Multi-objective Optimal Power Flow calculation based on the improved Artificial Fish Swarm Algorithm

With the improved Artificial Fish Swarm Algorithm (AFSA), a new multi-objective Optimal Power Flow (OPF) calculation method was proposed. To accelerate the algorithm convergence speed and satisfy the requirement of accuracy, Chaos with good ergodicity and stochasticity was employed to initialize the fish school. After improvement the step in the behaviour of AF_prey can be adjusted dynamically, which can speed up the convergence. The behaviour of AF_swarm was also modified to improve the searching accuracy. The improved AFSA was employed to the optimal power flow calculation, which has capability of dynamic optimization and is suitable to deal with the multidimensional and nonlinear issues. The objective function and constraint conditions were treated separately, which turned the optimization issue with constraint conditions to non-constraint optimization issue. IEEE standard model was employed to the OPF calculation with Microsoft Visual C. The simulation results proved the good performance in the algorithm convergence speed and calculation accuracy of optimal power flow calculation with the improved AFSP. And The simulation results verified the feasibility and validity of multi-objective OPF calculation based on improved AFSA.

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