Assessment and Mitigation of Power Quality Issues in Presence of Optimally Placed DGs in Radial Distribution System Using Heuristic Optimization Algorithms

Distributed Generation (DG) integration plays a significant role in improving the efficiency, reliability, and power quality of modern radial distribution systems. However, improper DG placement and sizing can lead to high power losses, unstable voltage profiles, and poor power quality act under changing load conditions. This study aims to improve power quality in the IEEE 33-bus radial distribution system by minimizing real power loss, Total Harmonic Distortion (THD), and voltage sag through optimal DG placement and sizing. A 24-hour load variation profile is considered to represent realistic operating conditions. The Backward-Forward Sweep (BFS) load flow method is utilized to calculate bus voltages, line currents, and power losses, while the Artificial Bee Colony (ABC) algorithm is useful to solve the multi-objective optimization problem involving power loss, THD, voltage deviation, and voltage sag index. Simulation results prove significant improvements after DG integration. The total active power loss is reduced from 159.1074 kW to 54.173 kW, achieving a 65.95% reduction, while the minimum bus voltage expands from 0.9188 p.u. to 0.9678 p.u. The total THD is reduced from 5.2716% to 2.6168%, while the voltage sag index decreases from 0.1958 to 0.1192. The results confirm the use of the proposed ABC-BFS approach for improving overall system performance and power quality under realistic operating conditions.

Load Flow Analysis, Backward-Forward Sweep, Artificial Bee Colony, Power Quality

1. Teferra, D.M., 2025. Performance Evaluation of a Radial Distribution Network Under Emerging Load Prediction Modeling Approach and DG Integration Using a Particle Swarm Optimization Algorithm. Journal of Electrical and Computer Engineering, 2025(1), p.1352068. [Google Scholar] [Crossref]

2. H. Iqbal, A. Stevenson, and A. I. Sarwat, “Impact Analysis and Optimal Placement of Distributed Energy Resources in Diverse Distribution Systems for Grid Congestion Mitigation and Performance Enhancement,” Electronics, vol. 14, no. 10, p. 1998, Jan. 2025, doi: 10.3390/electronics14101998. [Google Scholar] [Crossref]

3. S. Mokred, Y. Wang, M. Alruwaili, and M. A. Ibrahim, “A Novel Approach for Voltage Stability Assessment and Optimal Siting and Sizing of DGs in Radial Power Distribution Networks,” Processes, vol. 13, no. 7, p. 2239, Jul. 2025, doi: 10.3390/pr13072239. [Google Scholar] [Crossref]

4. S. Chanbasha, N. Jayakumar, and N. B. Kumar, “DG allocation for radial distribution system through optimal sizing in radial power distribution network using hybrid redfox pathfinder optimization,” Multimed Tools Appl, vol. 84, no. 16, pp. 16605–16629, May 2025, doi: 10.1007/s11042-024-18704-z. [Google Scholar] [Crossref]

5. M. Alanazi, “Optimal Integration of Distributed Generators and Soft Open Points in Radial Distribution Networks: A Hybrid WCA-PSO Approach,” Processes, vol. 13, no. 6, p. 1775, Jun. 2025, doi: 10.3390/pr13061775. [Google Scholar] [Crossref]

6. D. M. Teferra, L. M. H. Ngoo, and G. N. Nyakoe, “Optimizing Radial Distribution Network Performance Through Microgrid Integration Using a Hybrid PSO‐HSA Algorithm,” Journal of Electrical and Computer Engineering, vol. 2025, no. 1, p. 3701507, Jan. 2025, doi: 10.1155/jece/3701507. [Google Scholar] [Crossref]

7. B. K. Malika et al., “A quasi oppositional forensic based investigation algorithm for optimizing distributed generation placement and sizing in power distribution systems,” Sci Rep, vol. 15, no. 1, p. 16471, May 2025, doi: 10.1038/s41598-025-01378-4. [Google Scholar] [Crossref]

