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To generate electricity, solar photovoltaic (PV) systems are among the best, most eco-friendly and most cost-effective solutions available. Extraction of maximum possible electricity from the solar PV system is complicated by a number of factors brought on by the ever-changing weather conditions under which it must operate. Many conventional and evolutionary algorithm-based maximum power point tracking (MPPT) techniques have the limitation of not being able to extract maximum power under partial shade and rapidly varying irradiance. Hence, the purpose of this paper is to propose a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid bridge link-honey comb (BL-HC) configured PV system to enhance the better maximum power during dynamic and steady state operations within less time.

In this method, a hybridization of two algorithms is proposed to track the true with faster convergence under PSCs. Initially, the slime mould optimization (SMO) algorithm is initiated for exploration of optimum duty cycles and later P&O algorithm is initiated for exploitation of global duty cycle for the DC–DC converter to operate at GMPP and for fast convergence.

The effectiveness of the proposed HSMO MPPT is compared with adaptive coefficient particle swarm optimization (ACPSO), flower pollination algorithm and SMO MPPT techniques in terms of tracked GMPP, convergence time/tracking speed and efficacy under six complex partial shading conditions. From the results, it is noticed that the proposed algorithm tracks the true GMPP under most of the shading conditions with less tracking time when compared to other MPPT techniques.

This paper proposes a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid BL-HC configured PV system enhance the better maximum power under partial shading conditions (PSCs). This method operated in two stages as SMO for exploration and P&O for exploitation for faster convergence and to track true GMPP under PSCs. The proposed approach largely improves the performance of the MPP tracking of the PV systems. Initially, the proposed MPPT technique is simulated in MATLAB/Simulink environment. Furthermore, an experimental setup has been designed and implemented. Simulation results obtained are validated through experimental results which prove the viability of the proposed technique for an efficient green energy solution.

The solar photovoltaic (PV) system is one of the outstanding, clean and green energy options available for electrical power generation. The varying meteorological operating conditions impose various challenges in extracting maximum available power from the solar PV system. The drawbacks of conventional and evolutionary algorithms-based maximum power point tracking (MPPT) approaches are its inability to extract maximum power during partial shading conditions and quickly changing irradiations. Hence, the purpose of this paper is to propose a modified elephant herding optimization (MEHO) based MPPT approach to track global maximum power point (GMPP) proficiently during dynamic and steady state operations within less time.

A MEHO-based MPPT approach is proposed in this paper by incorporating Gaussian mutation (GM) in the original elephant herding optimization (EHO) to enhance the optimizing capability of determining the optimal value of DC–DC converter’s duty cycle (D) to operate at GMPP.

The effectiveness of the proposed system is compared with EHO based MPPT, Firefly Algorithm (FA) MPPT and particle swarm optimization (PSO) MPPT during uniform irradiation condition (UIC) and partial shading situation (PSS) using simulation results. An experimental setup has been designed and implemented. Simulation results obtained are validated through experimental results which prove the viability of the proposed technique for an efficient green energy solution.

With the proposed MEHO MPPT, it has been noted that the settling period is lowered by 3.1 times in comparison of FA MPPT, 1.86 times when compared to PSO based MPPT and 1.29 times when compared to EHO based MPPT with augmented efficiency of 99.27%.

The purpose of this paper is to propose a novel maximum power point track (MPPT) controller for a type of solar quad-copter to solve the problem of tracking the maximum power point (MPP) when it works in nonuniform environment conditions.

The influence of uniform and nonuniform illumination and different temperatures results in the output characteristics of the solar array arising multiple local MPPs. To track the global MPP of the solar array on the designed solar quadcopter, a type of MPPT controller based on an improved pigeon-inspired optimization (PIO) algorithm is proposed.

A novel type of MPPT controller based on extended search PIO (ESPIO) algorithm, called ESPIO–MPPT controller, is introduced emphatically, which is used to extend the solar quadcopter’s flight time. The simulation experiments show that the ESPIO–MPPT controller can find the global MPP (GMPP) with smaller amplitudes of oscillation and less time cost.

The proposed solar quadcopter with ESPIO–MPPT controller has satisfactory flight performance which can greatly broaden its mission scope.

A type of efficient MPPT algorithm based on ESPIO is proposed for GMPP tracking of solar quadcopters in nonuniform environment conditions.

Increased investment of a photovoltaic (PV) array makes it essential for the client to attain better results from the PV system. The nonlinearity of the PV array and the revolution and rotation of the earth require the appliance of maximum power point tracking (MPPT) to the system. Accordingly, grid connected PV systems have turn out to be renowned, because they do not require battery back-ups to accomplish MPPT. Stand-alone systems could also attain MPPT; however, they require appropriate battery back-ups for this function.

