TY - GEN
T1 - Optimizing Distributed Generator Placement in Distribution Networks Using Flower Pollination Algorithm with Self-Healing Integration
AU - Kusuma, Vicky Andria
AU - Wibowo, Rony Seto
AU - Uman Putra, Dimas Fajar
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This study aims to optimize power flow in distribution network systems using artificial intelligence, specifically the Flower Pollination Algorithm (FPA), integrated with a self-healing system to improve the reliability and efficiency of power distribution. The research focuses on mitigating common power distribution issues such as under-voltage and over-voltage by strategically placing Distributed Generators (DG) within the network. A modified IEEE 15-bus system is used as a test case to evaluate the proposed method. The FPA algorithm is chosen for its effectiveness in solving multi-objective optimization problems, incorporating both global and local pollination strategies. The objective function considers total power losses and voltage deviations to ensure optimal DG placement. Simulation results demonstrate that the combined application of FPA and self-healing mechanisms significantly reduces power losses and voltage fluctuations, enhancing overall network stability. This research provides a robust and efficient solution for modern power distribution systems, improving their adaptability to dynamic operational conditions.
AB - This study aims to optimize power flow in distribution network systems using artificial intelligence, specifically the Flower Pollination Algorithm (FPA), integrated with a self-healing system to improve the reliability and efficiency of power distribution. The research focuses on mitigating common power distribution issues such as under-voltage and over-voltage by strategically placing Distributed Generators (DG) within the network. A modified IEEE 15-bus system is used as a test case to evaluate the proposed method. The FPA algorithm is chosen for its effectiveness in solving multi-objective optimization problems, incorporating both global and local pollination strategies. The objective function considers total power losses and voltage deviations to ensure optimal DG placement. Simulation results demonstrate that the combined application of FPA and self-healing mechanisms significantly reduces power losses and voltage fluctuations, enhancing overall network stability. This research provides a robust and efficient solution for modern power distribution systems, improving their adaptability to dynamic operational conditions.
KW - Distributed Generator
KW - Flower Pollination Algorithm
KW - IEEE 15 Bus System
KW - Optimal Power Flow
KW - Self-Healing System
UR - https://www.scopus.com/pages/publications/105002271430
U2 - 10.1109/ICADEIS65852.2025.10933363
DO - 10.1109/ICADEIS65852.2025.10933363
M3 - Conference contribution
AN - SCOPUS:105002271430
T3 - ICADEIS 2025 - 2025 International Conference on Advancement in Data Science, E-learning and Information System: Integrating Data Science and Information System, Proceeding
BT - ICADEIS 2025 - 2025 International Conference on Advancement in Data Science, E-learning and Information System
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 International Conference on Advancement in Data Science, E-learning and Information System, ICADEIS 2025
Y2 - 3 February 2025 through 4 February 2025
ER -