Responding to the situation that the external network information in power systems is completely unknown and in order to analyze the research network, this paper presents a parameter estimation method for external network static equivalent model based on nonlinear programming genetic algorithm to build external network equivalent model. First of all, the typical two-port and three-port external network equivalent model are adopted, and the least squares estimation model of the equivalent parameters is deduced based on power equation of boundary nodes; then, combining the nonlinear programming method with genetic algorithm, a combinatorial intelligent optimization algorithm is put forward; finally, the nonlinear programming genetic algorithm is applied to estimate the external network static equivalent parameters. The proposed optimization algorithm does not require the initial value and can obtain the global optimal solution which is in accord with physical interpretation. Taking two-port and three-port equivalent for example, through simulation analysis of IEEE14 bus system and by comparing power flow distribution of the research system before and after the equivalent, the validity and versatility of the proposed method is verified.%针对电力系统外部网络信息未知的情况，为了对研究网络进行系统分析，提出一种基于非线性规划遗传算法的外网静态等值参数估计方法，来建立外网等值模型。首先，采用典型的双端口和三端口外网等值模型，通过边界节点的功率方程推导出等值参数的最小二乘估计模型；然后，结合非线性规划方法与遗传算法，提出一种组合智能优化算法；最后，运用非线性规划遗传组合算法进行外网静态等值参数的估计。提出的优化算法，不需要设定初值，能够更好地得到符合物理解释的全局最优解。以双端口和三端口等值为例，通过IEEE 14节点系统的仿真分析，并对比等值前后研究系统的潮流分布，验证所提方法的正确性和通用性。
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