This paper proposes an Adaptive Simulated Gorilla Troop Optimizer (ASGTO) to minimize the cost of switched capacitor placement in the IEEE 34-bus radial distribution network. The novelty of this work lies in the enhancement of the standard Gorilla Troop Optimizer (GTO) through the integration of circle chaotic mapping and step adaptive simulations, which improve the global optimization performance. The ASGTO adopts a two-step approach: a loss sensitivity analysis identifies candidate buses, followed by the determination of the optimal capacitor locations and sizes by ASGTO. The optimization process is validated using a backward-forward sweep power flow analysis based on standard IEEE data. Comparative results reveal the superiority of the proposed ASGTO method, thereby achieving a 27.9% reduction in active power loss, a 28.09% decrease in reactive power loss, and an annual energy cost saving of ＄9,122.32. The optimal placement of the capacitors significantly enhances the voltage stability, thereby maintaining voltage levels between 0.9505 per unit (p.u) and 0.9952 p.u. The results confirm the effectiveness of the ASGTO in reducing losses and costs while improving voltage profiles, thereby supporting the development of more efficient and sustainable distribution networks.
Citation: Bright Ayasu, Abdul-Fatawu Seini Yussif, Emmanuel Agyepong Nyantakyi. Enhancement of power distribution efficiency through optimal capacitor placement using adaptive simulated gorilla troop optimizer[J]. AIMS Electronics and Electrical Engineering, 2025, 9(3): 405-422. doi: 10.3934/electreng.2025019
This paper proposes an Adaptive Simulated Gorilla Troop Optimizer (ASGTO) to minimize the cost of switched capacitor placement in the IEEE 34-bus radial distribution network. The novelty of this work lies in the enhancement of the standard Gorilla Troop Optimizer (GTO) through the integration of circle chaotic mapping and step adaptive simulations, which improve the global optimization performance. The ASGTO adopts a two-step approach: a loss sensitivity analysis identifies candidate buses, followed by the determination of the optimal capacitor locations and sizes by ASGTO. The optimization process is validated using a backward-forward sweep power flow analysis based on standard IEEE data. Comparative results reveal the superiority of the proposed ASGTO method, thereby achieving a 27.9% reduction in active power loss, a 28.09% decrease in reactive power loss, and an annual energy cost saving of ＄9,122.32. The optimal placement of the capacitors significantly enhances the voltage stability, thereby maintaining voltage levels between 0.9505 per unit (p.u) and 0.9952 p.u. The results confirm the effectiveness of the ASGTO in reducing losses and costs while improving voltage profiles, thereby supporting the development of more efficient and sustainable distribution networks.
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Bright Ayasu, Abdul-Fatawu Seini Yussif, Emmanuel Agyepong Nyantakyi. Enhancement of power distribution efficiency through optimal capacitor placement using adaptive simulated gorilla troop optimizer[J]. AIMS Electronics and Electrical Engineering, 2025, 9(3): 405-422. doi: 10.3934/electreng.2025019
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