Real-Time MPPT Optimization of PV Systems by Means of DCD-RLS Based Identification

Maximum power point tracking (MPPT) algorithms continuously change duty cycle of a power converter to extract maximum power from photovoltaic panels. In all of MPPT methods, two parameters, i.e., perturbation period
$(T_{p})$
and amplitude
${(\Delta \text{D)}}$
, have a great effect on speed and accuracy of MPPT. Optimum value of the perturbation period is equal to the system settling time, which is the system model-dependent parameter. Since the system model varies according to the change of irradiance level and temperature, the value of
$T_{p}$
has to be determined online. In this paper, the parametric identification method is adopted to identify the online value of
$T_{p}$
. The proposed method is based on the dichotomous coordinate descent-recursive least squares algorithm and uses an infinite impulse response adaptive filter as the system model. Computation of this algorithm is based on an efficient, fixed-point, and iterative approach with no explicit division operations; these features are highly suitable for online applications. As a result, the proposed method compared to previous works leads to more accurate and faster identification of the system settling time. To test and validate the proposed method, it has been simulated and implemented to be further validated with experimental data.