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Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation

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  • Zidan, Aboelsood
  • El-Saadany, Ehab F.

Abstract

The interconnection of renewable energy sources with distribution systems is attracting increasing interest because these renewable sources are inexhaustible and nonpolluting. Wind and photovoltaic are among the most mature of these energy sources, and their penetration continues to increase. In this paper a method based on GA (genetic algorithm) is presented to investigate the distribution system reconfiguration problem taking into consideration the effect of load variation and the stochastic power generation of renewable DG (distributed generators units). The presented method determines the annual distribution network reconfiguration scheme considering switching operation costs in order to minimize annual energy losses by determining the optimal configuration for each season of the year. The uncertainties related to DG power and varying load are considered by the creation of a probabilistic generation-load model that combines all possible operating conditions of the renewable DG units with the probability of their occurrence, followed by the incorporation of this model into the reconfiguration problem. The constraints include the voltage limits, the line current limits, the radial topology, and feeding of all loads. In order to evaluate the effectiveness of the proposed method, both balanced and unbalanced distribution systems are used as case studies.

Suggested Citation

  • Zidan, Aboelsood & El-Saadany, Ehab F., 2013. "Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation," Energy, Elsevier, vol. 59(C), pages 698-707.
    • Handle: RePEc:eee:energy:v:59:y:2013:i:c:p:698-707
    DOI: 10.1016/j.energy.2013.06.061
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    7. Kavousi-Fard, Abdollah & Abbasi, Alireza & Rostami, Mohammad-Amin & Khosravi, Abbas, 2015. "Optimal distribution feeder reconfiguration for increasing the penetration of plug-in electric vehicles and minimizing network costs," Energy, Elsevier, vol. 93(P2), pages 1693-1703.
    8. Ferrari, M.L. & Cuneo, A. & Pascenti, M. & Traverso, A., 2017. "Real-time state of charge estimation in thermal storage vessels applied to a smart polygeneration grid," Applied Energy, Elsevier, vol. 206(C), pages 90-100.
    9. Esmaeeli, M. & Kazemi, A. & Shayanfar, H.A. & Haghifam, M.-R., 2015. "Multistage distribution substations planning considering reliability and growth of energy demand," Energy, Elsevier, vol. 84(C), pages 357-364.
    10. kianmehr, Ehsan & Nikkhah, Saman & Rabiee, Abbas, 2019. "Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner’s and DisCo’s perspectives," Renewable Energy, Elsevier, vol. 132(C), pages 471-485.
    11. Manvir Kaur & Smarajit Ghosh, 2017. "Effective Loss Minimization and Allocation of Unbalanced Distribution Network," Energies, MDPI, vol. 10(12), pages 1-17, November.
    12. Sedighizadeh, Mostafa & Esmaili, Masoud & Esmaeili, Mobin, 2014. "Application of the hybrid Big Bang-Big Crunch algorithm to optimal reconfiguration and distributed generation power allocation in distribution systems," Energy, Elsevier, vol. 76(C), pages 920-930.
    13. Gutiérrez-Alcaraz, G. & Galván, E. & González-Cabrera, N. & Javadi, M.S., 2015. "Renewable energy resources short-term scheduling and dynamic network reconfiguration for sustainable energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 256-264.
    14. Zidan, Aboelsood & Gabbar, Hossam A. & Eldessouky, Ahmed, 2015. "Optimal planning of combined heat and power systems within microgrids," Energy, Elsevier, vol. 93(P1), pages 235-244.
    15. Hashim, Haslenda & Ho, Wai Shin & Lim, Jeng Shiun & Macchietto, Sandro, 2014. "Integrated biomass and solar town: Incorporation of load shifting and energy storage," Energy, Elsevier, vol. 75(C), pages 31-39.
    16. Mahmoud M. Sayed & Mohamed Y. Mahdy & Shady H. E. Abdel Aleem & Hosam K. M. Youssef & Tarek A. Boghdady, 2022. "Simultaneous Distribution Network Reconfiguration and Optimal Allocation of Renewable-Based Distributed Generators and Shunt Capacitors under Uncertain Conditions," Energies, MDPI, vol. 15(6), pages 1-27, March.
    17. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah, 2015. "An efficient scenario-based stochastic programming for optimal planning of combined heat, power, and hydrogen production of molten carbonate fuel cell power plants," Energy, Elsevier, vol. 83(C), pages 734-748.
    18. Badran, Ola & Mekhilef, Saad & Mokhlis, Hazlie & Dahalan, Wardiah, 2017. "Optimal reconfiguration of distribution system connected with distributed generations: A review of different methodologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 854-867.

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