现实世界各个领域的生产实践中 ,人们常常遇到以非线性最小二乘为基础原理的数学模型。鉴于非线性理论的发展不完善 ,过去处理非线性的数值计算方法与计算工具的限制 ,人们往往采取将非线性函数泰勒级数展开 ,并取至一次项 ,即化成线性模型来处理 ,从而忽略了模型的非线性程度。该文采用双一次项展开方法有效地解决了这一问题 ,并将其应用到电力系统的状态估计中 ,一方面提高了估计结果的精度 ,同时由于顾及了二阶偏导数项 ,加速了迭代过程 ,缩短了计算时间 In production practice in all fields of the real world, people often encounter the mathematical model based on the principle of non-linear least squares. In view of the imperfect development of nonlinear theory and the limitations of numerical methods and computational tools that deal with nonlinear in the past, people often take the non-linear function Taylor series expansion and take it to the first term, that is, into a linear model to deal with, so as to ignore The degree of nonlinearity of the model. This paper solves this problem effectively by using the double-term expansion method and applies it to the state estimation of power system, which not only improves the accuracy of the estimation results but also accelerates the iteration due to the consideration of the second-order partial derivative term Process, shorten the calculation time