Design and Analysis of Digitally Controlled Algorithm-in-loop Newton-Raphson Method Based PV Emulator

Due to the Randomness and fluctuation of the photovoltaic (PV) system, Maximum Power Point Tracking (MPPT) algorithm is employed to ensure the maximum power extraction from PV arrays, when it is connected to the grid. The previous studies have indicated that the MPPT algorithm is one of the main causes of interharmonics emission in PV systems. The MPPT algorithm parameters such as perturbation step size inevitably have a strong impact on the interharmonics in the current injected to the grid. In general, a smaller MPPT perturbation step size will reduce the interharmonics emission level, but it will result in poor tracking performance of the MPPT algorithm. Thus, there is a trade-off between the MPPT efficiency and the interharmonics emission in PV system. In this paper, an interharmonics suppression scheme with variable step size MPPT algorithm was proposed. In the suppression scheme, two voltage values near by the MPPT voltage and two tracking step size are preset. When the dc-link voltage of PV is between the two preset voltage values, it means that the PV power near its MPP and the smaller perturbation step size implemented in the MPPT algorithm. Otherwise, the bigger perturbation step size is employed. It can greatly reduce interharmonics emission level and maintain the MPPT efficiency. Simulations have been carried out to verify the effectiveness of the suppression scheme.

Photovoltaic (PV) emulator (PVE) allows the development and testing of the PV equipment and system effectively. The PVE is an alternative to controllable light source that requires a large space and highly inefficient. The PVE requires a power converter and the buck converter is preferred due to the control simplicity and high efficiency. Nonetheless, the conventional design of the buck converter cannot be used since the output voltage of the PVE highly dependent on the output resistance. A proper design of the buck converter specified for the PVE application is needed to maintain continuous current mode operation and the output voltage ripple factor below the desired specification. This paper proposed the design for the passive components for the PVE using buck converter, which includes the output resistor, inductor, and capacitor. The single diode model is used to produce the current-resistance characteristic curves of the PV. The control strategy of the PVE is not included in this paper. The results show that the passive components for the buck converter obtained from the derivation able to maintain continuous current mode and has the output voltage ripple factor lower than the desired specification when operates as the PVE. This proves the derivation of the passive components is accurate.

By detection of input signal, Maximum Power Point Tracking (MPPT) algorithms are used to maximize the potential output power. Since Perturbation and Observe (P&O) method was first applied in a Photovoltaic (PV) system, a myriad of MPPT algorithms has been proposed. With the pros and cons of various MPPT algorithms, a detailed analysis of several typical direct search and module-integrated MPPT algorithms is presented in this paper. Directions of future work for implementing new MPPT algorithms are also outlined.

This work proposes an adaptative neuro-fuzzy inference system (ANFIS) method to model the behavior of solar photovoltaic (PV) module. The performance of the solar PV module is greatly influenced by various environmental factors and it is therefore necessary to operate the PV module at its optimal point ensuring that maximum power is extracted from the PV source. Several fixed step and variable step maximum power point tracking (MPPT) algorithms have been proposed in the literature. This paper presents a simple and fast MPPT method based on a structure that combines the agility of neuro-fuzzy system which a self-tuning and the precision of the perturb and observe (online method) (P&O), providing reduced oscillation, this way improving the power control efficiency.

<span>A Photovoltaic (PV) emulator is a device that produces a similar output as the PV module and it is useful for testing the PV generation system. This paper present a new and simple control strategy for the PV emulator using the combination of the Resistance Comparison Method with the Integral Controller. The closed-loop buck converter system with the current-mode controlled and the single diode model are used for the PV emulator. The results obtained from the proposed PV emulator are compared with the conventional PV emulator using the Direct Referencing Method as the control strategy. The proposed PV emulator produces a more accurate output, 74 % faster transient response, and a lower output voltage ripple compared to the conventional PV emulator.</span>

This paper presents an event-triggered approach to optimally implement a Maximum Power Point Tracking (MPPT) algorithm into a Digital Signal Processor (DSP). The proposed method allows improving the amount and distribution of time required for executing control tasks. The used nested loop control architecture has an outer loop of MPPT generating the conductance reference used by an inner loop which regulates the input conductance of a DC-DC converter. This last loop enforces a sliding-mode loss-free-resistor behavior for the power converter by means of a simple hysteresis comparator. Computations required by the MPPT algorithm are synchronously executed by the two possible commutation events produced by the inner loop during a switching period. Then, the acquisition of signals must be activated only at an instant before each one of the switching events, releasing the most of the time to implement other tasks. This last characteristic and the use of a nested loop control architecture facilitate the integration of the other essential control functions for photovoltaic (PV) generators in microgrids. Simulation and experimental results confirm the high potetialities of this implementation approach.

