To maximise functional efficacy and reliability of distributed generations (DGs), this study leads to modelling, control, stability analysis, and hardware validation of a new adaptive current controller in the application of an on-grid voltage source converter (VSC) system. For effective mitigation of power system hindrances without affecting the power quality (PQ), selftuning of weights associated with the proposed variable leaky adaptive step-size-least mean square (VLAS-LMS) control algorithm based on artificial neural network (ANN) is updated in natural frame and felicitous shaping of VSC outputs are witnessed. The selection of a constant step-size associated with proposed controller usually yields updating of same weights by all the sampling periods and hardly takes care of rate of convergence factor, which decides the stability of the controller. It can no longer avoid wavering of weights during grid disturbances, resulting in high-filtering gains. Again, a constant leaky factor may lead to over-or under-parameterisation of regularisation component. These disputes can be overcome in the proposed algorithm by the introduction of an adaptive step size along with a variable leaky factor. Furthermore, PQ is maintained as tradeoff by the inclusion of detuned LC filter. Experimental outcome ensures the validation and effectiveness of the proposed controller.
A relative assessment on conventional and adaptive current controllers used in reduced sensor-maximum power point tracking (MPPT) based photovoltaic (PV)-grid tied inverter systems for the improvement of system power quality is suggested. The steadystate and transients errors produced in the conventional PI and proportional resonant controllers, which are used to generate the references, can be fixed by using an intelligent ADALINE-LMS adaptive controller; moreover, it helps in reducing the %THD (total harmonic distortion) level measured at different power zones. Also, to track the maximum PV power, which is further integrated to DC-bus, a reduced sensor-based technology is added into the circuit that sidesteps the problem of tracking local MPP instead of global MPP and the drawbacks of using current sensors. The use of a reduced sensor-based MPPT controller confirms extraction of maximum PV power and it guarantees a constant DC-link voltage under all the possible test conditions. The overall control architectures and system performances, which are tested under different system dynamics, are validated through MATLAB/Simulink as well as experimental findings obtained using the dSPACE RTI 1202 interfacing kit. These experimental results confirm that the adaptive control technique used in reduced sensor-MPPT based PV-grid tied inverter systems performs unbeatably with balanced load and grid voltages, less harmonics, quick response time etc. under the operation of linear, non-linear and transient loads, whereas, conventional controllers are best only for the linear loads.
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