A Model Predictive Control-Based Voltage and Frequency Regulation through Distributed Generation in Isolated Microgrids: Part II Model Predictive Controller Implementation

被引:0
作者
Shabbir, Md Nasmus Sakib Khan [1 ]
Liang, Xiaodong [1 ]
Li, Weixing [2 ]
Imtiaz, Syed [3 ]
Quaicoe, John [4 ]
机构
[1] Univ Saskatchewan, Dept Elect & Comp Engn, Saskatoon, SK, Canada
[2] Dalian Univ Technol, Sch Elect Engn, Dalian, Liaoning, Peoples R China
[3] Mem Univ Newfoundland, Dept Proc Engn, St John, NL, Canada
[4] Mem Univ Newfoundland, Dept Elect & Comp Engn, St John, NL, Canada
来源
2022 IEEE/IAS 58TH INDUSTRIAL AND COMMERCIAL POWER SYSTEMS TECHNICAL CONFERENCE (I&CPS) | 2022年
关键词
Distributed generation; disturbance rejection; islanded microgrid; Kalman filter; model predictive control; self-adaptive; state observer; DROOP CONTROL METHOD; ANGLE DROOP; INVERTERS; IMPEDANCE; STABILITY;
D O I
10.1109/ICPS54075.2022.9773851
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
To realize operation automation in remote islanded microgrids, a model predictive control (MPC)-based distributed generation (DG) controller is proposed in Part 2 of this paper. The developed data-driven predictive model in Part 1 of this paper is implemented in Part 2 to realize the MPC controller. The proposed MPC controller does not incorporate any tunable coefficients, which may be sensitive under various operating conditions. Kalman filter-based state observer updates the system model with varying operating conditions. The KWIK optimizer is used to solve the MPC's constrained quadratic programming problem as it ensures a guaranteed convergence. The controller is smaller in size and does not require any intra-DG communication network. It ensures equal and proportional power sharing despite feeder line impedance mismatch. The effectiveness of the proposed MPC controller is validated through case studies.
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页数:8
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