Mitigating Phase Imbalance in Distribution Networks with Optimal DSTATCOM Placement using Hybrid Bacteria Foraging and Cuckoo Search Algorithm

References

[1] Adefarati, T., & Bansal, R. C. (2017). Reliability and economic assessment of a microgrid power system with the integration of renewable energy resources. Applied Energy, 206, 911–933.

[2] Gupta, N., Bansal, R. C., & Kumar, A. (2019). Distributed generation system planning: A review of techno-economic aspects. Renewable and Sustainable Energy Reviews, 104, 1–18.

[3] Mandal, P., Das, B., & Kothari, D. P. (2020). Voltage imbalance mitigation using custom power devices: An overview. Electric Power Systems Research, 189, 106672.

[4] Okonkwo, P. U., Yusuf, S. M., & Ochije, F. (2021). Technical loss reduction in power distribution networks in Nigeria using distributed compensation. Nigerian Journal of Electrical Engineering and Technology, 5(2), 102–110.

[5] Jain, S. K., & Singh, B. (2016). Performance comparison of grid interfaced distributed generation system with and without DSTATCOM in weak grid conditions. IET Renewable Power Generation, 10(4), 495–503.

[6] Sahu, R. K., & Panda, S. (2015). Hybrid optimization algorithm for DSTATCOM allocation in distribution systems. Energy Systems, 6(1), 1–22.

[7] Bhattacharya, S., Divan, D. M., & Banerjee, B. (2011). Synchronous frame-based controller implementation for a DSTATCOM. IEEE Transactions on Industry Applications, 37(6),1841–1847.

[8] Adebayo, T. A., & Daramola, O. A. (2021). Phase-specific compensation in unbalanced networks using fuzzy-adaptive PSO for DSTATCOM optimization. Energy Reports, 7, 3512–3521.

[9] Roosta, H.R. Eskandari, and M.H. Khooban, "Optimization of radial unbalanced distribution networks in the presence of distribution generation units by network reconfiguration using harmony search algorithm," Neural Computing and Applications, vol. 31, Nov. 2019. doi: 10.1007/s00521-018-3507-0.

[10] G. Fei, "Solving Load Phase Balancing Problem in LV Distribution Networks by Chaotic Simulated Annealing," Adv. Mater. Res., vol. 463-464, pp. 689-693, Feb. 2012, doi: 10.4028/www.scientific.net/AMR.463-464.689.

[11] Zhang, P. Nie, H. Zhang, and K. Ji, "Research on three-phase imbalance control strategy of low-voltage distribution station area," Proc. China Int. Conf. Electr. Distrib. (CICED), 2022.

[12] F. K. Handhal and A. T. Rashid, "Load Balancing in Distribution System Using Heuristic Search Algorithm," Proceedings of the International Conference on Advances in Sustainable Engineering and Applications 2018 (ICASEA'18)’, Wasit University, Iraq, March 2018, doi: 10.1109/ICASEA.2018.8370954.

[13] L. Gumilar, I. A. Wicaksono, A. N. Afandi, A. A. A. Samat, and Q. A. Sias, "Investigation of the Usage of Zigzag Transformers to Reduce Harmonics Distortion in Distribution Systems," Journal of Mechatronics, Electrical Power, and Vehicular Technology, vol. 14, 2023, e-ISSN: 2088-6985, p-ISSN: 2087-337.

[14] G. Grigoras, M. Gavrilas, B.-C. Neagu, O. Ivanov, I. Triștiu, and C. Bulac, "An Efficient Method to Optimal Phase Load Balancing in Low Voltage Distribution Network," Proceedings of the 2019 International Conference on ENERGY and ENVIRONMENT (CIEM), 2019.

[15] M. W. Siti, D. V. Nicolae, A. A. Jimoh, and A. Ukil, "Reconfiguration and Load Balancing in the LV and MV Distribution Networks for Optimal Performance," IEEE Transactions on Power Delivery, vol. 22, no. 4, 2017.

[16] C. H. Lin, C. S. Chen, M. Y. Huang, H. J. Chuang, M. S. Kang, C. Y. Ho, and C. W. Huang, "Optimal Phase Arrangement of Distribution Feeders Using Immune Algorithm," Proceedings of the 2007 International Conference on Intelligent Systems Applications to Power Systems, 2007.

[17] C.H. Lin, C.S. Chen, T.T. Ku, and C.Y. Ho, "Mitigation of three-phase unbalancing for distribution feeders by rephasing of laterals and distribution transformers," IEEE PES T&D 2010

[18] M. Mangaraj and A.K. Panda, "An efficient control algorithm based DSTATCOM for power conditioning," 2015 International Conference on Industrial Instrumentation and Control (ICIC), 2015.

[19] K. C. C. Laconico and R. A. Aguirre, "Optimal Load Balancing and Capacitor Sizing and Siting of an Unbalanced Radial Distribution Network," in Proceedings of the 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia), 2019.

[20] T. Wang, G. Li, H. Han, H. Chen, Z. Yan, and W. Chen, "Research on Methods of Suppressing Three-Phase Unbalanced Overvoltage in Distribution Network by Substation Photovoltaic System," in Proceedings of the 2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE), 2020.

@article{1716303,
      author = {Sabo Umar Usman, A. Salisu, Muhammad Yahaya Yarda, Ubaidullahi Sani},
      title = {Mitigating Phase Imbalance in Distribution Networks with Optimal DSTATCOM Placement using Hybrid Bacteria Foraging and Cuckoo Search Algorithm},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {2246-2254},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716303.pdf},
      abstract = {This research presents the optimal placement and sizing of a Distribution Static Compensator (DSTATCOM) on the 11 kV Malali feeder for phase balancing, power loss reduction, and voltage profile improvement. The study addresses challenges of voltage imbalance and excessive power losses common in unbalanced radial distribution networks. A hybrid optimization approach combining the Bacterial Foraging Optimization (BFO) and Cuckoo Search Optimization (CSO) algorithms was developed to determine the location and reactive power injection of the DSTATCOM. The 11 kV Malali feeder, modeled in MATLAB R2023b using the forward–backward sweep load flow method, served as the test network. Simulation results showed that Bus 15 was the most effective location for DSTATCOM placement. The hybrid BFO–CSO algorithm achieved a 75.7% reduction in real power loss, a 90.7% reduction in reactive power loss, and a 10.2% improvement in voltage profile, raising the minimum bus voltage from 0.889 p.u. to 0.98 p.u. The results demonstrate that the proposed hybrid optimization technique provides superior performance compared to standalone algorithms, achieving improved voltage stability, minimized losses, and enhanced phase balance in distribution networks. The study concludes that the hybrid BFO–CSO approach is an effective tool for multi-objective optimization in power distribution systems.},
      keywords = {Hybridization, Cuckoo search, Bacterial foraging, Voltage imbalance},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716303}
  }