8. B. K. Malika, V. Pattanaik, B. K. Sahu, P. K. Rout, S. Panda, and M. Bajaj, “Optimal distributed generation and shunt capacitor bank placement in microgrid distribution planning for enhanced performance,” Neural Comput & Applic, vol. 37, no. 22, pp. 17363–17388, Aug. 2025, doi: 10.1007/s00521-024-10503-9. [Google Scholar] [Crossref]

9. L. F. Grisales-Noreña, D. Sanin-Villa, O. D. Montoya, R. I. Bolaños, and K. X. Bonilla Rojas, “Cost-Optimal Coordination of PV Generation and D-STATCOM Control in Active Distribution Networks,” Sci, vol. 8, no. 1, p. 8, Jan. 2026, doi: 10.3390/sci8010008. [Google Scholar] [Crossref]

10. X. Chen, Q. He, C. Liu, F. Peng, and H. Tian, “Research and application of the impact of distributed photovoltaic power supply access on distribution network automation technology,” Discov Artif Intell, vol. 6, no. 1, p. 353, Mar. 2026, doi: 10.1007/s44163-026-00971-4. [Google Scholar] [Crossref]

11. N. Chothani et al., “Improving microgrid reliability and performance by implementing novel optimizing strategies for renewable energy and storage devices,” Energy Nexus, vol. 21, p. 100671, Mar. 2026, doi: 10.1016/j.nexus.2026.100671. [Google Scholar] [Crossref]

12. A. Islam, S. Rudra, and M. L. Kolhe, “Optimizing the placement of distributed energy storage and improving distribution power system reliability via genetic algorithms and strategic load curtailment,” Neural Comput & Applic, vol. 37, no.22, pp. 17589–17608, Aug.2025, doi:10.1007/s00521-025-11037-4. [Google Scholar] [Crossref]

13. P. Patel et al., “Multi-objective particle swarm optimization algorithm-based method for optimal placement and sizing of distributed generations and shunt capacitors in a radial distribution network,” Results in Engineering, vol. 27, p. 106514, Sep. 2025, doi: 10.1016/j.rineng.2025.106514. [Google Scholar] [Crossref]

14. R. Sundar et al., “Distributed generation and shunt capacitor allocation in radial distribution power networks using a hybrid optimization approach,” Sci Rep, vol. 16, no. 1, p. 6299, Jan. 2026, doi: 10.1038/s41598-026-37713-6. [Google Scholar] [Crossref]

15. H. Lalaymia et al., “Multi-objective optimization of PVDGs in power distribution networks using the self adaptive tyrannosaurus algorithm,” Energy Reports, vol. 15, p. 109074, Jun. 2026, doi: 10.1016/j.egyr.2026.109074. [Google Scholar] [Crossref]

16. B. K. Malika, V. Pattanaik, B. K. Sahu, P. K. Rout, S. Panda, and M. Bajaj, “Optimal distributed generation and shunt capacitor bank placement in microgrid distribution planning for enhanced performance,” Neural Comput & Applic, vol. 37, no. 22, pp. 17363–17388, Aug. 2025, doi: 10.1007/s00521-024-10503-9. [Google Scholar] [Crossref]

17. G. V. K. Murthy, S. Sivanagaraju, S. Satyanarayana, and B. H. Rao, “Optimal Placement of DG in Distribution System to Mitigate Power Quality Disturbances,” International Journal of Electrical and Computer Engineering, vol. 7, no. 2, 2013. [Google Scholar] [Crossref]

18. Al-Ammar, E.A., Farzana, K., Waqar, A., Aamir, M., Haq, A.U., Zahid, M. and Batool, M. ABC algorithm based optimal sizing and placement of DGs in distribution networks considering multiple objectives,” Ain Shams Engineering Journal, vol. 12, no. 1, pp. 697–708, Mar. 2021, doi: 10.1016/j.asej.2020.05.002. [Google Scholar] [Crossref]

• Integrative Analytical Framework: A Literature Review of the Ethical and Social Challenges of AI in Healthcare and Rehabilitation
• Real-Time Performance Evaluation of an MPPT-Based EV Charging System Incorporating LiFePO₄ Battery Backup