A New Hybrid MPPT Based on Incremental Conductance-Integral Backstepping Controller Applied to a PV System under Fast-Changing Operating Conditions

Abstract

Maximum power point tracking (MPPT) is becoming more and more important in the optimization of photovoltaic systems. Several MPPT algorithms and nonlinear controllers have been developed for improving the energy yield of PV systems. On the one hand, most of the conventional algorithms such as the incremental conductance (INC) demonstrate a good affinity for the maximum power point (MPP) but often fail to ensure acceptable stability and robustness of the PV system against fast-changing operating conditions. On the other hand, the MPPT nonlinear controllers can palliate the robust limitations of the algorithms. However, most of these controllers rely on expensive solar irradiance measurement systems or complex and relatively less accurate methods to seek the maximum power voltage. In this paper, we propose a new hybrid MPPT based on the incremental conductance algorithm and the integral backstepping controller. The hybrid scheme exploits the benefits of the INC algorithm in seeking the maximum power voltage and feeds a nonlinear integral backstepping controller whose stability was ensured by the Lyapunov theory. Therefore, in terms of characteristics, the overall system is a blend of the MPP-seeking potential of the INC and the nonlinear and robust potentials of the integral backstepping controller (IBSC). It was noted that the hybrid system successfully palliates the conventional limitations of the isolated INC and relieves the PV system from the expensive burden of solar irradiance measurement. The proposed hybrid system increased the operational efficiency of the PV system to 99.94% and was found better than the INC MPPT algorithm and 8 other recently published MPPT methods. An extended validation under experimental environmental conditions showed that the hybrid system is approximately four times faster than the INC in tracking the maximum power with better energy yield than the latter.

A New High-Performance Photovoltaic Emulator Suitable for Simulating and Validating Maximum Power Point Tracking Controllers

“…Therefore, it becomes imperative to continually track this point and ensure that PV systems operate at their maximum energy potential [20]. In the spirit of optimizing PV systems, numerous maximum power point tracking (MPPT) algorithms/controllers have been developed in this recent decade [19,[30][31][32][33]. The perturb and observe (P&O) and incremental conductance algorithm (INC) are the most popular MPPT algorithms/controllers.…”

“…9 International Journal of Photoenergy converter. Therefore, in this paper, we refer to the control algorithm developed for a boost converter as seen in the recently published work of [33].…”

“…To ensure that the system operates at the maximum power point, Ref. [33] derived the following nonlinear control law ðu mppt Þ: and p = Ð t o ðe 1 Þdt. As seen in Equation (17) and Figure 8, C B and L B are the capacitance and inductance of the boost converter in the MPPT controller, while K 1 , K 2 , and K are the parameters of the controller.…”

“…Figure 8: Architecture of the proposed PVE coupled with an MPPT controller (MPPT stage from[33,34]). …”

Solar irradiance estimation and optimum power region localization in PV energy systems under partial shaded condition

“…Faced with such continuous variation, it is crucial to continuously track the MPP. Consequently, a series of maximum power point tracking (MPPT) algorithms have been reported in different scientific literature MPP [ [2] , [3] , [4] , [5] , [6] ]. As revealed by the literature, the classical conventional algorithm such as perturb and observe (P&O), and incremental conductance algorithm (INC) stand out as the simplest and most popular approaches.…”