S.H., 1981. Optimum size and location of shunt capacitors for reduction of losses on distribution feeders. Power Apparatus and Systems, IEEE Transactions on, (3), pp.1105–1118. 59. Haffner, S., Pereira, L.F.A., Pereira, L.A. and Barreto, L.S., 2008. Multistage model for distribution expansion planning with distributed generation—Part I: Problem formulation. Power Delivery, IEEE Transactions on, 23(2), pp.915–923. 60. Haghifam, M.R. and Shahabi, M., 2002. Optimal location and sizing of HV/MV substations in uncertainty load environment using genetic algorithm. Electric Power Systems Research, 63(1), pp.37–50. 61. Hasan, I.J., Ghani, A., Ruddin, M. and Gan, C.K., 2014. Optimum MV Feeder Routing and Substation siting and rating in Distribution Network. Proceeding Book MUCET 2014 Malaysian Technical Universities Conference on Engineering & Technology, Volume 1 Engineering & Technology, pp.297-303. 62. Hogan, P.M., Rettkowski, J.D. and Bala, J.L., 2005. Optimal capacitor placement using branch and bound. In Power Symposium, 2005. Proceedings of the 37th Annual North American. IEEE, pp. 84–89. 63. Hongwei, D., Yixin, Y. and Chunhua, H., 1996. Optimal planning of distribution substation locations and sizes - model and algorithm. , 18(6), pp.353–357. 64. Hsiao, Y.-T., Chen, C.-H. and Chien, C.-C., 2004. Optimal capacitor placement in distribution systems using a combination fuzzy-GA method. International Journal of Electrical Power & Energy Systems, 26(7), pp.501–508. 65. Hsu, Y.-Y. and Chen, J.-L., 1990. Distribution planning using a knowledge-based expert system. Power Delivery, IEEE Transactions on, 5(3), pp.1514–1519. 66. Humayd, A.S. Bin and Bhattacharya, K., 2013. Comprehensive multi-year distribution system planning using back-propagation approach. IET Generation, Transmission & Distribution, 7(12), pp.1415–1425. 67. IEEE Power Engineering Society, 2007. IEEE Standard for Standard General Requirements for Liquid-Immersed Distribution , Power , and Regulating Transformers. 68. Ishak, R., Mohamed, A., Abdalla, A.N. and Che Wanik, M.Z., 2014. Optimal placement and sizing of distributed generators based on a novel MPSI index. International Journal of Electrical Power & Energy Systems, 60, pp.389–398. 69. Islam, S. and Ghani, M., 1999. Economical optimization of conductor selection in planning radial distribution networks. In Transmission and Distribution Conference. IEEE, Vol. 2, pp. 858-863). 70. Jabr, R.A., 2008. Optimal placement of capacitors in a radial network using conic and mixed integer linear programming. Electric Power Systems Research, 78(6), pp.941–948. 71. John, H.H., 1975. Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. USA: University of Michigan. Available at: http://scholar.google.com/scholar?hl=en&q=Adaptation+in+Natural+and+Artificial+Systems%3AAn+Introductory+Analysis+with+Applications+to+Biology%2C+Control%2C+and+Artificial+Intelligence+&btnG=&as_sdt=1%2C5&as_sdtp=#4 [Accessed December 19, 2012]. 72. Kalantari, M. and Kazemi, A., 2011. Placement of distributed generation unit and capacitor allocation in distribution systems using genetic algorithm. In Environment and Electrical Engineering (EEEIC), 2011 10th International Conference on. IEEE, pp. 1–5. 73. Kansal, S., Sai, B.B.R., Tyagi, B. and Kumar, V., 2011. Optimal placement of wind-based generation in distribution networks. Renewable Power Generation (RPG 2011), IET Conference on, pp.1–6. 74. Kennedy, J., 2010. Particle swarm optimization. In Encyclopedia of Machine Learning. Springer, pp. 760–766. 75. Kennedy, J. and Eberhart, R., 1995. Particle swarm optimization. Proceedings of ICNN’95 - International Conference on Neural Networks, 4, pp.1942–1948. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=488968. 76. Kersting, W., 2001. Radial distribution test feeders. Power Engineering Society Winter Meeting, IEEE, 2, pp.908–912. 77. Khalesi, N. and Haghifam, M.-R., 2009. Application of dynamic programming for distributed generation allocation. Electrical Power & Energy Conference (EPEC), 2009 IEEE, pp.1–6. 