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Solar array simulators (SAS) equipment is used to mimic the characteristics curve for photovoltaic (PV) generators. However, an in-depth stability analysis of the SAS with respect to its reference signal is yet to be investigated. This is due to implicit and nonlinear mapping equations used to describe the $I\text{--}V$ curve, which complicates the loop analysis. Our study proposes a super-elliptical method to approximate the $I\text{--}V$ characteristic curve and provide an explicit PV equation that is straightforward to manipulate. Furthermore, this approximate model is then used for the dynamic performance assessment for the typical control architecture. Based on the comparative study using the approximate mode either in the theoretical analysis and the experimental verification, the resistance-sensing control scheme tends to reduce the effect of loop interactions in the SAS, thereby showing more consistent dynamic performance than the other control structure. [ABSTRACT FROM AUTHOR]

The efficiency of photovoltaic generation systems depends on the maximum power point tracking (MPPT) technique. Among the various schemes presented in the literature, the incremental conductance (INC) method is one of the most frequently used due to its superb tracking ability under changes in insolation and temperature. Generally, conventional INC algorithms implement a simple duty-cycle updating rule that is mainly found on the polarity of the peak-power evaluation function. However, this fails to maximize the performance in both steady-state and transient conditions. In order to overcome this limitation, a novel regulated INC (r-INC) method is proposed in this paper. Like the compensators in automatic control systems, this method applies a digital compensator to evaluate the INC function and improve the capability of power tracking. Precise modeling of a new MPPT system is also presented in the optimized design process. A 120W boost peak power tracker is utilized to obtain comparative test results and to confirm the superiority of the proposed method over existing techniques. [ABSTRACT FROM AUTHOR]

Maximum power point tracking (MPPT) under the partial shading condition is a challenging research topic for photovoltaic systems. Shaded photo-voltaic module result in complex peak patterns on the power versus voltage curve which can misguide classical MPPT algorithms. Thus, various kinds of global MPPT algorithms have been studied. These have typically consisted of partial shading detection, global peak search and MPPT. The conventional partial shading detection algorithm aims to detect all of the occurrences of partial shading. This results in excessive execution of global peak searches and discontinuous operation of the MPPT. This in turn, reduces the achievable power for the PV module. Based on a theoretical investigation of power verse voltage curve patterns under various partial shading conditions, it is realized that not all the occurrences of partial shadings require a global peak search. Thus, an intelligent partial shading detection algorithm that provides exact identification of global peak search necessity is essential for the efficient utilization of solar energy resources. This paper presents a new partial shading determinant algorithm utilizing adaptive threshold levels. Conventional methods tend to be too sensitive to sharp shading patterns but insensitive to smooth patterns. However, the proposed algorithm always shows superb performance, regardless of the partial shading patterns. [ABSTRACT FROM AUTHOR]