期刊文献+

计及不确定因素的需求侧灵活性资源优化调度

Optimal Dispatch of Flexible Resource on Demand Side Considering Uncertainties
收藏 分享 导出
摘要 充分把握需求侧资源灵活性可以更好地实现日前优化调度以及合理地向电网提供辅助服务.然而,需求侧资源种类丰富、数量大、容量小、随机性强且分布于系统结构底层的不同位置,因此需要对其进行整合与量化.以含有高比例分布式能源的节点为研究对象,采用鲁棒边界的虚拟电池模型量化描述了具有不确定因素的集群电动汽车的灵活性与光伏出力.在此基础上,由交互平台参与日前电力市场,并采用协调优化策略合理地分配日前发用电计划与备用容量.算例验证了提出方法的有效性,既解决了由于高比例分布式能源导致的计算复杂问题,又降低了用户用电隐私信息暴露的风险. Sufficient grasp of flexibilities available from resources on demand side can better realize day-ahead optimal scheduling and reasonably provide ancillary services to power grids.However,the resources on demand side have abundant species,large quantities,small capacities and strong randomness.In addition,resources on demand side are usually distributed in different locations at the bottom of the system structure.Thus,these flexibilities need to be integrated and quantified.This paper takes the nodes with high-penetration of distributed energy as the research object.Virtual battery model with robust boundary is used to quantatively describe the flexibilities of aggregated electric vehicles and photovoltaic output considering their uncertainties.Based on the proposed virtual battery model,the transactive platform participates in the day-ahead electricity market and adopts a coordinated optimization strategy to reasonably allot energy schedule and reserve capacity.The case study verifies the effectiveness of the proposed method,which can reduce computational complexity caused by high-penetration distributed energy,and reduce the exposure risk of privacy electricity information for users.
作者 吴界辰 艾欣 胡俊杰 吴洲洋 WU Jiechen;AI Xin;HU Junjie;WU Zhouyang(State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University,Beijing 102206,China)
出处 《电力系统自动化》 EI CSCD 北大核心 2019年第14期73-80,89共9页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目(51877078) 北京市自然科学基金资助项目(3182037).
关键词 资源灵活性 鲁棒边界 虚拟电池模型 闵可夫斯基和 发用电计划 备用容量 resource flexibility robust boundary virtual battery model Minkowski sum power generation and consumption plan reserve capacity
作者简介 吴界辰(1991-),男,博士研究生,主要研究方向:新能源电力系统及微网.E-mail:wjcncepu@foxmail.com;艾欣(1964-),男,教授,博士生导师,主要研究方向:新能源电力系统及微网.E-mail:aixin@ncepu.edu.cn;通信作者:胡俊杰(1986-),男,副教授,硕士生导师,主要研究方向:新能源电力系统及微网.E-mail:junjiehu@ncepu.edu.cn.
  • 相关文献

参考文献10

二级参考文献133

  • 1刘敏,吴复立.电力市场环境下发电公司风险管理框架[J].电力系统自动化,2004,18(13):1-6. 被引量:50
  • 2张显,王锡凡.电力金融市场综述[J].电力系统自动化,2005,29(20):1-9. 被引量:61
  • 3World Wind Energy Association. World wind energy hal~year report 2012[R/OL]. [2012-10-15]. http.-//www, wwindea, org/ webimages / Hal~-year report_2012.pd~. 被引量:1
  • 4XIE L, CARVALHO P M S, FERREIRA L A F M, et al. Wind integration in power systems~ operational challenges and possible solutions[J]. Proceedings of the IEEE, 2011, 99(1).. 214-232. 被引量:1
  • 5WU Lei, SHAHIDEHPOUR M, LI Tao. Stochastic security constrained unit commitment[ J]. IEEE Trans on Power Systems, 2007, 22(2): 800-811. 被引量:1
  • 6KIMBALL L M, CLEMENTS K A, DAVIS P W. An implementation of the stochastic OPF problem [J]. Electric Power Components and Systems, 2003, 31(12): 1193-1204. 被引量:1
  • 7DANTZIG G B. Solving two-move games with perfect information[R]. 1958. 被引量:1
  • 8FALK J. A linear max-rain problem [J]. Mathematical Programming, 1973, 5(1)~ 169-188. 被引量:1
  • 9MILNOR J W. Games against nature[R]. 1951. 被引量:1
  • 10SZI~P J, FORGO F. Games against nature[M]. Netherlands~ Springer, 1985~ 230-236. 被引量:1

共引文献124

投稿分析

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部 意见反馈