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In this study, an optimisation method, based on bacteria foraging, is investigated to tune the parameters of the proportional-integral (PI) controllers in a doubly-fed induction generator (DFIG) wind energy system connected to the grid. The generator is connected to the grid directly at the stator and through the back-to-back converter at the rotor. The control system includes PI controllers, at the rotor side, to regulate the rotor currents and PI controller to regulate the dc-link voltage for efficient power transfer. The control parameters, of three PI controllers, are optimised offline using the bacteria foraging optimisation algorithm and a modelled DFIG wind energy system. Various performance criteria, based on the tracking errors, are used to assess the efficiency of the optimisation method. Furthermore, the conventional tuning method and genetic algorithm optimisation method are conducted and compared to the bacteria foraging optimisation method to demonstrate its advantages. The optimised control parameters are evaluated on a DFIG wind energy experimental setup. Experimental and simulation results are provided to validate the effectiveness of each optimisation method.

In photovoltaic (PV) applications, employing Surface-Mounted Permanent Magnet Synchronous Motor (SMPMSM) can be a suitable option, especially for solar pumping and Heating, Ventilation, and Air Conditioning (HVAC) applications. However, when the motor loads are supplied from varying and limited energy sources, such as solar PV, it is vital to determine operating behavior and provide a stable operation for a wide range of operating conditions. In this study, the operating stability of Permanent Magnet Synchronous Motor (PMSM) was improved by sensorless Field Oriented Control (FOC) based on Extended Kalman Filter (EKF). In order to achieve optimal operation of the PV system under various meteorological conditions and load variations, an incremental conductance approach based maximum power point tracking (MPPT) system was introduced. For estimation of the speed of PMSM in wide speed range, instead of using a hybrid estimation strategy, fixed d-axis current with EKF was applied to the low-speed regions of SMPMSM, while in the medium and high speed regions, the d-axis current was set to zero. The major contributions of this paper are to reduce complexity of the control method and testing the method in a photovoltaic system with MPPT operation. The complete system was modeled in a Matlab/Simulink environment and simulation results are shown according to a wide range of operating conditions.

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