A Novel Solution Method for the Distribution Network Reconfiguration Problem based on an Objective Function and considering the Cost of Electricity Transmission

Authors

  • Nguyen Tung Linh Faculty of Control and Automation, Electric Power University, Vietnam https://orcid.org/0000-0003-2645-4599
  • Pham Vu Long Institute of Energy, 6 Ton That Tung, Hanoi, Vietnam | Faculty of Control and Automation, Electric Power University, Vietnam
Volume: 13 | Issue: 6 | Pages: 12366-12372 | December 2023 | https://doi.org/10.48084/etasr.6568

Abstract

The problem of distribution reconfiguration is an important issue in the optimal operation of distribution networks. Nowadays, with the diverse development of renewable energy sources, the uncertainty of the load becomes more complex, and the need for competitive retail electricity markets is more evident. This paper presents an optimal solution to this problem, utilizing the global advantage of the simulated annealing algorithm, improving the time parameter, and combining it with the rapid mutation ability of the genetic algorithm. Simultaneously, the Zbus, EBE, and PS models were integrated to optimize the costs, considering transmission costs under constraints related to taxes and economic indicators when connected to the distribution grid. The proposed method was simulated and tested on the IEEE 33-node standard power grid with three different scenarios. The simulation results showed that the proposed method provides optimal results, which can be applied to calculate the optimal operation of the distribution grid when participating in retail electricity markets.

Keywords:

simulation annealing algorithm, genetic algorithms, distribution network reconfiguration, transmission system usage, transmission cost allocation

Downloads

Download data is not yet available.

References

M. E. Baran and F. F. Wu, "Optimal capacitor placement on radial distribution systems," IEEE Transactions on Power Delivery, vol. 4, no. 1, pp. 725–734, Jan. 1989.

M. E. Baran and F. F. Wu, "Network reconfiguration in distribution systems for loss reduction and load balancing," IEEE Transactions on Power Delivery, vol. 4, no. 2, pp. 1401–1407, Apr. 1989.

M. Mahdavi, H. H. Alhelou, N. D. Hatziargyriou, and F. Jurado, "Reconfiguration of Electric Power Distribution Systems: Comprehensive Review and Classification," IEEE Access, vol. 9, pp. 118502–118527, 2021.

T. L. Duong and T. T. Nguyen, "Network Reconfiguration for an Electric Distribution System with Distributed Generators based on Symbiotic Organisms Search," Engineering, Technology & Applied Science Research, vol. 9, no. 6, pp. 4925–4932, Dec. 2019.

Z. M. Zohrabad, "Application of Hybrid HS and Tabu Search Algorithm for Optimal Location of FACTS Devices to Reduce Power Losses in Power Systems," Engineering, Technology & Applied Science Research, vol. 6, no. 6, pp. 1217–1220, Dec. 2016.

H. Xing and X. Sun, "Distributed Generation Locating and Sizing in Active Distribution Network Considering Network Reconfiguration," IEEE Access, vol. 5, pp. 14768–14774, 2017.

Y. K. Wu, C. Y. Lee, L. C. Liu, and S. H. Tsai, "Study of Reconfiguration for the Distribution System With Distributed Generators," IEEE Transactions on Power Delivery, vol. 25, no. 3, pp. 1678–1685, Jul. 2010.

D. P. Bernardon, A. P. C. Mello, L. L. Pfitscher, L. N. Canha, A. R. Abaide, and A. A. B. Ferreira, "Real-time reconfiguration of distribution network with distributed generation," Electric Power Systems Research, vol. 107, pp. 59–67, Feb. 2014.

R. S. 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, vol. 28, no. 1, pp. 317–325, Oct. 2013.

J. Z. Zhu, "Optimal reconfiguration of electrical distribution network using the refined genetic algorithm," Electric Power Systems Research, vol. 62, no. 1, pp. 37–42, May 2002.

C. Vazquez, I. Pérez-Arriaga, and L. Olmos, "On the Selection of the Slack Bus in Mechanisms for Transmission Network Cost Allocation that are Based on Network Utilization." Rochester, NY, Jun. 22, 2002.

A. Zidan and E. F. El-Saadany, "Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation," Energy, vol. 59, pp. 698–707, Sep. 2013.

D. Kirschen, R. Allan, and G. Strbac, "Contributions of individual generators to loads and flows," IEEE Transactions on Power Systems, vol. 12, no. 1, pp. 52–60, Oct. 1997.

