In order to achieve the maximum power point (MPP) of photovoltaic (PV) system as quickly as possible and improve the MPPT adaptability to the varying weather conditions, in this paper, a maximum power point tracking (MPPT) control strategy with variable weather parameters (VWP) is proposed. In this strategy, the MPP difference between PV system with and without DC/DC converter is analyzed and used as the theoretical basis of acquiring the MPP control signal. Meanwhile, the direct relationship between control signal and VWP is found out by the curve-fitting technique, which is the key work to implement this proposed strategy. Finally, some simulation experiments show that the proposed control strategy is feasible and available to track the MPP successfully, and has better MPPT performance than conventional perturbation and observation (P&O) method under different weather conditions and than fuzzy control method under fast changing weather conditions.
Now almost all PV systems use the MPPT technique to avoid the produced power losses. These methods or strategies for MPPT control are mainly include the constant voltage tracking (Mohanty et al., 2014), the P&O method (Liu et al., 2014; Ahmed and Salam, 2015; Jiang et al., 2014; Ishaque et al., 2014), the incremental conductance (IncCond) method (Ishaque et al., 2014; Sivakumar et al., 2015; Elgendy et al., 2013), the genetic algorithm (Shaiek et al., 2013; Deshkar et al., 2015), the fuzzy logic control method (Mellit and Kalogirou, 2014; Guenounou et al., 2014), the neural network method (Salam et al., 2013), the sliding mode control method (Zhang et al., 2015; Hong and Chen, 2014), the predictive control technique (Tsang and Chan, 2013), and so on. In them, the P&O method, which is regarded as the representation of classical MPPT methods, and the fuzzy control method, which is regarded as the representation of intelligent MPPT methods, have been widely used in practical application. The advantages of P&O method mainly include its low-cost hardware, easy implementation and good performance without solar irradiance and temperature varying quickly with time. However, there are also some shortcomings including its slow tracking speed and oscillation around MPP. The fuzzy control method mainly has the good performance under fast changing weather conditions while carrying its high-cost processor and its difficult acquisition of empirical data. In this paper, the P&O method and the fuzzy control technique are all selected as the compared object in order to study the output performance of proposed MPPT strategy.
In this paper, through analyzing the effect of the DC/DC converter to the MPP of PV system, a MPPT control strategy with VWP, which has the ability to track the MPP more rapidly, has been proposed. In this study, the key work is to find out the way for acquiring the control signal at the MPP through analyzing deeply the difference between PV system with and without DC/DC converter. Meanwhile, the acquisition of mathematical relationship between control signal and VWP is also playing a key role to implement this proposed MPPT strategy. Finally, by simulation experiments, the feasibility and availability of this proposed control strategy have been verified, and the MPPT performance of this proposed control strategy has been analyzed under different weather conditions and has been compared with fuzzy method and P&O method under fast varying irradiance conditions.