optimal power flow with four conflicting objective functions using multiobjective ant lion algorithm: a case study of the algerian electrical network

In this study, a multiobjective optimization is applied to optimal power flow problem (opf). to effectively achieve this goal, a multiobjective ant lion algorithm (moalo) is proposed to find the pareto optimal front for the multiobjective opf. the aim of this work is to reach good solutions of active and reactive opf problem by optimizing 4-conflicting objective functions simultaneously. here are generation cost, environmental pollution emission, active power losses, and voltage deviation. the performance of the proposed moalo algorithm has been tested on various electrical power systems with different sizes such as ieee 30-bus, ieee 57-bus, ieee 118-bus, ieee 300-bus systems and on practical algerian dz114-bus system. the results of the tests proved the versatility of the algorithm when applied to large systems. the effectiveness of the proposed method has been confirmed by comparing the results obtained with those obtained by other algorithms given in the literature for the same test systems.