A Hybrid Fish Swarm Algorithm for Reactive Power Optimization in Distribution Networks
The artificial fish swarm algorithm is the same as the traditional swarm intelligence algorithm.Because of the ran-domness of the basic population and the uncertainty of the optimization route,the algorithm may not find the optimal solution.In or-der to solve the above problems,chaotic sequence is used to generate more uniform initial values.The adaptive field of view and step size are used to dynamically change the search range.An improved biological"elimination"mechanism is introduced,and the genes of contemporary and elite individuals are used to eliminate the fish schools and speed up the convergence.The hybrid algo-rithm is used in the reactive power optimization of the IEEE33-bus system distribution network.The results show that the improved algorithm is easier to jump out of the local optimum,and the convergence speed is faster,the convergence performance is better,and the optimization efficiency is improved.
artificial fish swarm algorithmchaotic sequenceadaptiveelimination mechanismreactive power optimization
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