Multi-objective optimal power flow using grasshopper optimization algorithm

This paper introduces grasshopper optimization algorithm to efficiently prove its superiority in the optimal power flow problem. To demonstrate the efficiency of the proposed algorithm, it is implemented on the standard IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus test systems with different objectives that reveal presentation indices of the power system. Twelve different cases, in single and multi-objective optimization space, are considered on different curves of fuel cost, environmental pollution emission, voltage profile, and active power loss. The simulation results obtained from grasshopper optimization algorithm techniques are compared to other new evolutionary optimization methods surfaced in the current state-of-the-art literature. It is revealed that the proposed approach secures better consequence over the other newly originated popular optimization techniques and reflects its improved quality solutions and faster convergence speed. The results obtained in this work demonstrate that the grasshopper optimization algorithm method can successfully be applied to solve the non-linear problems connected to power systems. 1. This paper introduces grasshopper optimization algorithm (GOA) to efficiently prove its superiority in the optimal power flow problem (OPF). 2. GOA is implemented on the standard IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus test systems with different objectives. 3. It is revealed that the proposed GOA secures better consequence over the other newly originated popular optimization techniques and reflects its improved quality solutions and faster convergence speed.image