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Adapting particle swarm optimisation for charge simulation method

Adapting particle swarm optimisation for charge simulation method

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The charge simulation method (CSM), owing to its favourable characteristics, is commonly used for electric field analysis of high-voltage insulation systems. In order to improve the precision of the electric field calculation and to minimise the reliance on personal experience, a novel combination of particle swarm optimisation (PSO) and CSM is proposed. In this, the optimum allocations of the simulating charges can be obtained using PSO. The conventional CSM is briefly considered and the optimised version is formulated. The potential distribution between two spherical electrodes is determined as a sample problem. Also, the solution of field distribution with non-axial symmetry resulting from a floating spherical conductor between the spheres is considered. The optimised CSM using PSO proved to be more efficient and there is no need for the experience that was required to set up and implement a solution of this kind.

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
      • Eberhart, R.: `Particle swarm optimization', Proc. IEEE Int. Conf. Neural Networks, 1995, Perth, Australia), p. 1942–1948, IEEE Service Center.
    5. 5)
      • Shi, Y., Eberhart, R.: `A modified particle swarm optimizer', Evolutionary Computation Proc., 1998, p. 69–73, IEEE World Congress on Computational Intelligence.
    6. 6)
    7. 7)
      • X. Liu , Y. Cao , E. Wang . Numerical simulation of electric field with open boundary using intelligent optimum charge simulation method. IEEE Trans. Magn. , 4 , 1159 - 1162
    8. 8)
    9. 9)
    10. 10)
      • E. Kuffel , W.S. Zaengl , J. Kuffel . (2000) High voltage engineering: Fundamental.
    11. 11)
    12. 12)
    13. 13)
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