Finite-time convergence robust control of battery energy storage system to mitigate wind power fluctuations |
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| Affiliation: | 1. SYSU-CMU Joint Institute of Engineering, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, Guangdong 510275, China;2. School of Electrical Engineering, Southeast University, Nanjing 210096, China;3. Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, China;1. Longitude 122 West, Inc., 885 Oak Grove Avenue, Menlo Park, CA 94025, USA;2. Zero Carbon Energy Solutions, Inc., 3534 Brunell Drive, Oakland, CA 94602, USA;1. Department of Industrial Engineering, University of Salerno, via Giovanni Paolo II 132, Fisciano, SA, Italy;2. Research Center of Portici, ENEA, Portici, NA, Italy;1. University of Shahreza, Dep. of Electrical Engineering, Shahreza, Iran;2. Amirkabir University of Technology, Dep. of Electrical Engineering, Tehran 15916-34311, Iran;3. Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education (Dept. of Electrical Engineering, Shanghai Jiao Tong University), Shanghai, China |
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| Abstract: | Wind energy is envisioned to be one of the most promising clean and renewable energy to drive our future society. Due to its intermittency nature, wind power may change rapidly and frequently. Wind power fluctuations pose great challenges on power quality, reliability and raise many other issues like frequency and voltage regulation. This paper proposes a finite-time convergence robust control algorithm of battery energy storage system (BESS) to mitigate the wind power fluctuations. The major advantages of the proposed algorithm include, being insensitive to uncertainty and disturbance, enabling adjustable convergence time to accommodate different operating conditions and maintaining the state of charge (SOC) within a proper range for regulation capability reserve. Finite-time convergence of the proposed algorithm is derived through rigorous analysis. Simulation results demonstrate the effectiveness of the proposed algorithm. |
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| Keywords: | Finite-time convergence Robust control Energy storage system State of charge Uncertainty |
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