Distributed generation allocation using the genetic algorithm of Chu-Beasley and sensitivity

• Autorzy: Belati E. A. , Rosa W. M. , Rossoni P. , Garces L.P. , Prado I.F.

Identyfikatory

DOI

10.15199/48.2016.08.53

Warianty tytułu

PL

Analiza lokalizacji rozproszonych generatorów przy wykorzystaniu algorytmu generycznego Chu-Beasley

• Języki publikacji: EN

Abstrakty

EN

This paper presents a methodology for the allocation of distributed generation (DG) units to minimize active power losses in distribution networks. This methodology is based on the genetic algorithm of Chu-Beasley (GACB) and first-order sensitivity (FOS). To evaluate the different proposals of solution, instead of using Load Flow (LF), a FOS technique was used in order to directly estimate the solution of the LF. The proposed methodology was applied to three distribution systems, containing 34, 70 and 126 buses, respectively. Results obtained for the 34 bus system using GACB and FOS technique were compared with that obtained using GACB but solving the LF via Newton-Raphson (NR) method, showing the computational time gain when the FOS technique is used. For the three systems, the best locations for allocation two DG units are shown and the technical impacts in the network, i.e., active power losses and voltage profiles, are verified.

PL

W artykule opisano metodologię lokalizacji rozproszonych źródeł energii przy kryterium minimalizacji strat mocy czynnej. Metoda bazuje na algorytmie genetycznym Chu-Beasley i czułości pierwszego rzędu. Metodę sprawdzono na przykładzie trzech różnych sieci dystrybucyjnych.

Słowa kluczowe

EN

distributed generation; sensitivity analysis; genetic algorithm of Chu-Beasley

PL

generacja rozproszona; algorytm genetyczny Chu-Beasley

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2016
• Tom: R. 92, nr 8
• Strony: 194--199
• Opis fizyczny: Bibliogr. 17 poz., rys., tab., wykr.

Twórcy

autor

Belati E. A.

• CECS, Federal University of ABC, Rua Santa Adélia, 166, CEP 09,210- 170, Santo Andre - SP, Brazil

autor

Rosa W. M.

• CECS, Federal University of ABC, Rua Santa Adélia, 166, CEP 09,210- 170, Santo Andre - SP, Brazil

autor

Rossoni P.

• CECS, Federal University of ABC, Rua Santa Adélia, 166, CEP 09,210- 170, Santo Andre - SP, Brazil

autor

Garces L.P.

• EMC, Federal University of Goias (UFG), Av. Universitária, 1488, 74605-010, Setor Leste Universitário, Goiânia, GO, Brazil

autor

Prado I.F.

• DCET, State University of Santa Cruz (UESC), Rod. Jorge Amado, km 16, 45662-900, Bairro: Salobrinho, Ilhéus, BA, Brazil

Bibliografia

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• [3] A. Kazemi and M. Sadeghi, "Distributed Generation Allocation for Loss Reduction and Voltage Improvement," in Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia- Pacific, 2009, pp. 1-6.
• [4] N. Acharya, P. Mahat, and N. Mithulananthan, "An analytical approach for DG allocation in primary distribution network," International Journal of Electrical Power & Energy Systems, vol. 28, pp. 669-678, 12// 2006.
• [5] A. A. Abou El-Ela, S. M. Allam, and M. M. Shatla, "Maximal optimal benefits of distributed generation using genetic algorithms," Electric Power Systems Research, vol. 80, pp. 869-877, 7// 2010.
• [6] G. Carpinelli, G. Celli, F. Pilo, and A. Russo, "Distributed generation siting and sizing under uncertainty," in Power Tech Proceedings, 2001 IEEE Porto, 2001, p. 7 pp. vol.4.
• [7] W. F. Tinney and C. E. Hart, "Power Flow Solution by Newton's Method," IEEE Transactions on Power Apparatus and Systems, vol. PAS-86, pp. 1449-1460, 1967.
• [8] Y. Hui, W. Fushuan, W. Liping, and S. N. Singh, "Newton- Downhill algorithm for distribution power flow analysis," in Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International, 2008, pp. 1628-1632.
• [9] W. M. D. Rosa and E. A. Belati, "First-Order Sensitivity Applied in Power Distribution System," Przeglad Elektrotechniczny, vol. 7, 2014.
• [10] J. H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence: University of Michigan Press, 1975.
• [11] P. C. Chu and J. E. Beasley, "A genetic algorithm for the generalised assignment problem," Computers & Operations Research, vol. 24, pp. 17-23, 1997.
• [12] I. D. J. Silva, M. J. Rider, R. Romero, and C. A. Murari, "Transmission network expansion planning considering uncertainness in demand," in Power Engineering Society General Meeting, 2005. IEEE, 2005, pp. 1424-1429 Vol. 2.
• [13] R. Romero, M. J. Rider, and I. d. J. Silva, "A Metaheuristic to Solve the Transmission Expansion Planning," Power Systems, IEEE Transactions on, vol. 22, pp. 2289-2291, 2007.
• [14] I. de J Silva, M. J. Rider, R. Romero, A. V. Garcia, and C. A. Murari, "Transmission network expansion planning with security constraints," Generation, Transmission and Distribution, IEE Proceedings-, vol. 152, pp. 828-836, 2005.
• [15] M. Chis, M. M. A. Salama, and S. Jayaram, "Capacitor placement in distribution systems using heuristic search strategies," Generation, Transmission and Distribution, IEE Proceedings-, vol. 144, pp. 225-230, 1997.
• [16] M. E. Baran and F. F. Wu, "Optimal capacitor placement on radial distribution systems," Power Delivery, IEEE Transactions on, vol. 4, pp. 725-734, 1989.
• [17] I. F. d. Prado, "Alocação de Geração Distribuída Utilizando o Algoritmo Genético de Chu-Beasley e Índices de Sensibilidade," Master, Electrical Engineering, Federal University of ABC Santo André - Brazil, 2013.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.