Application of distributed predictive control in coordinated control of microgrid

被引:0
|
作者
Ma M.-M. [1 ,2 ]
Shao L.-Y. [1 ]
Liu X.-J. [1 ,2 ]
机构
[1] School of Control and Computer Engineering, North China Electric Power University, Beijing
[2] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing
关键词
Automatic control technology; Distributed predictive control; Economic dispatch; Microgrid; Power balance;
D O I
10.13229/j.cnki.jdxbgxb20191065
中图分类号
学科分类号
摘要
This paper proposes a distributed coordinated predictive control scheme for the power balance and economic dispatch problems of microgrid systems. We design the distributed coordinated predictive controllers for the wind power generation subsystem and solar power generation subsystem by minimizing a suitable objective function, respectively. The objective function is chosen based on the principle that the wind power subsystem is operated as the primary generation system, the solar power subsystem is considered as the auxiliary generation system, and the battery bank is only activated when the wind and solar power subsystem can't satisfy the power demand. The output of the distributed predictive controller is regarded as the reference input of each subsystem, so that it can respond to the load change in full operation condition, and distribute the output power of each subsystem reasonably. The simulation results show that the proposed distributed coordinated predictive control scheme can allocate the output power of subsystems reasonably under varying environment conditions, which not only can satisfy the load demand but also attenuate excessive fluctuations of output power to protect the power generation equipment. © 2020, Jilin University Press. All right reserved.
引用
收藏
页码:2258 / 2265
页数:7
相关论文
共 28 条
  • [1] Tomislav D, Lu X N, Vasquez J C, Guerrero J M., DC microgrids-part I: a review of control strategies and stabilization techniques, IEEE Transactions on Power Electronics, 31, 7, pp. 4876-4891, (2016)
  • [2] Tomislav D, Lu X N, Vasquez J C, Et al., DC microgrids-part II: a review of power architectures, applications, and standardization issues, IEEE Transactions on Power Electronics, 31, 5, pp. 3528-3549, (2015)
  • [3] Lopez-Gonzalez A, Domenech B, Gomez-Hernandez D., Renewable microgrid projects for autonomous small-scale electrification in Andean countries, Renewable & Sustainable Energy Reviews, 79, pp. 1255-1265, (2017)
  • [4] Jiang W, Yang C, Liu Z, Et al., A hierarchical control structure for distributed energy storage system in DC micro-grid[J], IEEE Access, 7, pp. 128787-128795, (2019)
  • [5] Zhou A., Comparison of dispatch strategy in hybrid energy micro-grid with high PV penetration, IEEE Innovative Smart Grid Technologies, (2019)
  • [6] Abdellatif E, Ouladsine R, Bakhouya M, Et al., A model predictive control approach for energy management in micro-grid systems, 2019 International Conference on Smart Energy Systems and Technologies, (2019)
  • [7] Zhou H L, Zhao Y Q, Lin S., Coordinated control strategy for photovoltaic/battery micro-grid, 2018 Chinese Automation Congress, (2018)
  • [8] Tayab U B, Roslan M A B, Hwai L J, Et al., A review of droop control techniques for microgrid, Renewable & Sustainable Energy Reviews, 76, pp. 717-727, (2017)
  • [9] Nutkani I U, Loh P C, Blaabjerg F., Droop scheme with consideration of operating costs, IEEE Transactions on Power Electronics, 29, 3, pp. 1047-1052, (2013)
  • [10] Zhao R, Zhang L Q, Xin H H, Et al., A decentralized self-optimizing control strategy for islanded microgrid, Automation of Electric Power Systems, 39, 21, pp. 30-36, (2015)