考虑风光不确定性的暂态稳定约束最优潮流模型研究  

Transient Stability Constrained Optimal Power Flow Model Considering Uncertainty of Wind and Photovoltaic Output

作　　者：陈萍 党喜 刘龙成 李正浩 王秋杰[1,2] 刘颂凯 CHEN Ping;DANG Xi;LIU Longcheng;LI Zhenghao;WANG Qiujie;LIU Songkai(College of Electrical Engineering and New Energy,China Three Gorges University,Yichang 443002,China;Hubei Provincial Collaborative Innovation Center for New Energy Microgrid,Yichang 443002,China)

机构地区：[1]三峡大学电气与新能源学院,湖北宜昌443002 [2]新能源微电网湖北省协同创新中心,湖北宜昌443002

出　　处：《智慧电力》2024年第3期17-24,共8页Smart Power

基　　金：国家自然科学基金资助项目(52307109);湖北省自然科学基金资助项目(2022CFB825)。

摘　　要：针对风光接入电力系统后的不确定性问题,同时为兼顾运行中的经济性和安全性,提出考虑风光不确定性的暂态稳定约束最优潮流(TSCOPF)模型和求解方法。首先,采用高斯混合模型(GMM)为电力系统中风光出力的预测误差模型,搭建包含旋转备用机会约束的TSCOPF模型;然后,利用序列运算对机会约束进行确定性转换,将TSCOPF模型转换为混合整数线性规划(MILP),并利用Gurobi求解器进行求解;最后,通过对IEEE 39节点的案例分析,验证了所提模型和方法的有效性。Aiming at the uncertainty in a power system with wind power integration,the paper proposes a transient stability constrained optimal power flow(TSCOPF)model and the solution method considering the uncertainty of wind and photovoltaic output,with the consideration of both economy and security in operation.Firstly,a Gaussian mixture model(GMM)is used as the prediction error model of wind and photovoltaic output in the power system to build a TSCOPF model with the rotating reserve chance constraints.Then deterministic transformation for the chance constraints is carried out using sequence operations,and the TSCOPF model is converted into a mixed integer linear programming(MILP)model,which is solved using the Gurobi solver.Finally,the case analysis on IEEE 39-node system verifies the validity of the proposed model and method.

关 键 词：暂态稳定约束最优潮流 高斯混合模型 机会约束 序列运算 

分 类 号：TM712[电气工程—电力系统及自动化]