This survey intends to formulate a review on the PV-based microgrid (MG) systems. Here, the literature analyses on diverse techniques associated with PV-based MG systems. It reviews 65 research papers and states the significant analysis. Initially, the analysis depicts various controllers that are contributed in different papers. Subsequently, the analysis also focuses on various features such as PV capacity and inverter topology, and it also analyses the renewable grid source that are exploited in each paper. Furthermore, this paper provides the detailed study regarding the chronological review and performance achievements in each contribution. Finally, it extends the various research issues which can be useful for the researchers to accomplish further research on PV-based MG systems.

This paper has presented a detailed review on PV-based MG systems that were enumerated in the above sections. Here, various controllers along with their better achievements were analyzed and described. From the review, it was known that several PV-based MG systems were really at the point for enabling better power output and conversion efficiency. In conclusion, this paper reviewed about 65 research papers and declared the significant analysis. Initially, the analysis also focused on various controller classifications in PV-based MG systems that were reviewed in this paper. Subsequently, the analysis also focused on various features, such as PV capacity and inverter topology. The analysis also reviewed the performance achievements and renewable gird source that were exploited in PV-based MG systems. At last, this paper has presented various research issues which can be useful for the researchers to accomplish further research on the features of PV-based MG systems.

This paper presents a brief analysis of PV-based MG systems. This is the first work that uses PV-based MG systems for better regulation of MPPT.

Silicon photovoltaics technology has drawbacks of high cost and power conversion efficiency. In order to extract the maximum output power of the module, maximum power point (MPP) is used by implying the nonlinear behavior of I-V characteristics. Different techniques are used regarding maximum power point tracking (MPPT). The paper aims to review the techniques of MPPT used in PV systems and review the comparison between Perturb and Observe (P&O) method and incremental conductance (IC) method that are used to track the maximum power and gives a comparative review of all those techniques.

A study of MPPT techniques for photovoltaic (PV) systems is presented. Matlab Simulink is used to find the MPP using P&O simulation along with IC simulation at a steady temperature and irradiance.

MATLAB simulations are used to implement the P&O method and IC method, which includes a PV cell connected to an MPPT-controlled boost converter. The simulation results demonstrate the accuracy of the PV model as well as the functional value of the algorithms, which has improved tracking efficiency and dynamic characteristics. P&O solution gave 94% performance when configured. P&O controller has a better time response process. As compared to the P&O method of tracking, the incremental conductance response rate was significantly slower.

In PV systems, MPPT techniques are used to optimize the PV array output power by continuously tracking the MPP under a variety of operating conditions, including cell temperature and irradiation level.

Renewable energy sources such as solar photovoltaic (PV) and wind are ubiquitous because of their lower environmental impact. Output from solar PV and wind turbines is unstable; hence, this article aims to propose an effective controller to extract maximum available power.

By focusing on the varying nature of solar irradiance and wind speed, the paper presents the maximum power point tracking (MPPT) technique for renewable energy sources, and power regulation is made by the novel inverter design. Moreover, a DC–DC boost converter is adopted with solar PV, and a doubly fed induction generator is connected with the wind turbine. The proposed MPPT technique is used with the help of a rain optimization algorithm (ROA) based on bi-directional long short-term memory (Bi-LSTM) (ROA_Bi-LSTM). In addition, the sinusoidal pulse width modulation inverter is used for DC–AC power conversion.

The proposed MPPT technique has jointly tracked the maximum power from solar PV and wind under varying climatic conditions. The power flow to the transmission line is stabilized to protect the load devices from unregulated frequency and voltage deviations. The power to the smart grid is regulated by three-level sinusoidal pulse width modulation inverter.

The methodology and concept of the paper are taken by the author on their own. They have not taken a duplicate copy of any other research article.

In most maximum power point tracking (MPPT) methods described in the literature, the optimal operating point of the PV systems is estimated by linear approximations. These approximations can reduce considerably the performances of the PV systems. This paper seeks to provide comparative analyses of different MPPT methods used in photovoltaic (PV) systems and proposes a new approach that uses a nonlinear expression of the optimal voltage in combination with perturbation and observation (P&O) methods.

First, an analytical model for determining the nonlinear PV optimal operating point is detailed and each equation is explained. Second, a combination of the new method with P&O method is proposed to reduce the PV losses.

The simulation results showed that the approach improves clearly the tracking efficiency of the maximum power available at the PV modules output. The implementation of this new method will improve PV systems energy production rate and its long‐term storage in hydrogen form.

The simulation results showed that the new approach improves the MPP's tracking efficiency of the PV system on average at 92 percent. The implementation of the developed approach in a PV system with hydrogen storage increased the energy transfer from PV modules to the electrolyzer.

