Fractional-Order Model Predictive Frequency Control of an Islanded Microgrid

• Published in: Energies (Basel) Vol. 12; no. 1; p. 84
• Main Authors: Chen, Min-Rong, Zeng, Guo-Qiang, Dai, Yu-Xing, Lu, Kang-Di, Bi, Da-Qiang
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2019
• Subjects: Algorithms; Automation; Calculus; Computer simulation; Control algorithms; Controllers; Cost function; Design; Distributed generation; Energy resources; Frequency control; Gasoline; Genetic algorithms; Laboratories; Methods; Multiple objective analysis; Operators (mathematics); Optimization; Order parameters; Process controls; Simulation; Speed control; State space models; Turbines; Wind power; China
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en12010084

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.