Nowadays, Photovoltaic (PV) energy sources are responsible for more than 720TWh of the global energy consumed. Therefore, among all the arising research topics regarding PV sources, Maximum Power Point tracking (MPPT) algorithms are widely studied, since they have critical importance in order to properly track and acquire the Maximum Power Point (MPP) of energy that can be harvested from the PV source; where, metaheuristic optimization algorithms have been adapted as MPPT solutions, showing an improved settling time with steady-state oscillations reduction. Yet, many of the Metaheuristic-based MPPTs have issues against dynamically variable MPP through time, since they cannot work properly without a reset signal upon temperature and irradiance parametric changes, due the fact that those algorithms converge on a global solution after some iterations and need to know when to start looking for the MPP again in order to avoid getting stuck in old MPP points. Hence, this work shows the implementation of Artificial Neural Networks (ANN) for pattern recognition through the power data acquisition, which enables an efficient solution that allows detecting changes in solar irradiation, which leads to a reliable reinitialization signal through the detection of solar irradiation through the ANN; where, results show over 99% of accuracy from the change in solar irradiation detection. Moreover, the ANN was trained using the metaheuristic Earthquake Algorithm (EA), which was again validated as a training method for ANN. In addition, this work enables other users to suite the EA algorithm to other applications and the implementation of ANN into the Simulink environments; both achievements, through the presentation and exploration of a complete MATLAB code example for the implementation of the EA as ANN training method, and the complete Simulink testbed design with a full description of the ANN implementation for the Simulink environment.KeywordsArtificial neural networksMetaheuristicsPhotovoltaic systems

Currently, Photovoltaic (PV) energy is the most important energy resource in electrical power applications around the world since it is inexhaustible, clean and pollution free. As the output power from the PV arrays changing with solar irradiance and temperature, so it is necessary to operate the photovoltaic (PV) system at the maximum power point (MPP) to increase the power extraction from the solar panel. For this effective operation and maximum power extraction from a PV system, Maximum power point tracking (MPPT) algorithm plays a vital role by operating the PV energy system near the MPP. In this work, amongst several existing well established MPPT algorithms, the open voltage (OV) based algorithm is chosen for simulation of a PV system using Matlab / Simscape. As maximum power point (MPP) can be attained with a certain amount of load from the PV power system, so load matching is an important concept of MPPT algorithms. Here, the performances of this open voltage (OV) based algorithm method is evaluated for different values of solar radiation and battery was used as load to see the charging performance for the algorithm.

Photovoltaic (PV) modules subject to partial shading (PS) or inhomogeneous irradiation drastically decrease the PV string power output. An algorithm composed of maximum voltage point tracking (MVPT) and maximum power point (MPP) tracking (MPPT) is presented to restore part of the power loss caused by PS. The MVPT can simultaneously drive the operating point of series PV modules toward their respective MPPs and guarantee power peak uniqueness. The MVPT is performed by means of a controllable current transformer (CCT) disposed at the terminal of each PV module permitting a compatible current in the series path of a PV string. The CCT output current can be regulated using a dependent current source according to the MPPT algorithm. An appropriate CCT current determined by the MPPT algorithm can avert undue CCT activation and consequently reduces the switching and copper losses of the converter circuit. Experimental results validate that the proposed strategy can balance the PV modules' output current subject to PS and facilitate convergence to the theoretical global MPP.

A comparative study between frequently used maximum power point tracking (MPPT) algorithms and a proposed Least Squares Support Vector Machine (LS-SVM) based MPPT algorithm under rapidly changing insolation condition (RCIC) is presented in this paper. The comparison shows that the proposed LS-SVM based MPPT algorithm offers some advantages over existing MPPT algorithms under RCIC, namely elimination of ripples in the output voltage of a PV solar system as well as improved tracking accuracy. The algorithms have been tested through simulation studies carried out on real data recorded by the Australia Bureau of Meteorology. The study compares the performances of LS-SVM, P&O and IncCond.

