含风电电力系统机组组合问题的两阶段对称模糊建模与优化  

Two-stage symmetrical fuzzy modeling and optimization for the unit commitment in wind power systems

作　　者：蔡佳铭 王承民[1] 谢宁[1] 李欣 CAI Jiaming;WANG Chengmin;XIE Ning;LI Xin(School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;Shanghai Electric Power Design Institute Co.,Ltd.,Shanghai 200012,China)

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200240 [2]上海电力设计院有限公司,上海200012

出　　处：《电力科学与技术学报》2020年第6期36-45,共10页Journal of Electric Power Science And Technology

基　　金：国家自然科学基金(51777121);国家电网有限公司科技项目(17H300000437)。

摘　　要：为解决含风电电力系统机组组合问题固有预测误差带来的不确定性问题,建立同时模糊约束与目标的两阶段对称模糊优化模型。模型的第1阶段用于确定系统的模糊参数,第2阶段计算接近运行实际的模糊解和对应的模糊水平,将机组组合阶段的不确定性量化。由于引入较多待求解的模糊变量,故提出简化运算的外点迭代解法。算例从日前预测、日内4 h滚动预测、日内1 h超短期滚动预测与实际运行等尺度评估该法求解机组组合问题的结果对预测误差的适应性。结果表明,模糊优化在一定程度上能够缩减因预测误差而引起的机组组合误差,因而适用于求解不确定性较强系统的机组组合问题。In order to solve the problem of uncertainty caused by the inherent prediction error in the unit commitment decision-making involving the wind generation,this paper establishes a two-stage symmetric fuzzy optimization model with both fuzzy constraints and fuzzy targets.The first stage of the model determines the fuzzy parameters of the system.While,in the second stage,the actual fuzzy solution and the corresponding fuzzy level are calculated,and the uncertainty of the unit commitment is quantified.Due to the introduction of un-solved fuzzy variables,a simplified operation based on the outer-point iteration method is proposed.In case of the day-ahead prediction,the 4 h rolling prediction in the day,the 1 h ultra-short rolling prediction,the adaptability to the forecasting error of this method is analyzed though comparing with the actual situation.The results show that the fuzzy optimization can reduce the scheduling error caused by the prediction error to a certain extent,so it is suitable for the usage of system scheduling with a high uncertainty.

关 键 词：对称模糊优化 可再生能源 机组组合问题 不确定性 

分 类 号：TM614[电气工程—电力系统及自动化]