This paper proposes a new approach to determine the maximum power point (MPP) from the measurement of the open circuit voltage of PV modules. A nonlinear expression of the optimal voltage was developed and is used in combination with P&O methods. The proposed approach largely improves the performance of the MPP tracking of the PV systems.

Photovoltaic (PV) systems are experiencing exponential growth due to environmental concerns, unlimited and ubiquitous solar energy, and starting-to-make-sense panel costs. Alongside designing more efficient solar panels, installing solar trackers and special circuitry for optimizing power delivery to the load according to a maximum power point tracking (MPPT) algorithm are other ways of increasing efficiency. However, it is critical for any efficiency increase to account for the power consumption of any amendments. Therefore, this paper aims to propose a novel tracker while using MPPT to boost the PV system's actual efficiency accounting for the involved costs.

The proposition is an experimental pneumatic dual-axis solar tracker using light-dependent resistor (LDR) sensors. Due to its embedded energy storage, the pneumatic tracker offers a low duty-cycle operation leading to tracking energy conservation, fewer maintenance needs and scalability potential. While MPPT assures maximum load power delivery, the solar PV's actual delivered power is calculated for the first time, accounting for the solar tracking and MPPT power costs.

The experiments' results show an increase of 37.6% in total and 35.3% in actual power production for the proposed solar tracking system compared to the fixed panel system, with an MPPT efficiency of 90%. Thus, the pneumatic tracking system offers low tracking-energy consumption and good actual power efficiency. Also, the newly proposed pneumatic stimulant can significantly simplify the tracking mechanism and benefit from several advantages that come along with it.

To the best of the authors’ knowledge, this work proposes, for the first time, a single-motor pneumatic dual-axis tracker with less implementation cost, less frequent operation switching and scalability potential, to be developed in future works. Also, the pneumatic proposal delivers high actual power efficiency for the first time to be addressed.

The purpose of this paper is to focus on two major areas of concern for the Photovoltaic (PV) system, i.e. power quality and maximum power point tracking (MPPT). Novel control strategies have been proposed for both these issues, and their respective superiorities over the existing techniques have been established. On the other hand, as far as MPPT is concerned, two limitations are found in the available techniques. One is the inability of effective MPPT in dynamic conditions where the environmental parameters changes very rapidly. Second one is the ineffective tracking of global maxima under partial shading conditions.

Here, modified Kalman filtering approach has been applied for estimating the reference current of active power filter, incorporated for power quality improvement. The proposed Kalman algorithm introduces a weighted matrix, which advances the estimated values of state variables. This paper presents a simple and enhanced model-based (MB) MPPT algorithm that has the capability of tracking MPPT effectively in both these working conditions. The proposed MB algorithm uses the mathematical modelling, and based on precised estimation of parameters, it pre-determines the MPP analytically.

It has been tested successfully for dynamic variations of insolation, temperature and partial shading, where all these three parameters are rigorously varied over the full scale of practical values. The results have been also investigated experimentally and compared with the simulated one. A close matching of both the results has been shown through the plots, which validates the effectiveness of proposed algorithms.

This research paper is part of the original research work carried out in Lab. Simulated results are obtained in MATLAB/Simulink platform, whereas these are further validated experimentally on 2-KW panel constituted with all types of commercial products, namely, mono, poly and thin-film.

The aviation industry has started environment friendly and also conventional energy independent alternative energy dependent designs to reduce negative impacts on the nature and to maintain its future activities in a clear, renewable and sustainable way. One possible solution proposed is solar energy. Solar-powered aerial vehicles are seen as key solutions to reduce global warming effects. This study aims to simulate a mathematical model of a solar powered DC motor of an UAV on MATLAB/Simulink environment.

Maximum power point tracking (MPPT) is a critical term in photovoltaic (PV) array systems to provide the maximum power output to the related systems under certain conditions. In this paper, one of the popular MPPT techniques, “Incremental Conductance”, is simulated with solar-powered DC motor for an UAV design on MATLAB/Simulink.

The cascade structure (PV cell, MPPT, buck converter and DC motor models) is simulated and tested under various irradiance values, and results are compared to the DC motor technical data. As a result of that, mathematical model simulation results are overlapped with motor technical reference values in spite of irradiance changes.

It is suggested to be used in real time applications for future developments.

Different from other solar-powered DC motor literature works, a solar-powered DC motor mathematical model of an UAV is designed and simulated on MATLAB/Simulink environment. To adjust the maximum power output at the solar cell, incremental conductance MPPT technique is preferred and a buck converter structure is connected between MPPT and DC motor mathematical model. It is suggested to be used in solar-powered UAV designs for future developments.