78. Khator, S.K. and Leung, L.C., 1997. Power distribution planning: a review of models and issues. IEEE Transactions on Power Systems, 12(3), pp.1151–1159. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=630455. 79. Khodr, H.M., Gomez, J.F., Barnique, L., Vivas, J.H., Paiva, P., Yusta, J.M. and Urdaneta, A.J., 2002. A linear programming methodology for the optimization of electric power-generation schemes. Power Systems, IEEE Transactions on, 17(3), pp.864–869. 80. Khodr, H.M., Olsina, F.G., Jesus, P.M. and Yusta, J.M., 2008. Maximum savings approach for location and sizing of capacitors in distribution systems. Electric Power Systems Research, 78(7), pp.1192–1203. 81. Khodr, H.M., Yusta, J.M., Vale, Z. and Ramos, C., 2008. An efficient method for optimal location and sizing of fixed and switched shunt capacitors in large distribution systems. In Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE. IEEE, pp. 1–9. 82. Kim, K.-H., Lee, Y.-J., Rhee, S.-B., Lee, S.-K. and You, S.-K., 2002. Dispersed generator placement using fuzzy-GA in distribution systems. In Power Engineering Society Summer Meeting, 2002 IEEE. IEEE, pp. 1148–1153. 83. Kirkpatrick, S. and Vecchi, M.P., 1983. Optimization by simmulated annealing. science, 220(4598), pp.671–680. 84. Koutsoukis, N.C., Georgilakis, P.S. and Hatziargyriou, N.D., 2014. A Tabu search method for distribution network planning considering distributed generation and uncertainties. In Probabilistic Methods Applied to Power Systems (PMAPS), 2014 International Conference on. IEEE, pp. 1–6. 85. Kumar, A. and Gao, W., 2010. Optimal distributed generation location using mixed integer non-linear programming in hybrid electricity markets. IET generation, transmission & distribution, 4(2), pp.281–298. 86. Lakervi, E. and Holmes, E.J., 1995. Electricity distribution network design, IET. 87. Lin, L., Zhu, C., Wang, Q. and Zeng, J., 2013. Active power economic dispatch of wind farm cluster based on integer linear programming. In PowerTech (POWERTECH), 2013 IEEE Grenoble. IEEE, pp. 1–6. 88. Liu, C.-M., Kao, R.-L. and Wang, A.-H., 1994. Solving location-allocation problems with rectilinear distances by simulated annealing. Journal of the Operational Research Society, pp.1304–1315. 89. Liu, Z. and Zhang, J., 2007. Optimal planning of substation locating and sizing based on refined multi-team PSO algorithm. In Zhongguo Dianji Gongcheng Xuebao(Proceedings of the Chinese Society of Electrical Engineering). pp. 105–111. 90. Lo, K.L. and Nashid, I., 1996. Interactive expert system for optimal design of electricity distribution systems. IEE Proceedings-Generation, Transmission and Distribution, 143(2), pp.151–156. 91. Mady, I., 2009. Optimal sizing of capacitor banks and distributed generation in distorted distribution networks by genetic algorithms. 20th International Conference on Electricity Distribution, CIRED, pp.8–11. 92. Masoum, M. a. S., Ladjevardi, M., Jafarian, a. and Fuchs, E.F., 2004. Optimal Placement, Replacement and Sizing of Capacitor Banks in Distorted Distribution Networks by Genetic Algorithms. IEEE Transactions on Power Delivery, 19(4), pp.1794–1801. 93. Mazhari, S.M. and Monsef, H., 2013. Dynamic sub-transmission substation expansion planning using learning automata. Electric Power Systems Research, 96, pp.255–266. 94. Medeiros, M., 2011. A memetic algorithm based on mixed ant colony optimization and genetic algorithm for optimal capacitor placement. 16th International Conference on Intelligent System Application to Power Systems (ISAP), pp.1–6. 95. Miranda, V., Ranito, J. V and Proenca, L.M., 1994. Genetic algorithms in optimal multistage distribution network planning. IEEE Transactions on Power Systems, 9(4), pp.1927–1933. 96. Moradi, A. and Fotuhi-Firuzabad, M., 2008. Optimal switch placement in distribution systems using trinary particle swarm optimization algorithm. Power Delivery, IEEE Transactions on, 23(1), pp.271–279. 