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The research into series connection of dc–dc converters has been concentrating more recently on creating a high voltage low current string. However, the interleaving technique of series-connect photovoltaic (PV) module integrated converters (MICs) has not been sufficiently addressed so far. This paper proposes a low cost high performance interleaving technique based on series PV MICs to reduce the output voltage-ripples. With the reduced voltage-ripples, the size and cost of capacitors at grid connected inverters can be reduced. The proposed technique is capable of solving the problem for PV panels with mismatched operating conditions. Each PV panel is able to track its own maximum power point (MPP) which simultaneously delivers the maximum power for the system. The proposed technique is mathematically investigated based on boost (step-up) converters and validated by Simulink/Matlab simulation and experiment results. The MPP tracking (MPPT) algorithm is tested for a PV/battery charging system with satisfactory performances in both steady-state and transient responses with reduced voltage-ripples.

This paper proposed an adaptive neuro-fuzzy model (ANFIS) to multilevel inverter (MLI) for grid connected photovoltaic (PV) system. The purpose of the proposed controller is that it is not requiring any optimal pulse width modulated (PWM) switching-angle generator and proportional–integral controller. The proposed method strictly prohibits the variations present in the output voltage of the cascaded H-bridge MLI. In this method, the ANFIS have the input which is grid voltage, the difference voltage and the output target is control voltage. By using these parameters, the ANFIS makes the rules and has been tuned perfectly. During the testing time, the ANFIS gives the control voltage according to the different inputs. The resultant control voltage equivalent gate pulses are utilized for controlling the insulated gate bi-polar switches (IGBT) of MLI. Then the ANFIS based MLI for grid connected PV system is implemented in the MATLAB/simulink platform and the effectiveness of the proposed control technique is analyzed by comparing with the neural network (NN), fuzzy logic control, etc. The comparison results demonstrate the superiority of the proposed approach and confirm its potential to solve the problem. A prototype of three-phase grid connected cascaded H-bridge inverter has been developed using field-programmable gate array (FPGA) and results are analyzed.

Power quality (PQ) issue is referred to as any problem that exposes in the voltage and current or in frequency value that causes a malfunction of protection devices or maloperation of the system. The improvement of the PQ is important at the load side when the production processes get more complicated and require a bigger liability level. An Elephant Herding Optimization (EHO) algorithm is presented for improving the PQ and reducing the harmonic distortion using the Static Switched Filter Compensation (SSFC) in Photovoltaic (PV) interconnected wind energy conversion system (WECS). The novelty of the proposed system is enhancing the performance of the grid-connected hybrid energy system such as stabilizing the voltage, reducing the power loss and mitigating the harmonic distortion using the SSFC. Here, the proposed controller is used to optimize the control pulses for SSFC. The SSFC and voltage-source converters with smart dynamic controllers are emerging as stabilization and power filtering equipment to improve the PQ. The proposed method has implemented in MATLAB/Simulink platform and their performances are evaluated and contrasted with the existing technologies such as Bat algorithm (BA) and Firefly algorithm (FA) techniques.

A new generation of metal-free organic dyes with a range of donor (D1) and acceptors (A1-A3) were designed and examined for dye-sensitized solar cells (DSSCs) based on (3a) dye as a literature. Triphenylamine (TPA), thiophene ($\pi )$ and 2-cyanoacrylic acid groups each perform the roles of an acceptor (A), donor (D) and spacer in order to produce a D-$\pi$-A system. To investigate the intramolecular charge transfer (ICT), electronic distribution, ultra-violet visible (UV–Vis) absorption wavelengths, molecular electrostatic potential (MEP) and photovoltaic (PV) parameters of the D1 and A1–A3 molecules, density functional theory (DFT) and time-dependent DFT (TD-DFT) were used. The classification of the tunable donor D1 and A1–A3 determines the PV performance of the dye molecules. Results show that the A2 dye replacement group increases the performance of PV cells via red-shifting absorption spectra. Also, when compared to 3a, A2 dye have lower energy gap ($E_g)$ and superior UV–Vis spectra that cover the full visible range. These results demonstrate the viability of molecular tailoring as an approach to improve D-$\pi$-A sensitizer proposal for efficient DSSCs fabrication.

Solar energy and wind energy are the two most viable renewable energy resources in the world. Hybrid PV-wind generation systems are becoming popular for remote areas (such as Hong Yuan in Sichuan) power applications because of the good complementary effect of solar radiation and wind speed. This paper introduces a modeling of hybrid PV-wind generating system (HPWGS) and describes mathematically to model HPWGS components. An analysis of the complementary and charge-discharge strategies of solar and wind for remote area is presented. It can be deduced that the LPSP method is being considered to be implemented for a hybrid PV-wind generation system employing a battery bank.