Primary Frequency Control of Doubly Fed Induction Generator- Superconducting Magnetic Energy Storage Complementary System
Liu Wei1, 2, Gu Wei1, 2, Sun Rong3, Li Qun3, Wang Rui1, 2
1. Southeast University Nanjing 210096 China 2. Jiangsu Key Laboratory of Smart Grid Technology and Equipment Zhenjiang 212009 China 3. Jiangsu Electric Power Research Institute Nanjing 211103 China
Abstract:Due to the development of wind power, the frequency control capacity of wind farm is required, so the additional frequency control and the coordination with stored energy win particular attention recently. A new fuzzy neural network combination control is proposed to doubly fed induction generator(DFIG)-superconducting magnetic energy storage(SMES) complementary system. It takes advantage of the learning ability of neural network to form an adaptable fuzzy neural controller to control the rotor kinetic energy and reserve power of DFIG; and it also optimizes the active power of SMES to give frequency control support during sizeable frequency deviation. The performance of the control strategy is simulated based on 4 machine 2 area system, the results indicate that the proposed fuzzy neural control strategy has good robustness, and the complementary system can effectively improve the frequency control stability of system.
柳伟, 顾伟, 孙蓉, 李群, 王锐. DFIG-SMES互补系统一次调频控制[J]. 电工技术学报, 2012, 27(9): 108-116.
Liu Wei, Gu Wei, Sun Rong, Li Qun, Wang Rui. Primary Frequency Control of Doubly Fed Induction Generator- Superconducting Magnetic Energy Storage Complementary System. Transactions of China Electrotechnical Society, 2012, 27(9): 108-116.
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