97. Moradi, M.H. and Abedinie, M., 2010. A combination of Genetic Algorithm and Particle Swarm Optimization for optimal DG location and sizing in distribution systems. 2010 Conference Proceedings IPEC, pp.858–862. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5697086. 98. Moradi, M.H., Zeinalzadeh, A., Mohammadi, Y. and Abedini, M., 2014. An efficient hybrid method for solving the optimal sitting and sizing problem of DG and shunt capacitor banks simultaneously based on imperialist competitive algorithm and genetic algorithm. International Journal of Electrical Power & Energy Systems, 54, pp.101–111. 99. Nahman, J.M. and Peric, D.M., 2008. Optimal planning of radial distribution networks by simulated annealing technique. Power Systems, IEEE Transactions on, 23(2), pp.790–795. 100. Nahman, J.M.. and Peric, D.M.., 2008. Optimal Planning of Radial Distribution Networks by Simulated Annealing Technique. IEEE Transactions on Power Systems, 23(2), pp.790–795. 101. Najafi, S., Hosseinian, S.H., Abedi, M., Vahidnia, a. and Abachezadeh, S., 2009. A Framework for Optimal Planning in Large Distribution Networks. IEEE Transactions on Power Systems, 24(2), pp.1019–1028. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4808226. 102. Nara, K., Hayashi, Y., Ikeda, K. and Ashizawa, T., 2001. Application of tabu search to optimal placement of distributed generators. In Power Engineering Society Winter Meeting, 2001. IEEE. IEEE, pp. 918–923. 103. Navarro, A. and Rudnick, H., 2009. Large-Scale Distribution Planning—Part II: Macro-Optimization With Voronoi’s Diagram And Tabu Search. Power Systems, IEEE Transactions on, 24(2), pp.752–758. 104. Nazar, M.S., Haghifam, M.R. and Nažar, M., 2012. A scenario driven multiobjective Primary–Secondary Distribution System Expansion Planning algorithm in the presence of wholesale–retail market. International Journal of Electrical Power & Energy Systems, 40(1), pp.29–45. 105. Nerves, A. and Savet, F., 2006. Voltage and reactive-power control optimization in a distribution system. IEEE Region 10 Conference, TENCON 2006, pp.1–4. 106. Niknam, T., 2005. Optimal Operation of Distribution System with Regard to Distributed Generation : A Comparison of Evolutionary Methods. , pp.2690–2697. 107. Niknam, T., Taheri, S.I., Aghaei, J., Tabatabaei, S. and Nayeripour, M., 2011. A modified honey bee mating optimization algorithm for multiobjective placement of renewable energy resources. Applied Energy, 88(12), pp.4817–4830. 108. Norton, B., 1999. Renewable electricity-what is the true cost? Power Engineering Journal, 13(1), pp.6–12. 109. De Oliveira, L.W., Carneiro Jr, S., de Oliveira, E.J., Pereira, J.L.R., Silva Jr, I.C. and Costa, J.S., 2010. Optimal reconfiguration and capacitor allocation in radial distribution systems for energy losses minimization. International Journal of Electrical Power & Energy Systems, 32(8), pp.840–848. 110. Onate Yumbla, P.E., Ramirez, J.M. and Coello Coello, C.A., 2008. Optimal power flow subject to security constraints solved with a particle swarm optimizer. Power Systems, IEEE Transactions on, 23(1), pp.33–40. 111. Paiva, P.C., Khodr, H.M., Domínguez-Navarro, J.A., Yusta, J.M. and Urdaneta, A.J., 2005. Integral planning of primary-secondary distribution systems using mixed integer linear programming. Power Systems, IEEE Transactions on, 20(2), pp.1134–1143. 112. Parada, V., Ferland, J.A., Arias, M. and Daniels, K., 2004. Optimization of electrical distribution feeders using simulated annealing. Power Delivery, IEEE Transactions on, 19(3), pp.1135–1141. 113. Parada, V., Ferland, J.A., Arias, M., Schwarzenberg, P. and Vargas, L.S., 2010. Heuristic determination of distribution trees. Power Delivery, IEEE Transactions on, 25(2), pp.861–869. 114. Park, J.-B., Jeong, Y.-W., Shin, J.-R. and Lee, K.Y., 2010. An improved particle swarm optimization for nonconvex economic dispatch problems. Power Systems, IEEE Transactions on, 25(1), pp.156–166. 