TY - GEN
T1 - Application of Archimedes Optimization Algorithm for Network Reconfiguration to Minimize Power Loss and Voltage Deviation
AU - Adegoke, Samson Ademola
AU - Sun, Yanxia
AU - Wang, Zenghui
AU - Oladipo, Stephen
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - An optimal Network Reconfiguration (NR) is presented in this paper using a Chaotic sinusoidal map-based Archimedes Optimization Algorithm (CAOA) to address the issues of poor voltage profile and incurred power loss in the distribution system. The chaotic sinusoidal map was used to improve AOA sluggish and premature convergence. AOA was derived from the law Archimedes principle of physics, which mimics the buoyant force exerted upward on an object, fully or partially immersed in a fluid and proportional to the weight of fluid displaced. The exceptional qualities of AOA are efficiency, simplicity, and robustness. The initialization phase of AOA was improved using the chaotic sinusoidal map to improve the diversity strength of the AOA and obtain a better solution. Searching begins with random acceleration, volume, and densities in the search space. CAOA is applied for optimal NR in power distribution to minimize power loss and Voltage Deviation (VD). The verification of CAOA is tested on the IEEE 30 bus system, and the power loss decreases to 139.365 KW from the base case of 202.68 KW. This has led to a 31.238% reduction. The least voltage magnitude increases to 0.948 p.u using the proposed CAOA from 0.913 p.u of the base case. The base case (before reconfiguration) VD is 0.0035498 p.u and decreased to 0.0013403 p.u after reconfiguration. The result reveals that CAOA is suitable for lowering power loss and VD, thereby improving the bus voltage. The comparison with other methods proves that CAOA is effective in lower power loss and VD. It can be concluded from the simulation that CAOA led to improvement in system distribution performance for quality power supply and reliability.
AB - An optimal Network Reconfiguration (NR) is presented in this paper using a Chaotic sinusoidal map-based Archimedes Optimization Algorithm (CAOA) to address the issues of poor voltage profile and incurred power loss in the distribution system. The chaotic sinusoidal map was used to improve AOA sluggish and premature convergence. AOA was derived from the law Archimedes principle of physics, which mimics the buoyant force exerted upward on an object, fully or partially immersed in a fluid and proportional to the weight of fluid displaced. The exceptional qualities of AOA are efficiency, simplicity, and robustness. The initialization phase of AOA was improved using the chaotic sinusoidal map to improve the diversity strength of the AOA and obtain a better solution. Searching begins with random acceleration, volume, and densities in the search space. CAOA is applied for optimal NR in power distribution to minimize power loss and Voltage Deviation (VD). The verification of CAOA is tested on the IEEE 30 bus system, and the power loss decreases to 139.365 KW from the base case of 202.68 KW. This has led to a 31.238% reduction. The least voltage magnitude increases to 0.948 p.u using the proposed CAOA from 0.913 p.u of the base case. The base case (before reconfiguration) VD is 0.0035498 p.u and decreased to 0.0013403 p.u after reconfiguration. The result reveals that CAOA is suitable for lowering power loss and VD, thereby improving the bus voltage. The comparison with other methods proves that CAOA is effective in lower power loss and VD. It can be concluded from the simulation that CAOA led to improvement in system distribution performance for quality power supply and reliability.
KW - archimedes optimization algorithm
KW - chaotic sinusoidal map
KW - network reconfiguration
KW - power loss
KW - voltage deviation
UR - http://www.scopus.com/inward/record.url?scp=105002855097&partnerID=8YFLogxK
U2 - 10.1109/ICPET62369.2024.10941383
DO - 10.1109/ICPET62369.2024.10941383
M3 - Conference contribution
AN - SCOPUS:105002855097
T3 - 2024 6th International Conference on Power and Energy Technology, ICPET 2024
SP - 1608
EP - 1612
BT - 2024 6th International Conference on Power and Energy Technology, ICPET 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Power and Energy Technology, ICPET 2024
Y2 - 12 July 2024 through 15 July 2024
ER -