内点法 (Interior Point Method)是一种求解线性规划或非线性凸优化问题的算法。 它是由John von Neumann发明的，他利用戈尔丹的线性齐次系统提出了这种新的求解线性规划的方法。后被Narendra Karmarkar于1984年推广应用到线性规划，即Karmarkar算法。
原对偶内点法 prime-dual interior point method ; Primal-Dual Interior Method ; Primal-dual interior-point algorithm
对偶内点法 PDIPM ; Primal Dual Interior Point Method ; prime-dualinteriorpointmethod
线性最优化的内点法 Interior point methods for linear optimization second edition
和内点法 Interior Point Method ; IPM
始对偶内点法 Primal Dual Interior Point Method ; PDIPM
原始对偶内点法 Primal Dual Interior Point Method ; PDIPM
校正原对偶内点法 Predictor-Corrector Primal-Dual Interior Point Method ; PCPDIPM
牛顿内点法 Interior-Point Newton method
Thirdly, the model of Optimal Power Flow (OPF) with UPFC is established, and solved by interior point method.
然后,建立了计及UPFC的最优潮流数学模型,并用内点法进行求解。
参考来源 - 计及UPFC的电力系统暂态稳定预防控制研究The thesis discusses the practicality of reduced grade algorithm and interior point algorithm for reactive power optimization.
本文就无功优化的缩减梯度法、内点法实用性了探讨。
参考来源 - 山东电网无功优化的实用性研究This paper mostly researches the calculation of ATC,and uses a trust region interior-point method to the calculation model of TTC(Total Transmission Capacity) based on the OPF(Optimal Power Flow) arithmetic.
本文主要研究ATC的计算问题,并提出将一种信赖域内点法应用到基于最优潮流(OPF)的总传输容量计算模型中。 本文首先在第一章中介绍了有关ATC的概念,在第二章中阐述了现有的ATC计算方法。
参考来源 - 基于信赖域内点法的静态ATC计算It considers the m inimal purchase cost increm ent as objective function and restrictive conditions. The nonlinear interior point algorithm of optim al power flow is employed to control the congestion in power m arket.
该方法以购电费用增加最小为目标函数 ,考虑了电力市场中的约束条件 ,用非线性内点法最优潮流实现电力市场中的阻塞调度控制。
参考来源 - 电力市场中的阻塞调度·2,447,543篇论文数据，部分数据来源于NoteExpress
如此交替等值和内点法修正，直到分布式无功优化计算收敛。
The procedures of iterative equivalent and internal bus modification are followed to gain the convergence of distributed reactive optimization.
文中提出了实时平衡交易模型并给出基于内点法的求解算法。
A balancing transaction model and its corresponding algorithm based on interior-point method is presented in this paper.
信赖域内点法可以很好地解决逐线性规划方法中的步长调整问题。
Trust region interior point method can settle the problem of adjusting step sizes on successive linear programming well.
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