115. Pearl, J., 1983. Heuristics: Intelligent Search Strategies for Computer Problem Solving. 116. Ponnavaikko, N., Rao, K.S. and Venkata, S.S., 1987. Distribution system planning through a quadratic mixed integer programming approach. Power Delivery, IEEE Transactions on, 2(4), pp.1157–1163. 117. Popović, Ž.N., Kerleta, V.D. and Popović, D.S., 2014. Hybrid simulated annealing and mixed integer linear programming algorithm for optimal planning of radial distribution networks with distributed generation. Electric Power Systems Research, 108, pp.211–222. 118. Popović, Ž.N. and Popović, D.S., 2010. Graph theory based formulation of multi-period distribution expansion problems. Electric Power Systems Research, 80(10), pp.1256–1266. 119. Puttgen, H.B., Macgregor, P.R. and Lambert, F.C., 2003. Distributed generation: Semantic hype or the dawn of a new era? Power and Energy Magazine, IEEE, 1(1), pp.22–29. 120. Ramirez-Rosado, I.J. and Bernal-Agustin, J.L., 1998. Genetic algorithms applied to the design of large power distribution systems. Power Systems, IEEE Transactions on, 13(2), pp.696–703. 121. Ramírez-Rosado, I.J. and Domínguez-Navarro, J.A., 2006. New multiobjective tabu search algorithm for fuzzy optimal planning of power distribution systems. Power Systems, IEEE Transactions on, 21(1), pp.224–233. 122. Rao, K.S. and Rao, M.N., 2012. Multiple distributed generator allocation by Harmony search algorithm for loss reduction. Emerging Trends in Electrical Engineering and Energy Management (ICETEEEM), 2012 International Conference on, pp.59–64. 123. Rau, N.S. and Wan, Y., 1994. Optimum location of resources in distributed planning. Power Systems, IEEE Transactions on, 9(4), pp.2014–2020. 124. Red, C.I., Wille-haussmann, B. and Tenbohlen, S., 2009. Paper 0779 Grid definition. , (0779), pp.8–11. 125. Reeves, C.R., 1993. Modern heuristic techniques for combinatorial problems, John Wiley & Sons, Inc. 126. Resk Ebrahim Uosef, 2011. The impact of distributed generation on secondary networks.Polytechnc Institute of New York University, PhD Thesis. 127. Rotaru, F., Chicco, G., Grigoras, G. and Cartina, G., 2012. Two-stage distributed generation optimal sizing with clustering-based node selection. International Journal of Electrical Power & Energy Systems, 40(1), pp.120–129. 128. Roy, R. and Ghoshal, S.P., 2008. A novel crazy swarm optimized economic load dispatch for various types of cost functions. International Journal of Electrical Power & Energy Systems, 30(4), pp.242–253. 129. Sedghi, M., Aliakbar-Golkar, M. and Haghifam, M.-R., 2013. Distribution network expansion considering distributed generation and storage units using modified PSO algorithm. International Journal of Electrical Power & Energy Systems, 52, pp.221–230. 130. Sepasian, M.S., Seifi, H., Foroud, A.A., Hosseini, S.H. and Kabir, E.M., 2006. A new approach for substation expansion planning. Power Systems, IEEE Transactions on, 21(2), pp.997–1004. 131. Sirjani, R., Mohamed, A. and Shareef, H., 2011. An improved harmony search algorithm for optimal capacitor placement in radial distribution systems. 5th International Power Engineering and Optimization Conference (PEOCO2011),IEEE, (June), pp.6–7. 132. Sirjani, R., Mohamed, A. and Shareef, H., 2011. Optimal Capacitor Placement in Three-Phase Distribution Systems Using Improved Harmony Search Algorithm. International Review of Electrical Engineering, 6(4), pp.1783–1793. 133. Smith, J.W., Dugan, R. and Sunderman, W., 2011. Distribution modeling and analysis of high penetration PV. 2011 IEEE Power and Energy Society General Meeting, pp.1–7. 134. Stützle, T.G., 1999. Local search algorithms for combinatorial problems: analysis, improvements, and new applications, Infix Sankt Augustin, Germany. 135. Sudhakar, T.D., 2012. Power Restoration in Distribution Network Using MST Algorithms. INTECH Open Access Publisher. 136. Taher, S.A., Karimian, A. and Hasani, M., 2011. A new method for optimal location and sizing of capacitors in distorted distribution networks using PSO algorithm. Simulation Modelling Practice and Theory, 19(2), pp.662–672. 