Abstract
Wind power has randomicity and intermittence. As the wind power penetration rate increases, it poses a threat to the frequency of the power grid. In the power systems with high-permeability of wind power, relying solely on conventional crew tuning is no longer sufficient to ensure that the frequency is within safe limits. The battery energy storage has a fast response speed, but it is expensive. The frequency regulation provided by the wind farm itself has a short inertial control support time, the pitch control response is slow, and both frequency modulation methods are subject to wind speed. In order to improve the frequency adjustment capability of the wind farm, the battery energy storage and the wind farm’s own frequency modulation means are combined to adjust the system frequency. However, how to set the battery energy storage output to make the system frequency characteristics optimal hasn’t been studied. In this paper, the particle swarm optimization algorithm is used to select the optimal parameters, so that the frequency characteristics are optimal. The example shows that compared with the unoptimized energy storage frequency modulation coefficient, the optimal frequency modulation coefficient found by the PSO algorithm can greatly reduce the maximum frequency drop of the power system and improve the frequency stability of the power system.
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