Convex Reformulation for Two-sided Distributionally Robust Chance Constraints with Inexact Moment Information  

作　　者：Lun Yang Yinliang Xu Zheng Xu Hongbin Sun 

机构地区：[1]TsinghuaBerkeley Shenzhen Institute,Tsinghua Shenzhen International Graduate School,Tsinghua University,Shenzhen 518055,China [2]Department of Electrical Engineering,State Key Laboratory of Power Systems,Tsinghua University,Beijing 100084,China

出　　处：《Journal of Modern Power Systems and Clean Energy》2022年第4期1060-1065,共6页现代电力系统与清洁能源学报（英文）

基　　金：This work was supported by the Natural Science Foundation of Guangdong Province(No.2021A1515012450)。

摘　　要：Constraints on each node and line in power systems generally have upper and lower bounds,denoted as twosided constraints.Most existing power system optimization methods with the distributionally robust(DR)chance-constrained program treat the two-sided DR chance constraint separately,which is an inexact approximation.This letter derives an equivalent reformulation for the generic two-sided DR chance constraint under the interval moment based ambiguity set,which does not require the exact moment information.The derived reformulation is a second-order cone program(SOCP)formulation and is then applied to the optimal power flow(OPF)problem under uncertainty.Numerical results on several IEEE systems demonstrate the effectiveness of the proposed SOCP formulation and show the differences with other DR chance-constrained OPF approaches.

关 键 词：Two-sided chance constraint distributionally robust conic reformulation interval moment optimal power flow 

分 类 号：TM73[电气工程—电力系统及自动化]