137. Temraz, H.K. and Quintana, V.H., 1993. Distribution system expansion planning models: an overview. Electric power systems research, 26(1), pp.61–70. 138. Thompson, G.L. and Wall, D.L., 1981. A branch and bound model for choosing optimal substation locations. Power Apparatus and Systems, IEEE Transactions on, (5), pp.2683–2688. 139. TNB Electricity Supply Application Handbook, 2007. TENAGA NASIONAL BERHAD, 140. Umapathy, P., Venkataseshaiah, C. and Arumugam, M.S., 2010. Particle Swarm Optimization with Various Inertia Weight Variants for Optimal Power Flow Solution. Discrete Dynamics in Nature and Society, 2010, pp.1–15. 141. Del Valle, Y., Venayagamoorthy, G.K., Mohagheghi, S., Hernandez, J.-C. and Harley, R.G., 2008. Particle swarm optimization: basic concepts, variants and applications in power systems. IEEE Transactions on Evolutionary Computation, 12(2), pp.171–195. 142. Wall, D.L., Thompson, G.L. and Northcote-Green, J.E.D., 1979. An optimization model for planning radial distribution networks. Power Apparatus and Systems, IEEE Transactions on, (3), pp.1061–1068. 143. WANG, C., Liu, T. and XIE, Y., 2006. Substation Locating and Sizing Based on Hybrid Genetic Algorithm [J]. Automation of Electric Power Systems, 6, 007. 144. Wang, C. and Nehrir, M.H., 2004. Analytical approaches for optimal placement of distributed generation sources in power systems. Power Systems, IEEE Transactions on, 19(4), pp.2068–2076. 145. Wang, D.-C., Ochoa, L.F. and Harrison, G.P., 2011. Modified GA and data envelopment analysis for multistage distribution network expansion planning under uncertainty. Power Systems, IEEE Transactions on, 26(2), pp.897–904. 146. Wang, Z. and Xu, Q., 2011. On distribution system planning method for reliability and its application. 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), pp.1727–1731. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5994176. 147. Wei, H., Sasaki, H., Kubokawa, J. and Yokoyama, R., 2000. Large scale hydrothermal optimal power flow problems based on interior point nonlinear programming. Power Systems, IEEE Transactions on, 15(1), pp.396–403. 148. Willis, H.L., 2004. Power distribution planning reference book, CRC press. 149. Wu, W.C., Zhang, B.M. and Lo, K.L., 2010. Capacitors dispatch for quasi minimum energy loss in distribution systems using a loop-analysis based method. International Journal of Electrical Power & Energy Systems, 32(6), pp.543–550. 150. Yang, G.Y., Hovland, G., Majumder, R. and Dong, Z.Y., 2007. TCSC allocation based on line flow based equations via mixed-integer programming. Power Systems, IEEE Transactions on, 22(4), pp.2262–2269. 151. Zarate, L.A., Castro, C.A., Ramos, J.L.M. and Ramos, E.R., 2006. Fast computation of voltage stability security margins using nonlinear programming techniques. Power Systems, IEEE Transactions on, 21(1), pp.19–27. 152. Zehar, K. and Sayah, S., 2008. Optimal power flow with environmental constraint using a fast successive linear programming algorithm: Application to the algerian power system. Energy Conversion and Management, 49(11), pp.3362–3366. 153. Ziari, I., 2011. Planning of distribution networks for medium voltage and low voltage. PhD Thesis 154. Ziari, I. and Jalilian, A., 2010. A new approach for allocation and sizing of multiple active power-line conditioners. Power Delivery, IEEE Transactions on, 25(2), pp.1026–1035. 155. Ziari, I., Ledwich, G. and Ghosh, A., 2011. Optimal Control of Distributed Generators and Capacitors by Hybrid DPSO. Optimal Control of Distributed Generators and Capacitors by Hybrid DPSO, ww44(e), p.weww. 156. Ziari, I., Ledwich, G. and Ghosh, A., 2011. Optimal integrated planning of MV–LV distribution systems using DPSO. Electric Power Systems Research, 81(10), pp.1905–1914.

Electricity distribution network for low and medium voltages based on evolutionary approach optimization

Similar Items