The evolving multiphase induction generators (MPIGs) with more than three phases are receiving prominence in high power generation systems. This paper aims at the development of a comprehensive model of the wind turbine driven seven-phase induction generator (7PIG) along with the necessary power electronic converters and the controller for grid interface. The dynamic model of the system is developed in MATLAB/Simulink (R2015b, The MathWorks, Inc., Natick, MA, USA). A synchronous reference frame phase-locked loop (SRFPLL) system is incorporated for grid synchronization. The modeling aspects are detailed and the system response is observed for various wind velocities. The effectiveness of the seven phase induction generator is demonstrated with the fault tolerant capability and high output power with reduced phase current when compared to the conventional 3-phase wind generation scheme. The response of the PLL is analysed and the results are presented.
Abstract:The evolving multiphase induction generators (MPIG) with more than three phases are receiving prominence in high power generation systems. This paper aims at the development of a comprehensive model of the wind turbine driven seven-phase induction generator (7PIG) along with necessary the power electronic converters and controller for grid interface. The dynamic model of the system is developed in Maltlab/Simulink. Synchronous reference frame phase-locked loop (SRFPLL) system is incorporated for grid synchronization. The modeling aspects are detailed and the system response is observed for various wind velocities. The effectiveness of seven phase induction generator is demonstrated with the fault tolerant capability and high output power with reduced phase current when compared to conventional 3-phase wind generation scheme. The response of the PLL is analyzed and the results are presented.
Herein, an optimal control approach for the energy management of hybrid energy storage system (HESS) like battery, supercapacitor (SC), and integrated charging unit in plugin hybrid electric vehicle (PHEV) is proposed. The proposed approach is the combination of both the jellyfish search optimizer (JS) and gradient boosting decision tree algorithm (GBDT) and it is termed as JS‐GBDT approach. The high energy density battery and high power density SC are combined for satisfying the demand of vehicle. To balance the charging, an uncontrolled rectifier with DC to DC buck converter, and to guarantee smooth transition of energy, two bidirectional DC–DC buck–boost converters are utilized. To meet the load requirements, GBDT approach predicts and integrates the total power supply and the charging level of the power source. The output voltage regulation, reference generation, and smooth tracking of current are performed by the energy management of PHEV using JS approach. The proposed methodology is executed on MATLAB/Simulink working platform. The performance of the HESS is evaluated by utilizing the comparison analysis with existing systems. From the analysis, the proposed approach provides less stress for primary and secondary sources and improves the charging unit performance and enhances the battery life.
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