scholarly journals Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 84 ◽  
Author(s):  
Min-Rong Chen ◽  
Guo-Qiang Zeng ◽  
Yu-Xing Dai ◽  
Kang-Di Lu ◽  
Da-Qiang Bi

Optimal frequency control of an islanded microgrid has been a challenging issue in the research field of microgrids. Recently, fractional-order calculus theory and some related control methods have attempted to handle this issue. In this paper, a novel fractional-order model predictive control (FOMPC) method is proposed to achieve the optimal frequency control of an islanded microgrid by introducing a fractional-order integral cost function into model predictive control (MPC) algorithm. Firstly, a discrete state-space model is derived for the optimal frequency control problem of an islanded microgrid. Afterward, a fractional-order integral cost function is designed to guide the FOMPC algorithm to obtain optimal control law by borrowing the Grünwald-Letnikov (GL) definition of fractional order calculus. Six simulation studies have been carried out to illustrate the superiority of FOMPC to conventional MPC under dynamical load disturbances, perturbed system parameters and random dynamical power fluctuation of wind turbines.

Processes ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 451 ◽  
Author(s):  
Shiquan Zhao ◽  
Ricardo Cajo ◽  
Robain De De Keyser ◽  
Clara-Mihaela Ionescu

The steam/water loop is a crucial part of a steam power plant. However, satisfying control performance is difficult to obtain due to the frequent disturbance and load fluctuation. A fractional order model predictive control was studied in this paper to improve the control performance of the steam/water loop. Firstly, the dynamic of the steam/water loop was introduced in large-scale ships. Then, the model predictive control with an extended prediction self adaptive controller framework was designed for the steam/water loop with a distributed scheme. Instead of an integer cost function, a fractional order cost function was applied in the model predictive control optimization step. The superiority of the fractional order model predictive control was validated with reference tracking and load fluctuation experiments.


Author(s):  
Qihui Fu ◽  
Zishun Peng ◽  
Zipeng Ke ◽  
Huimin Quan ◽  
Zhenxing Zhao ◽  
...  

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