J. C. López, M. Lavorato, and M. J. Rider, "Optimal reconfiguration of electrical distribution systems considering reliability indices improvement," International Journal of Electrical Power & Energy Systems, vol. 78, pp. 837–845, Jun. 2016.

I. Benitez Cattani, E. Chaparro, and B. Barán, "Distribution System Operation and Expansion Planning using Network Reconfiguration," IEEE Latin America Transactions, vol. 18, no. 05, pp. 845–852, Feb. 2020.

S. Civanlar, J. J. Grainger, H. Yin, and S. S. H. Lee, "Distribution feeder reconfiguration for loss reduction," IEEE Transactions on Power Delivery, vol. 3, no. 3, pp. 1217–1223, Jul. 1988.

Y. J. Jeon and J. C. Kim, "Application of simulated annealing and tabu search for loss minimization in distribution systems," International Journal of Electrical Power & Energy Systems, vol. 26, no. 1, pp. 9–18, Jan. 2004.

P. J. M. van Laarhoven and E. H. L. Aarts, "Simulated annealing," in Simulated Annealing: Theory and Applications, P. J. M. van Laarhoven and E. H. L. Aarts, Eds. Dordrecht, Netherlands: Springer Netherlands, 1987, pp. 7–15.

Y. R. Elhaddad, "Combined Simulated Annealing and Genetic Algorithm to Solve Optimization Problems," International Journal of Computer and Information Engineering, vol. 6, no. 8, pp. 1047–1049, Aug. 2012.

T. L. Duong, T. T. Nguyen, N. A. Nguyen, and T. Kang, "Available Transfer Capability Determination for the Electricity Market using Cuckoo Search Algorithm," Engineering, Technology & Applied Science Research, vol. 10, no. 1, pp. 5340–5345, Feb. 2020.

N. T. Linh and P. T. Cat, "Improving of Simulated Annealing Algorithm for Network Reconfiguration problem considering the Impact of Distributed Generation," Ciencia e Tecnica Vitivinicola Journal, vol. 31, no. 4, 2016, Art. no. A0hY6.

M. Ilic, F. Galiana, and L. Fink, Power Systems Restructuring: Engineering and Economics. New York, NY, USA: Springer Science & Business Media, 2013.

F. D. Galiana, A. J. Conejo, and H. A. Gil, "Transmission network cost allocation based on equivalent bilateral exchanges," IEEE Transactions on Power Systems, vol. 18, no. 4, pp. 1425–1431, Aug. 2003.

H. A. Gil, F. D. Galiana, and A. J. Conejo, "Multiarea transmission network cost allocation," IEEE Transactions on Power Systems, vol. 20, no. 3, pp. 1293–1301, Dec. 2005.

A. J. Conejo, J. Contreras, D. A. Lima, and A. Padilha-Feltrin, "Zbus Transmission Network Cost Allocation," IEEE Transactions on Power Systems, vol. 22, no. 1, pp. 342–349, Oct. 2007.

"MATLAB." https://www.mathworks.com/products/matlab.html.

"PSS®SINCAL – simulation software for analysis and planning of all network types," siemens.com Global Website. https://www.siemens.com/global/en/products/energy/grid-software/planning/pss-software/pss-sincal.html.

J. Bialek, "Topological generation and load distribution factors for supplement charge allocation in transmission open access," IEEE Transactions on Power Systems, vol. 12, no. 3, pp. 1185–1193, Dec. 1997.

J. S. Savier and D. Das, "Impact of Network Reconfiguration on Loss Allocation of Radial Distribution Systems," IEEE Transactions on Power Delivery, vol. 22, no. 4, pp. 2473–2480, Jul. 2007.

D. Shirmohammadi and H. W. Hong, "Reconfiguration of electric distribution networks for resistive line losses reduction," IEEE Transactions on Power Delivery, vol. 4, no. 2, pp. 1492–1498, Apr. 1989.

Downloads

How to Cite

[1]
Linh, N.T. and Long, P.V. 2023. A Novel Solution Method for the Distribution Network Reconfiguration Problem based on an Objective Function and considering the Cost of Electricity Transmission. Engineering, Technology & Applied Science Research. 13, 6 (Dec. 2023), 12366–12372. DOI:https://doi.org/10.48084/etasr.6568.

Metrics

Abstract Views: 297
PDF Downloads: 306

Metrics Information

Most read articles by the same author(s)