access icon free Model reference adaptive control of STATCOM for grid integration of wind energy systems

This article proposes a model reference adaptive control (MRAC) of static synchronous compensator (STATCOM) for enhancing the integration of driven wind turbine-based self-excited induction generator (SEIG) into electrical grids. An MRAC-based Massachusetts Institute of Technology adaptive mechanism is utilised to control the reactive power flow of grid-integrated SEIG. The voltage-source inverter sinusoidal pulse width modulation of the STATCOM is used to overcome the abnormal operating conditions in the wind energy conversion system. This accordingly increases the low-voltage ride through (LVRT) capability. The abnormal operating conditions are faults occurring at the point of common coupling between the generator and the grid. The proposed MRAC is compared to proportional-integral (PI) controllers tuned by genetic algorithm (GA). To evaluate the proposed control of STATCOM for enhancing grid-integrated SEIG, a part of the Egyptian 220 kV network integrated with Zafarana Wind Energy System is used. The results provide evidence of an efficient and robust proposed adaptive control performance rather than static PI controller whose parameters tuned by GA in the voltage, currents, and wind generator speed responses. Moreover, the proposed controller increases the capability of continuous operation of the wind turbines under different abnormal operating conditions and also increases the LVRT capability.

Inspec keywords: wind power plants; load flow control; asynchronous generators; static VAr compensators; PI control; adaptive control; genetic algorithms; reactive power control

Other keywords: model reference adaptive control; static synchronous compensator; PI controllers; GA; STATCOM; proportional-integral controllers; driven wind turbine-based self-excited induction generator; grid integration; SEIG; Massachusetts Institute of Technology adaptive mechanism; LVRT capability; wind energy conversion system; static PI controller; adaptive control performance; reactive power flow control; Egyptian network; point-of-common coupling; wind generator speed responses; voltage-source inverter sinusoidal pulse width modulation; low-voltage ride through capability; MRAC; Zafarana wind energy system; genetic algorithm; wind energy systems

Subjects: Optimisation techniques; Self-adjusting control systems; Power and energy control; Control of electric power systems; Wind power plants; Asynchronous machines; Optimisation techniques

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-epa.2017.0662
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content/journals/10.1049/iet-epa.2017.0662
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