Identifying the Basic Challenges in Determining the Optimal Tie Points of Real Distribution Networks and Providing a Solution

Document Type : Research Paper

Authors

1 Semnan Province Electric Power Distribution Company, Semnan, Iran

2 Electrical and Computer Engineering Faculty, Semnan University, Semnan, Iran

Abstract

One of the factors of high losses in the distribution network is its radial utilization. Therefore, reducing losses in distribution networks is one of the goals of operators. For this purpose, various measures have been thought out, among which, network reconfiguration is the most economical and fastest possible method. This process can reduce losses in the distribution network by adjusting the load of medium voltage distribution feeders. In addition, the increasing penetration of distributed generation (DG) can play a significant role. Finding suitable tie points in real distribution networks is difficult due to the large search space in which the number of impossible answers is much higher than the possible answers. This article aims to provide a method to find the optimal tie points among the existing tie points in the real medium voltage distribution in the presence/absence of DGs to reduce network losses. For this purpose, first, the basic challenges to solve this problem are identified and then an effective strategy is used based on the innovative dynamic switching set heuristic algorithm (DSSHA) considering the network constraints as a solution to the problem. Using this algorithm will limit the search space, reduce the volume of calculations and save time. This algorithm is written as a module with Python programming language, which can be implemented on any distribution network.

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Main Subjects


[1] A.S. Reddy, M.D. Reddy, and Y.K. Reddy. "Feeder reconfiguration of distribution systems for loss reduction and emissions reduction using MVO algorithm." Majlesi Journal of Electrical Engineering 12, no. 2 (2018): 1-8.
[2] S.H. Mirhoseini, S.M. Hosseini, M. Ghanbari, and M. Ahmadi. "A new improved adaptive imperialist competitive algorithm to solve the reconfiguration problem of distribution systems for loss reduction and voltage profile improvement." International Journal of Electrical Power & Energy Systems 55 (2014): 128-143.
[3] A. Zidan, and E.F. El-Saadany. "Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation." Energy 59 (2013): 698-707.
[4] R.E. Brown, and L.A. Freeman. "Analyzing the reliability impact of distributed generation." In 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No. 01CH37262), vol. 2, pp. 1013-1018. IEEE, 2001.
[5] A.G. Patel, and C. Patel. "Distribution network reconfiguration for loss reduction." In 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), pp. 3937-3941. IEEE, 2016.
[6] T.T. Nguyen, T.T. Nguyen, L.T. Duong, and V.A. Truong. "An effective method to solve the problem of electric distribution network reconfiguration considering distributed generations for energy loss reduction." Neural Computing and Applications 33 (2021): 1625-1641.
[7] A. Abbaskhani-Davanloo, M. Amini, M. Sadegh Modarresi, and F. Jafarishiadeh. "Distribution system reconfiguration for loss reduction incorporating load and renewable generation uncertainties." In 2019 IEEE Texas Power and Energy Conference (TPEC), pp. 1-6. IEEE, 2019.
[8] V. Glamocanin. "Optimal loss reduction of distributed networks." IEEE Transactions on Power Systems 5, no. 3 (1990): 774-782.
[9] T.E. McDermott, I. Drezga, and R.P. Broadwater. "A heuristic nonlinear constructive method for distribution system reconfiguration." IEEE Transactions on Power Systems 14, no. 2 (1999): 478-483.
[10] M.H. Haque. "Improvement of power delivery efficiency of distribution systems through loss reduction." In 2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No. 00CH37077), vol. 4, pp. 2739-2744. IEEE, 2000.
[11] H.C. Chin, and K.Y. Huang. "A simple distribution reconfiguration algorithm for loss minimization." In PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No. 00EX409), vol. 2, pp. 607-611. IEEE, 2000.
[12] A. Ebrahimi, and S. Mohseni. "Multipurpose reconfiguration of distribution systems using fuzzy reasoning approach." In 16th International Conference and Exhibition on Electricity Distribution, 2001. Part 1: Contributions. CIRED.(IEE Conf. Publ No. 482), vol. 4, pp. 5-pp. IET, 2001.
[13] S.S. Souza, R. Romero, J. Pereira, and J. Tomé Saraiva. "Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios." In 2015 IEEE Eindhoven PowerTech, pp. 1-5. Ieee, 2015.
[14] R. Rajaram, K. Sathish Kumar, S. Prabhakar Karthikeyan, and J. Edward Belwin. "Distribution System Reconfiguration for Loss Minimization Using Modified Artificial Neural Network Approach of 16 Bus and 33 Bus Standard Test Systems with a Compensator." Applied Mechanics and Materials 573 (2014): 767-776.
[15] A. Shang, and S. Yan. "Power System Reconfiguration Using Graph Trace Analysis and Multi-agent System." In International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2015), pp. 501-505. Atlantis Press, 2015.
[16] R. Pegado, Z. Ñaupari, Y. Molina, and C. Castillo. "Radial distribution network reconfiguration for power losses reduction based on improved selective BPSO." Electric Power Systems Research 169 (2019): 206-213.
[17] T.T. Nguyen, and A.V. Truong. "Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm." International Journal of Electrical Power & Energy Systems 68 (2015): 233-242.
[18] 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 28, no. 1 (2012): 317-325.
[19] D.L. Duan, X.D. Ling, X.Y. Wu, and B. Zhong. "Reconfiguration of distribution network for loss reduction and reliability improvement based on an enhanced genetic algorithm." International Journal of Electrical Power & Energy Systems 64 (2015): 88-95.
[20] L.C. Daniel, I. Hafeezulah Khan, and S. Ravichandran. "Distribution network reconfiguration for loss reduction using ant colony system algorithm." In 2005 Annual IEEE India Conference-Indicon, pp. 619-622. IEEE, 2005.
 
Volume 23, Special Issue 81
Celebrating the 50th Anniversary of Semnan University- In Progress
July 2025
Pages 175-188
  • Receive Date: 06 June 2024
  • Revise Date: 21 October 2024
  • Accept Date: 04 November 2024