期刊文献+

基于混合整数规划的微电网日前优化调度模型

Day Ahead Optimal Dispatching Model of Microgrid Based onMixed Integer Programming
下载PDF
导出
摘要 为了提升微电网的效益,妥善管理微电网内的分布式电源和储能的运行,实现微电网经济、技术效益的最大化成为了研究热点。文章以微电网内负荷平均供电单价最小为目标,考虑风、光、蓄电池组成的微电网与主网之间的能量交换,建立了一个混合整数规划模型,最后通过实例对模型进行了仿真,仿真结果表明考虑可再生能源的参与可以提高微电网的经济性,验证了所提模型的有效性。 In order to improve the effi ciency of microgrid,properly manage the operation of distributed power and energy storage in microgrid,and realize the maximization of economic,technological benefi ts of microgrid has become a research hotspot.In this paper,a mixed integer programming model is established to minimize the average unit price of power supply in the microgrid,considering the energy exchange between the microgrid and the main grid composed of wind,light and battery.Finally,an example is given to simulate the model.The simulation results show that considering the participation of renewable energy can improve the economy of microgrid and verify the effectiveness of the proposed model.
作者 许英强 高章鹏 李晓航 Xu Ying-qiang;Gao Zhang-peng;Li Xiao-hang
出处 《电力系统装备》 2020年第11期79-81,共3页 Electric Power System Equipment
关键词 微电网 新能源消纳 日前优化调度 混合整数规划 microgrid new energy consumption day ahead optimal scheduling mixed integer programming
  • 相关文献

参考文献6

二级参考文献98

  • 1陈贵敏,贾建援,韩琪.粒子群优化算法的惯性权值递减策略研究[J].西安交通大学学报,2006,40(1):53-56. 被引量:309
  • 2Li R, Ma H, Wang F, et al. Game optimization theory and application in distribution system expansion planning, including distributed generation[J]. Energies, 2013, 6(2): 1101-1124.
  • 3Evangelopoulos V A, Georgilakis P S. Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm[J]. IET Generation, Transmission and Distribution, 2014, 8(3): 389-400.
  • 4Liu Zhipeng, Wen Fushuan, Gerard Ledwich. Optimal siting and sizing of distributed generators in distribution systems considering uncertainties[J]. IEEE Transactions on Power Delivery, 2011, 26(4): 2541-2551.
  • 5Shaaban M F, EI-Saadany E F. Accommodating high penetrations of PEVs and renewable DG considering uncertainties in distribution systems[J]. IEEE Transactions on Power Systems, 2014, 29(1): 259-270.
  • 6Aghaei J, Muttaqi K M, Azizivahed A, et al. Distribution expansion planning considering reliability and security of energy using modified PSO (particle swarm optimization) algorithm[J]. Energy, 2014,65(2): 398-411.
  • 7Sun J, Wu X, Palade V, et al. Convergence analysis and improvements of quantum-behaved particle swarm optimization[J]. Information Sciences, 2012, 193(1): 81-103.
  • 8Zhang C, Yi Z. Scale-free fully informed particle swarm optimization algorithm[J]. Information Sciences, 2011, 181(20): 4550-4568.
  • 9Mahmood Sadeghi, Mohsen Kalantar. Multi types DG expansion dynamic planning in distribution system under stochastic conditions using covariance matrix adaptation evolutionary strategy and Monte-Carlo simulation[J]. Energy Conversion and Management, 2014, 78(13): 455-471.
  • 10HATZIARGYRIOU N, ASANO H, IRAVANI R, et al. Microgrids Jl. Power and Energy Magazine, IEEE, 2007, 5 (4) : 78-94.

共引文献762

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