Optimal power flow calculation with reverse mutation seagull optimization algorithm
Aiming at the shortcomings of poor global search ability and slow convergence speed of seagull optimization algorithm,a reverse mutation seagull optimization algorithm(RMSOA)was proposed to solve the optimal power flow problem.Firstly,the reverse mutation strategy was introduced to select the initial population of seagull.Subsequently,combined the nonlinear convergence factor and particle swarm algorithm speed optimization,the global search and local development ability of algorithm were balanced.Then,the generation cost or active power loss or node voltage deviation were taken as objective functions of the single-objective optimal power flow calculation,the generation cost and its weighted sum with active power loss or node voltage deviation were taken as objective functions of the multi-objective optimal power flow calculation.Optimization results of the proposed RMSOA algorithm were compared with those of other intelligence algorithms.Simulation results of IEEE 30 bus test system and IEEE 118 bus test system indicate that RMSOA algorithms has advantages of higher search accuracy,faster convergence speed and stronger robustness in solvinig optimal power flow problem.
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