Adaptive group search optimization algorithm for multi-objective optimal power flow problem

• A new method for solving the multi-objective optimal power flow problem is proposed.
• Total operation cost, total emitted emission, and proposed N-1 contingency index are considered as objectives.
• A new security index is proposed.
• The fuzzy decision-making approach is utilized to handle the multi-objective OPF problem.
• AGSO is proposed to precise the convergence characteristic of conventional GSO algorithm.

This paper presents an adaptive group search optimization (AGSO) algorithm for solving optimal power flow (OPF) problem. In this study, different aspects of the OPF problem are considered to form the accurate multi-objective model. The system total operation cost, the total emission, and N-1 security index are first, second, and third ordered objectives, respectively. Additionally, to consider accurate model of the problem, transmission losses and different equality and inequality constrains, such as feasible operating ranges of generators (FOR) and power flow equations are taken into account. Moreover, this study presents adaptive form of conventional GSO to precise the convergence characteristic of GSO. The effectiveness and accuracy of the proposed method for solving the nonlinear and nonconvex problems is validated by carrying out simulation studies on sample benchmark test cases and 30-bus and 57-bus IEEE standard test systems. Based on the comprehensive simulation studies, the accuracy of the proposed method is validated.

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