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Mitigation of the leakage current components represents a critical issue in transformerless photovoltaic (PV) inverters. Recently, PV inverters with inherent common-ground (CG) connection are becoming promising proposals for nearly total elimination of leakage current components. However, developing multilevel output while injecting grid currents with high quality is a challenging task for classical control schemes. This article presents a reduced computational burden weighting factorless finite-control-set model-predictive control (WFL-FCSMPC) for the CG five-level single-phase switched capacitor cells inverter-based PV systems. The proposed reduced computational burden WFL-FCSMPC avoids the cascaded control loops of classical controllers. Thence, the problems related to adjusting weighting factors of standard finite control-set model-predictive control (FCSMPC) are eliminated by dividing the control objectives into the desired cost functions. Moreover, high computational burdens in classical FCSMPC methods are considerably reduced using the proposed WFL-FCSMPC, especially at a high number of levels. Therefore, robust and simplified design and implementation are obtained by applying the proposed WFL-FCSMPC while long tuning procedures of weighting factors are avoided. Simulation and experimental results are provided for verifying the superior performance of the proposed WFL-FCSMPC over standard FCSMPC and linear controllers.

The operation of photovoltaic (PV) array under shade faces great challenges due to the power loss that reduces the extracted power. Reconfiguration process is one of the most promising solutions to reduce the effect of shadow on the array. However, the physical array relocation methods like total cross-tied (TCT) and Su Do Ku have some limitations due to their complicated arrangements. Therefore, this paper presents a recent metaheuristic approach of coyote optimization algorithm (COA) to solve the reconfiguration process of the partially shaded PV array. The main target is maximizing the global maximum power (GMP) extracted from the array. The proposed COA is applied on 9×9 PV array operated under four standard shadow patterns which are short wide (SW), long wide (LW), short narrow (SN), and long narrow (LN). The obtained configurations via the proposed COA method are compared to TCT, Su Do Ku, flower pollination algorithm (FPA), marine predators algorithm (MPA), and butterfly optimization algorithm (BOA) based arrangements. The best enhancement of GMP obtained via the proposed COA with respect to TCT configuration occurs in SW shadow pattern of 26.58% while the least on is 7.68% placed in SN pattern. The obtained results confirmed the competence and superiority of the proposed COA in reconfiguring the shaded array optimally.

Light-fidelity (Li-Fi) communication systems have gained increased concerns as new and alternative paradigm for wireless communications. Through the increased applications of light emitting diode (LED) lamps for lighting in indoor and outdoor applications, industrial and academic interests have been risen towards adding communication functionality to the standard light emitting diode lamp illumination functionality in light-fidelity systems. As being the same source for lighting and communication, extra power losses and stresses are imposed on the light emitting diode lamp and its power electronic drivers to perform the dual functionalities. Therefore, proper light emitting diode lamp driver design and control systems are required. This paper reviews the different architectures of light-fidelity communication systems and develops a powerful systematic approach for assessing the energy efficiency and the communication system performance metrics for light-fidelity systems. Various light-fidelity structures, communication modulators, power converters, and communication modulation methods are considered based on the mathematical modelling. Simulation results show that energy efficiency and communication system performance are largely affected by system architectures, components, and communication modulators. The obtained results show that the proposed method represents a systematic approach for calculating the energy efficiency and power losses for various elements in light-fidelity systems. Additionally, the calculated energy efficiency with adding the communication functionality is lower than the traditional illumination of the lamps. The type of modulation technique, type of modulator, modulation index value, and forward lamp current have substantial effects on the calculated energy efficiency.

The susceptibility of modern interconnected microgrid (MG) systems to undesirable frequency oscillations represents a critical issue resulting from the intermittency properties of renewable energy generation systems (RESs). Thence, extensive efforts are needed for developing more robust frequency regulators. Maintaining required frequency regulation using load frequency controllers (LFCs) can play a vital role in modern interconnected multi-MG systems with high levels of RESs penetration. Moreover, wide concerns exist about taking advantage of installed electric vehicle (EV) battery energy storage devices in regulating the frequency of MG systems. Therefore, this paper proposes an improved optimal fractional order (FO) LFC technique for developing robust multi-MG systems. The proposed technique uses two cascaded control loops, wherein the one plus proportional double derivative with filter (1+PDDF) in the outer loop and FO proportional integral tilt (FOPIT) control technique. To avoid complex control design procedures and parameter tuning, the recent powerful artificial hummingbird optimizer algorithm (AHA) is proposed to simultaneously optimize proposed control parameters in various interconnected multi-MG systems. The AHA optimizer outputs optimal parameters of the proposed control to achieve the best system response and stability. The proposed 1+PDDF/FOPIT control scheme yields a high rejection rate of existing disturbances resulting from uncertainties in RESs and/or loads, which enhances frequency stability and robustly mitigates frequency oscillations. Several comparisons and evaluations are provided for the proposed 1+PDDF/FOPIT control scheme and AHA optimizer with featured existing schemes in literature to prove several superiority indices of system response. For instance, the integral squared error (ISE) comparison at step load scenario for the proposed 1+PDDF/FOPIT controller was 0.31%, 0.29%, 1.25%, and 4.12% of the obtained ISE values under the studied PIT, FOPIT, 1+PDDF, and 1+PIDF/FOPID LFC methods from literature, respectively.

Multilevel inverters (MLIs) have proven superior performance in several applications, especially in photovoltaic (PV) applications. However, power switches in MLIs possess high failure rates due to unequal power losses distributions that shorten lifetime of the whole PV inverter. Therefore, a new pulsewidth modulation (PWM) methodology for loss balance in grid connected PV single-phase five-level inverters is presented in this paper. The proposed loss balance PWM (LBPWM) method is based on swapping the utilization of power switches through half or quarter of the fundamental line period based on the redundancies between the switching states in MLIs. In addition, the proposed LBPWM method achieves natural balance among voltages over the dc-link capacitors. The effectiveness and feasibility of the proposed LBPWM method are verified using the simulation environment and experimental prototype. Different operating conditions and points of PV inverters are investigated in addition to reliability evaluation of the PV inverter are provided. Moreover, the superior performance criterion of the proposed LBPWM methods are verified through comprehensive comparisons with the most prominent previously developed PWM methods in the literature. The generalization and implementation steps of the proposed LBPWM method are also provided.

This paper presents a new parameters estimation method for the single diode model and the double diode model of photovoltaic cells. A new application of the slime mould algorithm (SMA) stochastic optimization method represents one of the main contributions in this paper. The employment of the slime mould algorithm provides highly accurate and fast determination procedures of photovoltaic cells parameters. The slime mould algorithm stochastic optimization provides unique mathematical modelling of the optimization problem through using adaptive weights. These adaptive weights emulate the process of generating positive and negative feedbacks in the propagated wave of the slime mould. Moreover, the slime mould algorithm is successful at accurately extracting the global optimal values for the solar photovoltaic cell parameters. It has the ability to handle the non-linearity and multi-modal properties of the photovoltaic cell characteristics. The proposed method provides a generalized solution for precisely determining the parameters for various photovoltaic cells technologies. Comprehensive comparisons of the proposed slime mould algorithm with existing photovoltaic cell parameter extraction methods are performed in the paper. The results confirm the superior performance and accuracy of the proposed slime mould algorithm over the existing methods.