1. Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid
- Author
-
Bi Daqiang, Min-Rong Chen, Kang-Di Lu, Guo-Qiang Zeng, and Yuxing Dai
- Subjects
0209 industrial biotechnology ,Control and Optimization ,Wind power ,Renewable Energy, Sustainability and the Environment ,business.industry ,Computer science ,020209 energy ,Automatic frequency control ,Energy Engineering and Power Technology ,Order (ring theory) ,02 engineering and technology ,Function (mathematics) ,Optimal control ,Field (computer science) ,Model predictive control ,020901 industrial engineering & automation ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,optimal frequency control ,islanded microgrid ,fractional-order calculus ,model predictive control ,cost function ,Microgrid ,Electrical and Electronic Engineering ,business ,Engineering (miscellaneous) ,Energy (miscellaneous) - Abstract
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.
- Published
- 2018