期刊文献+

基于改进集中竞价的多能源系统交易优化方法 被引量:3

Multi-energy system transaction optimization method based on improved centralized bidding
下载PDF
导出
摘要 能源互联网是以电力系统为核心,与天然气网络、热力网络等其他系统紧密耦合而成的复杂多能源网络,是能源与互联网深度融合的产物。为了满足需求方的负荷需求和多能源用能主张,为其选择最合适的能量路由方式,使能源经过最优路径传输至负载端。基于交易利润最大化的能量路由机制设计了能源广域网中园区间的多能源协同交易方式,提出了基于改进集中竞价的能源互联网多能源交易优化方法,为多园区间的能源交易寻找交易利润最大的经济最优路径。通过算例验证了所提优化方法的有效性。 The energy internet is a complex multi-energy network formed by the power system as the core,closely coupled with other systems such as natural gas networks and thermal networks,which is a product of the deep integration of energy and the Internet.In order to meet the demand side's load demand and multi-energy use proposition,choosing the most suitable energy routing method for the energy to be transmitted to the load side through the optimal path,this paper designs the energy WAN park in the energy wide area network based on the energy routing mechanism that maximizes transaction profits.The multi-energy collaborative trading method between the two countries,proposes an energy Internet multi-energy transaction optimization method based on improved centralized bidding,and finds the economically optimal path with the largest trading profit for energy transactions between multiple parks.Finally,an example is used to verify the effectiveness of the proposed optimization method.
作者 刘颖坤 刘东 翁嘉明 高飞 陆海 LIU Yingkun;LIU Dong;WENG Jiaming;GAO Fei;LU Hai(Key Laboratory of Control of Power Transmission and Conversion,Ministry of Education(Shanghai Jiao Tong University),Shanghai 200240,China;Yunnan Power Grid Co.,Ltd.,Kunming 650200,China)
出处 《供用电》 2022年第10期75-83,共9页 Distribution & Utilization
基金 国家重点研发计划资助项目(2020YFE0200400)。
关键词 能量路由机制 最优路径 多能源系统 交易优化 集中竞价 energy routing mechanism optimal path multi-energy system transaction optimization centralized bidding
  • 相关文献

参考文献14

二级参考文献232

  • 1International Energy Agency. World energy outlook 2014 [ EB/OL ]. [2014 - 11 - 12]. http: //www. worldenergyoutlook, org/.
  • 2AKOMENO O, RUCHI C, ADAM 13. Distributed energy resource system optimisation using mixed interger linear programming[J]. Energy Policy, 2013, 61: 249- 266.
  • 3REN H. A MILP model for integrated plan and evaluation of distributed energy systems[J]. Applied Energy, 2010,87 (3): 1001-1014.
  • 4东京电力.料金单偭表[EB/OL].[2015-04-15].http://www, tepco, co. ip/e-rates/individual/menu/ home/home08-j, html.
  • 5东京燃氪.料金单偭表[EB/OL]. [2015-04-15].http: // e-com, tokyo-gas, co. jp/ryokin/Default. aspxtik= 1.
  • 6Huang A Q, Crow M L, Heydt G T, et al. The future renewable electric energy delivery and management (FREEDM) system: the energy internet[J]. Proceedings of the lEEE, 2011, 99(1): 133-148.
  • 7AI-Hinai A, Feliachi A. Dynamic model ofa microturbine used as a distributed generator[C]//Proceedings of the Thirty-Fourth Southeastern Symposium on System Theory. Huntsville, AL, USA: IEEE, 2002: 209-213.
  • 8Freitas W, Asada E, Morelato A, et al. Dynamic improvement of induction generators connected to distribution systems using a DSTATCOM[C]//Proeeedings of International Conference on Power System Technology. Kunming, China: IEEE, 2002, 1: 173-177.
  • 9Nagpal M, MoshrefA, Morison G K, et al. Experiencewith testing and modeling of gas turbines[C]//Proceedings of IEEE Power Engineering Society Winter Meeting. Columbus, OH: IEEE, 2001, 2: 652-656.
  • 10Xu X, Jia Hongjie, Chiang H D, et al. Dynamic modeling and interaction of hybrid natural gas and electricity supply system in microgrid[J]. IEEE Transactions on Power Systems, 2015, 30(3): 1212-1221,.

共引文献939

同被引文献56

引证文献3

二级引证文献1

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