The objective of the proposed work is to develop a Maximum Power Point Tracking (MPPT) controller and inverter controller by applying the adaptive least mean square (LMS) algorithm to control the total harmonics distortion of a solar photovoltaic system. The advantage of the adaptive LMS algorithm is given by its simplicity and reduced required computational time. The adaptive LMS algorithm is applied to modify the Perturb and Observe (P&O), MPPT controller. In this controller, the adaptive LMS algorithm is used to predict solar photovoltaic power. The adaptive LMS maximum power point tracking controller gives better optimal solutions with less steady error 0.7% (6 watts) and 0% peak overshot in power with the tradeoff being more settling time at 0.33 s. The development of the inverter control law is performed using the d-q frame theory. This helps to reduce the number of equations to build a control law. The load current, grid current and grid voltage are sensed and transformed into d and q components. This adaptive LMS control law is used to extract the reference grid currents and, later, to compare them with the actual grid currents. The result of this comparison is used to generate the switching gate pulses for the inverter switches. The proposed controllers are developed and implemented with a solar PV system in MATLAB Simulink. The total harmonics distortion in grid and load current (3.25% and 7%) and voltage (0%) is investigated under linear and non-linear load conditions with changes in solar irradiations. The analysis is performed by selecting step incremental values and sampling time.

A Least Mean Square (LMS) adaptive Finite Impulse Response (FIR) filter-predictive controller is presented for the control of a grid-connected solar PV energy system. The objective of the work is to reduce total harmonic distortion (THD) in the grid and load current. It follows the systematic development and analysis of the implementation of an adaptive LMS control based on the direct-quadrature control theory. The analysis is done for the proposed adaptive control technique for grid-connected solar photovoltaic systems under the variation of solar irradiation and load. In this proposed work, the reference current is estimated by developing the LMS control technique. The proposed system is modeled in d-q frame form and simulated on the MATLAB Simulink platform. Developing an LMS control algorithm using the p-q theory reduces computational hard work. The reduction in load current harmonics is improved. The simulation results are used to discuss the convergence rate, harmonics reduction, and advantages of the adaptive LMS algorithm d-q control theory.