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A framework for optimal clustering of a greenfield distribution network area into multiple autonomous microgrids

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Microgrids (MGs) are recognized as cores and clusters of smart distribution networks. The optimal planning and clustering of smart low-voltage distribution networks into autonomous MGs within a greenfield area is modeled and discussed in this paper. In order to form and determine the electrical boundary of MGs set, some predefined criteria such as power mismatch, supply security and load density are defined. The network includes an external grid as backup and both dispatchable and non-dispatchable Distributed Energy Resources (DERs) as MGs resources. The proposed strategy offers optimum sizing and siting of DERs and MV substations for the autonomous operation of multiple MGs simultaneously. The imperialist competitive algorithm (ICA) is used to optimize the cost function to determine the optimal linked MG clustering boundary. To evaluate the algorithm the proposed method is applied to a greenfield area which is planned to become a mixed residential and commercial town. The MGs’ optimal border, DERs location, size and type within each MG and LV feeders route are illustrated in both graphical and tabular form.
Rocznik
Strony
219--228
Opis fizyczny
Bibliogr. 32 poz., rys., tab., wykr.
Twórcy
  • Smart Distribution Grid Research Lab, Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
  • Smart Distribution Grid Research Lab, Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
  • Electric Transmission & Distribution Research Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran;
Bibliografia
  • [1] Levelized cost calculations. Available: http://en.openei.org/apps/TCDB/levelized_cost_calculations.html.
  • [2] Tansparent cost database. Available: http://en.openei.org/apps/TCDB/, March 2015.
  • [3] Gargari E. A. and Lucas C. Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition. IEEE Congress on Evolutionary Computation, 2007.
  • [4] Khodaei A., Bahramirad S., and M. Shahidehpour. Microgrid planning under uncertainty. IEEE Transactions on Power Systems, 30(5):2417– 2425, 2015.
  • [5] S. A. Arefifar, I Mohamed Y. A. R., and M. El-Fouly T. H. Optimum microgrid design for enhancing reliability and supply-security. IEEE Transactions on Smart Grid, 4(3):1567–1575, 2013.
  • [6] Kroposki B., Lasseter R., Ise T., Morozumi S., Papathanassiou S., and Hatziargyriou N. Making microgrids work. IEEE Power and Energy Magazine, 6(3):40–53, 2008.
  • [7] I. Bae and J. Kim. Reliability evaluation of customers in a microgrid. IEEE Transactions on Power Systems, 23(3):1416–1422, 2008.
  • [8] Arya L. D., Choube S. C., and Arya R. Probabilistic reliability indices evaluation of electrical distribution system, accounting outage due to overloading and repair time omission. International Journal of Electrical Power & Energy Systems, 33(2):296–302, 2011.
  • [9] M. Fotuhi-Firuzabad and Rajabi-Ghahnavie A. An analytical method to consider dg impacts on distribution system reliability. Proceedings of the IEEE Transmission and Distribution Conference and Exhibition, pages 1–6, 2005.
  • [10] Kanchev H., Lu D., Colas F., Lazarov V., and Francois B. Energy management and operational planning of a microgrid with a pv-based active generator for smart grid applications. IEEE Transactions on Industrial Electronics, 58(10):4583–4592, 2011.
  • [11] Lasseter R. H. Smart distribution: Coupled microgrids. Proceedings of the IEEE, 99(6):1074–1082, 2011.
  • [12] Bae I. and Kim J. Reliability evaluation of customers in a microgrid. IEEE Transactions on Power Systems, 23(3):1416–1422, 2008.
  • [13] Bae I.S. and Kim J.O. Reliability evaluation of distributed generation based on operation mode. IEEE Transactions on Power Systems, 22 (2):785–790, 2007.
  • [14] Bae I.S. and Kim J.O. Reliability evaluation of customers in a microgrid. IEEE Transactions on Power Systems, 23(3):1416–1422, 2008.
