梯级水库优化调度的改进遗传算法

Na Li, Ya-dong Mei
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引用次数: 3

摘要

根据梯级水电站优化运行的特点,建立了多级优化的数学模型。为了提高传统算法在梯级水库优化调度中的能力,提出了小生境遗传算法(NGA)。该方法避免了遗传算法在较早阶段收敛的情况。通过对三个经典函数的求解,验证了改进算法的有效性。最后将其成功应用于清河梯级水电站。结果表明,NGA不仅具有更好的优化能力,而且具有更好的精度。它能以较大的概率局部搜索全局解,是一种优越的非线性优化方法。
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An Improved Genetic Algorithm for Optimal Operation of Cascaded Reservoirs
Based on the characteristics of optimal operation of cascaded hydropower stations, a mathematic model about the multistage optimization is established. In order to improve the capability of the traditional algorithm in optimal operation of cascaded reservoirs, Niche Genetic Algorithm (NGA) is suggested. This method could avoid the situation of GA convergence at a much earlier stage. The validity of improvement algorithm is testified by the solution of three classic functions. Finally it is successfully applied to the cascaded hydropower stations of the Qing River. The results show that NGA has not only better optimization capability, but also better accuracy. It is a superior non-linear optimal method which could locally search the global solution with greater probability.
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