In this paper, we present a direct power control (DPC) of three-phase pulsewidth modulation rectifier with constant switching frequency using space-vector modulation (SVM). The developed DPC scheme is based on the predictive control strategy to achieve direct control of instantaneous active and reactive power of the converter. For this purpose, at the beginning of each switching period, the required rectifier average voltage vector allowing the cancellation of active and reactive power tracking errors, at the end of the switching period, is calculated by means of predictive control algorithm in the sense of deadbeat control. The main advantages of the proposed control, compared to the works published in this subject, are that no need to use predefined switching table and voltage vector or virtual flux position, PI-based active and reactive power control loops are not necessary and constant-switching frequency. The proposed predictive direct power control was tested both in simulations and experimentally and compared with DPC using switching table. Results have proved excellent performance, and verify the validity of the proposed DPC scheme, which is much better than conventional DPC using switching table.

In this paper an intelligent method of maximum power point tracking (MPPT) using fuzzy logic control for stand-alone photovoltaic (PV) system has been presented. The PV system is composed of PV solar array, buck DC-DC converter, and MPPT controller. Fuzzy logic controller (FLC) is easy to implement, and does not need knowledge of the exact model of the system. Simulation results compared with those obtained by the conventional perturbation and observation (P&O) technique show the effectiveness of the fuzzy logic controller during steady-state and varying weather conditions

This paper proposes a novel and simple direct power control (DPC) scheme of a three-phase pulsewidth-modulated rectifier without the use of a predefined switching table. The converter switching state selection is based on fuzzy logic rules, using the instantaneous active and reactive power tracking errors as fuzzy logic variables. The basic idea of fuzzy rules synthesis is based on the knowledge of the instantaneous variation of active and reactive power. According to the input fuzzy variables and in a specific moment, the best switching state of the converter is chosen to restrict the instantaneous active and reactive power tracking errors simultaneously, for maintaining the DC-bus voltage close to the reference value and guarantying the unity-power-factor operation. The main advantages of the proposed DPC scheme, compared to the classical one, are that it is not necessary to use hysteresis comparators, and smooth control of active and reactive power is obtained during all sectors. Finally, the developed DPC was tested both in simulations and experimentally, and illustrative results are presented here. Results have proven excellent performance, and verify the validity of the proposed DPC scheme which is much better than the classical DPC.

Maximum Power Point Tracking (MPPT) methods are used in photovoltaic (PV) systems to continually maximize the PV array output power, which strongly depends on both solar radiation and cell temperature. The PV power oscillations around the maximum power point (MPP) resulting from the conventional methods and complexity of the non-conventional ones are convincing reasons to look for novel MPPT methods. This paper deals with simple Genetic Algorithms (GAs) based MPPT method in order to improve the convergence, rapidity, and accuracy of the PV system. The proposed method can also efficiently track the global MPP, which is very useful for partial shading. At first, a review of the algorithm is given, followed with many test examples; then, a comparison by means Matlab/Simulink© (R2009b) is conducted between the proposed MPPT and, the popular Perturb and Observe (PO) and Incremental Conductance (IC) techniques. The results show clearly the superiority of the proposed controller. Indeed, with the proposed algorithm, oscillations around the MPP are dramatically minimized, a better stability is observed and increase in the output power efficiency is obtained. All these results are experimentally validated by a test bench developed at LIAS laboratory (Poitiers University, Poitiers, France) using real PV panels and a PV emulator which allows one to define a profile insolation model. In addition, the proposed method permits one to perform the test of linearity between the optimal current ${\mathrm{I}}_{\mathrm{mp}}$ (current at maximum power) and the short-circuit current ${\mathrm{I}}_{\mathrm{sc}}$ , and between the optimal voltage ${\mathrm{V}}_{\mathrm{mp}}$ and open-circuit voltage ${\mathrm{V}}_{\mathrm{oc}}$ , so the current and voltage factors can be easily obtained with our algorithm.