A new LQG optimal control strategy applied on a hybrid wind turbine/solid oxide fuel cell/ in the presence of the interval uncertainties. (March 2020)

• Record Type: Journal Article
• Authors: Yu, Dongmin; Mao, Yingying; Gu, Bing; Nojavan, Sayyad; Jermsittiparsert, Kittisak; Nasseri, Maryam
• Is Part Of: Sustainable energy, grids and networks. Volume 21(2020)
• Publication Date: 2020-03
• Subjects: Gas turbine -- Solid oxide fuel cell -- Hybrid -- Interval analysis -- Chebyshev inclusion method -- LQG control design -- Uncertainty; Renewable energy sources -- Periodicals; Smart power grids -- Periodicals; Electric power systems -- Periodicals; 333.794
• DOI: 10.1016/j.segan.2019.100296
• Languages: English
• ISSNs: 2352-4677

Abstract

Abstract: In recent years, the application of solid oxide fuel cells is increasingly progressed as popular sustainable energy resources. The most advantage of the solid oxide fuel cells is that they can work in high temperatures to cooperation with other power generators for achieving a high-performance hybrid plant. In this paper, a hybrid system including the Gas turbine along with solid oxide fuel cells is utilized to design a reliable power generating system. Designing a proper control system for the hybrid solid oxide fuel cell and the gas turbine makes a significant impact on the system's robustness. The main purpose of this study is to propose a control strategy to improve the system's lifetime. The most important part of the present study is to consider the system model uncertainties and to utilize the interval analysis for solving a model of the considered hybrid system in the presence of interval uncertainties derived from its parameters. The final result of this method is to achieve a confidence interval for the problem. To do so, an extended version of the LQG control methodology based on interval analysis is proposed for obtaining a robust and optimal solution. Chebyshev inclusion method is utilized for solving the Riccati equation of the LQG system. Simulation results show a higher efficiency of the proposed system and its impact on the reliability of the system by performing a comparison with the ordinary LQR controller and De-centralized method for showing the efficiency of the proposed method.