Interval linear programming method for day-ahead optimal economic dispatching of microgrid considering uncertainty

被引:14
|
作者
Wang, Shouxiang [1 ]
Wang, Dong [1 ]
Han, Liang [1 ]
机构
[1] Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin
来源
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2014年 / 38卷 / 24期
基金
中国国家自然科学基金;
关键词
Interval linear programming; Microgrid; Optimal economic dispatching; Uncertainty;
D O I
10.7500/AEPS20131212010
中图分类号
学科分类号
摘要
The renewable energy power and load power in a microgrid both have uncertainty characteristics, the effects of which arc worth careful consideration in the optimal economic dispatching of the microgrid. In order to characterize these uncertainties in the microgrid, the randomness of the wind speed and light intensity is described by the interval, and combined with the interval description of load uncertainty, a microgrid economical optimization model based on interval linear programming (ILP) is proposed. Then by referring to the time-of-use pricing, the issue of power exchange with an external grid is considered. The CPLEX optimization software combined with the C++ programming is applied to the above issue. Finally, with the influence analysis of energy storage on the economical operation of the system as an example, the impact of uncertainty of renewable energy power and load power on the optimization result is discussed. The results have verified the robustness of the proposed method and model, and shown their effectiveness in dealing with uncertainty optimization. © 2014 State Grid Electric Power Research Institute Press.
引用
收藏
页码:5 / 11and47
页数:1142
相关论文
共 23 条
  • [1] Lu Z., Wang C., Min Y., Et al., Overview on microgrid research, Automation of Electric Power Systems, 31, 19, pp. 100-105, (2007)
  • [2] Chen C.L., Simulated annealing-based optimal wind-thermal coordination scheduling, IET Generation, Transmission and Distribution, 1, 3, pp. 447-455, (2007)
  • [3] Willish L., Analytical methods and rules of thumb for modeling DG-distribution interaction, Proceedings of IEEE Power Engineering Society Summer Meeting, pp. 1643-1644, (2000)
  • [4] Sun Y., Wu J., Li G., Et al., Dynamic economic dispatch considering wind power penetration based on wind speed forecasting and stochastic programming, Proceedings of the CSEE, 29, 4, pp. 41-47, (2009)
  • [5] Chen H., Chen J., Duan X., Fuzzy modeling and optimization algorithm on dynamic economic dispatch in wind power integrated system, Automation of Electric Power Systems, 30, 2, pp. 22-26, (2006)
  • [6] Wang R., Gu W., Wu Z., Economic and optimal operation of a combined heat and power microgrid, Automation of Electric Power Systems, 35, 8, pp. 22-27, (2011)
  • [7] Huang W., Huang T., Zhou H., Et al., Dynamic economical dispatch for microgrid hased on improved differential evolution algorithm, Automation of Electric Power Systems, 38, 9, pp. 211-217, (2014)
  • [8] Ma X., Wu Y., Fang H., Et al., Optimal sizing of hyhrid solar-wind distributed generation in an islanded microgrid using improved bacterial foraging algorithm, Proceedings of the CSEE, 31, 25, pp. 17-25, (2011)
  • [9] Miao Y., Jiang Q., Cao Y., Microgrid stochastic dispatch considering electric vehicles and battery swap stations, Electric Power Automation Equipment, 32, 9, pp. 18-24, (2012)
  • [10] Wu X., Wang X., Wang J., Et al., Economic generation scheduling of a microgrid using mixed integer programming, Proceedings of the CSEE, 33, 28, pp. 1-7, (2013)