引用本文:仉梦林,艾小猛,文劲宇.含风电电力系统的主从博弈经济调度[J].控制理论与应用,2018,35(5):653~661.[点击复制]
ZHANG Meng-lin,AI Xiao-meng,WEN Jin-yu.Economic dispatch for power system integrated with wind power using Stackelberg game[J].Control Theory and Technology,2018,35(5):653~661.[点击复制]
含风电电力系统的主从博弈经济调度
Economic dispatch for power system integrated with wind power using Stackelberg game
摘要点击 2450  全文点击 1459  投稿时间：2017-09-17  修订日期：2018-01-06
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/CTA.2017.70676
  2018,35(5):653-661
中文关键词  电力系统经济调度  鲁棒优化  主从博弈  风电安全区间  教与学算法
英文关键词  economic dispatch of power system  robust optimization  Stackelberg game  safe interval of wind power  teaching and learning algorithm
基金项目  国家自然科学基金项目(51707070), 中国博士后科学基金资项目(2016M590693), 国家电网公司科技项目(5228001600DX)资助.
作者单位E-mail
仉梦林 华中科技大学电气与电子工程学院强电磁工程与新技术国家重点实验室 zhangml1207@foxmail.com 
艾小猛 华中科技大学电气与电子工程学院强电磁工程与新技术国家重点实验室  
文劲宇* 华中科技大学电气与电子工程学院强电磁工程与新技术国家重点实验室  
中文摘要
      风力发电具有显著的随机性和波动性, 对电力系统原有调度模式提出挑战. 采用鲁棒优化处理风电不确定 性, 利用鲁棒优化蕴含的博弈思想, 将风电场看作调度中心的一个虚拟博弈者, 利用双层规划法建立了二者的主从 博弈模型, 将调度中心看作领导层, 其决策目标为电网运行的成本最低, 将风电场看作下属层, 其决策目标是能保证 系统实时安全运行的最大风电出力区间. 由于考虑了火电机组的阀点效应, 主从博弈模型呈现出非线性双层规划 的数学特点, 提出一种改进教与学算法与线性规划相嵌套的求解方法. 最后, 采用改进的10机39节点系统对模型以 及求解方法的有效性进行了验证.
英文摘要
      Wind power generation has obvious randomness and volatility, which challenge the original scheduling mode of power systems. The paper adopts robust optimization method to cope with the wind power uncertainty, and it takes the wind farm as a virtual game player of the dispatching center by using the game theory contained in robust optimization. A Stackelberg game model for dispatching center and the wind farm is established by utilizing the bi-level programming method. In the model, the dispatching center is taken as the leader level whose decision objective is the lowest power system operation cost, and the wind farm is taken as the follower level whose decision objective is the maximum wind power safe interval which can ensure the power system operation safety in real-time. As the valve point effect of thermal power units is considered, the model presents the characteristics of bi-level nonlinear programming, and a nested solving method of an improved teaching-and-learning method and linear programming is proposed. Finally, the revised 10-machine 39-node system is used to verify the effectiveness of the model and the solution method.