摘要
以节能减排调度为研究框架,针对风电出力的随机性,采用自回归滑动平均模型(auto-regressive and moving average,ARMA)生成大量风速场景,并基于场景削减技术得到具有代表性的典型风速;针对电动汽车入网的不确定性,采用随机概率抽样的电动汽车集群模型,最终建立风-车互动接入的多目标电力调度动态模型。以CPLEX作为求解工具,采用模糊两阶段规划方法求解折衷规划结果。通过不同场景、不同电动汽车规模等算例,分析风电及电动汽车接入电网的调度策略及优化结果,验证所提模型及相关调度策略在改善电网运行经济性、降低污染气体排放方面的优势。
Based on the framework of energy saving and emission reduction,aiming at the randomness of wind power output,the autoregressive and moving average(ARMA)model is used to generate a large number of wind speed scenarios,and representative typical wind speeds are obtained based on scenario reduction technology. Furthermore,in view of the uncertainty of electric vehicles accessing the power grid,the cluster model of electric vehicles with random probability sampling is used,and the dynamic model of multiobjective power dispatching with wind-vehicle interaction is finally established. Also,this paper takes CPLEX as the solving tool,and the compromise dispatching results are solved by using fuzzy two-stage programming method. Through different scenarios,different scale of electric vehicles and other examples,the dispatching strategy and optimization results of wind power and electric vehicles connected to power grid are analyzed. The advantages of the proposed model and relevant dispatching strategies in improving the operation economy of power grid and reducing pollution gas emissions are verified.
作者
朱永胜
杨俊林
董燕
瞿博阳
廖伍代
陈斌
Zhu Yongsheng;Yang Junlin;Dong Yan;Qu Boyang;Liao Wudai;Chen Bin(School of Electronic and Information Engineering,Zhongyuan University of Technology,Zhengzhou 450007,China;Henan Senyuan Electric Co.,Ltd.,Changge 461500,China)
出处
《太阳能学报》
CSCD
北大核心
2021年第8期316-324,共9页
Acta Energiae Solaris Sinica
基金
国家自然科学基金面上项目(61873292,61876209)
河南省高等学校青年骨干教师培养计划(2018GGJS104)
河南省高等学校重点科研项目计划(20A470019)。
关键词
节能减排
ARMA模型
场景削减
电动汽车集群
风-车互动
模糊两阶段规划
energy saving and emission reduction
ARMA model
scenario reduction
electric vehicle cluster
wind-electric vehicle interaction
fuzzy two-stage programming