  • [15] Carrasco J., Franquelo L., Bialasiewicz J., Galvan E., Guisado R., Prats M., Leon J., and Moreno-Alfonso N. Power electronic systems for the grid integration of renewable energy sources: A survey. IEEE Transactions on Power Electronics, 53(4):1002–1016, 2006.
  • [16] Basu A. K., Chowdhury S., and Chowdhury S. P. Impact of strategic deployment of CHP-based DERs on microgrid reliability. IEEE Transactions on Power Delivery, 25(3):1697–1705, 2010.
  • [17] Moslehi K. and Kumar R. A reliability perspective of the smart grid. IEEE Transactions on Smart Grid, 1(1):57–64, 2010.
  • [18] S. Kennedy and Marden M. Reliability of islanded microgrids with stochastic generation and prioritized load. IEEE Powertech, Bucharest, June 2009.
  • [19] Che L., Zhang X., M. Shahidehpour, Alabdulwahab A., and Abusorrah A. Optimal interconnection planning of community microgrids with renewable energy sources. IEEE Transactions on Smart Grid, pages 1–10, 2015.
  • [20] Guo L., Liu W., Cai J., Hong B., and Wang C. A two-stage optimal planning and design method for combined cooling, heat and power microgrid system. Energy Conversion and Management, 74:433–445, 2013.
  • [21] Khodayar M.E., Barati M., and Shahidehpour M. Integration of high reliability distribution system in microgrid operation. IEEE Transactions on Smart Grid, 3(4):1997–2006, 2012.
  • [22] Biggs N. Algebraic graph theory, 1974.
  • [23] Ravadenegh S. N., Hosseinian S. H., Abedi M., Vahidnia A., and Abachezadeh S. A framework for optimal planning in large distribution networks. IEEE Transactions on Power Systems, 24(2):1019–1028, 2009.
  • [24] Jahangiri P. and Fotuhi-Firuzabad M. Reliability assessment of distributed system with distributed generation. Proceedings of the IEEE 2nd Conference on Power and Energy, pages 1551–1556, 2008.
  • [25] Majumder R., Ghosh A., Ledwich G., and Zare F. Load sharing and power quality enhanced operation of a distribute microgrid. IET Renewable Power Generation, 3(2):109–119, 2009.
  • [26] Vallem M. R. and Mitra J. Siting and sizing of distributed generation for optimal microgrid architecture. IEEE Proceedings of the 37th Annual North American Power Symposium,, pages 611–616, 2005.
  • [27] Conti S., Nicolosi R., and Rizzo S. A. Generalized systematic approach to assess distribution system reliability with renewable distributed generators and microgrids. IEEE Transactions on Power Delivery, 27(1): 261–270, 2012.
  • [28] Kennedy S. and Marden M. Reliability of islanded microgrids with stochastic generation and prioritized load. In Proceedings of IEEE Powertech, Bucharest, 2009.
  • [29] Arefifar S.A., Mohamed Y. A. R. I, and El-Fouly T. H. M. Supplyadequacy- based optimal construction of microgrids in smart distribution systems. IEEE Transactions on Smart Grid, 3(3):1491–1502, 2012.
  • [30] M. Shahabi, Haghifam M. R., Mohamadian M., and Nabavi-Nivaki S. A. Microgrid dynamic performance improvement using a doubly fed induction wind generator. IEEE Transactions on Energy Conversion, 24(1):137–145, 2009.
  • [31] Gu W., Wu Z., Bo R., Liu W., Zhou G., Chen W., and Wu Z. Modeling, planning and optimal energy management of combined cooling, heating and power microgrid: A review. International Journal of Electrical Power & Energy Systems, 54:26–37, 2014.
  • [32] He Y. and Sharma R. Microgrid generation expansion planning using agent-based simulation. In Proceedings of IEEE Innovative Smart Grid Technologies Conference, 2013.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-de66d086-6bb1-4d31-ad2b-33269a48fd13
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