With increasing solar photovoltaic-based power generation, a photovoltaic emulator (PVE) is necessary to experimentally validate new control strategies without the influence of external factors such as irradiance and temperature. However, two significant challenges with PVEs are (i) solving the nonlinear equation of photovoltaic (PV) panel and (ii) oscillations in constant current (voltage) region with voltage (current) control. Thus, in this paper, a PVE with the ability to mimic both uniformly irradiated and partially shaded PV panels is proposed by employing artificial neural network (ANN) and piecewise-linearization technique. Based on the input operating conditions (irradiance, temperature, and partial shading), the ANN breaks the nonlinear I-V curve into piecewise-linear segments and outputs their boundary points. Then, with these boundary points, piecewise-linear equations of the segments relating PVE’s voltage and current are formed. Subsequently, using these piecewise-linear equations, the reference PVE voltage corresponding to PVE’s output current is calculated and given to the PI controller of a synchronous buck converter to mimic a PV panel. Thus, the proposed PVE overcomes the problem of solving nonlinear I-V equation by piecewise linearization which in turn aids an impedance-matching technique to mitigate the aforementioned oscillations. The generation of training data and development of ANN were carried out in MATLAB. Finally, the simulation studies performed in MATLAB/Simulink and hardware experiments validated the steady-state accuracy and the transient response which settled within 10 ms endorsing the real-time application of the proposed PVE.

Recently, many Maximum power point tracking (MPPT) techniques are proposed in the Photovoltaic (PV) systems. However, a comprehensive comparison of various MPPT techniques especially the dynamic tracking performance has not been made quantitatively for different working conditions. By reviewing different methods, the day-by-day operating evaluation method with practical meteorological data is used in this paper. Furthermore, three typical MPPT techniques including fixed step size P&O method, variable step size incremental conductance method, and hybrid step size Beta method, are selected in the performance evaluation. In order to improve the experimental repeatability and minimize the effect of random environmental factor such as partial shading, an indoor test system that consists of a DC-DC boost converter, a PV emulator and a dSPACE is used. The practical meteorological data are used for the evaluation these typical MPPT techniques and main experimental results are presented.

This Harnessing energy from the abundant and free sunlight is now a days a hot-topic among the research community. The availability of cheap solar modules has made it possible to harvest solar energy with better efficiency. The nature of solar modules is nonlinear and therefore the process of impedance matching is essential. The proper impedance matching ensures extraction of the maximum power from solar PV module. Several algorithms are reported in literatures that are used to operate the DC-DC converter around MPP. Maximum power point tracking (MPPT) algorithm acting an significant part in photovoltaic (PV) power generating system because it exploit the output power from a PV generating set for a various climatically conditions. This paper suggested a new modified work for MPPT of PV energy gathering system by using the optimized novel fuzzy logic controller (FLC). In the optimized FLC method, the membership functions tune automatically. In this paper MATLAB simulation effort shows with MPPT controller, a zero voltage and zero current dc to dc buck-boost Luo converter feeding a battery load is achieved. The results demonstrate that the suggested novel rule FLC MPPT in the photovoltaic generating system is valid.

In this paper, a high efficiency interleaved flyback (IFB) converter is proposed for photovoltaic (PV) electric power generation. An incremental conductance (INC) based maximum power point tracking (MPPT) algorithm is implemented for the proposed PV system to maximize the output power extracted from the PV array. Among the isolated converter topologies, flyback converter is selected for its simple configuration and low cost. It is also the most popular isolated converter used in low power, electronic applications. Interleaving technique is applied for the flyback converters in order to reduce the input current and output voltage ripples, and to increase the efficiency. A 100 W prototype is developed and tested. The simulation and experimental results obtained for different irradiations validate the effectiveness of proposed converter for the PV applications.

This paper presents a performance analysis of grid connected SPV system for different maximum power point tracking (MPPT) algorithms. The detailed mathematical model of grid connected three-phase solar photovoltaic (SPV) system with parametric model of SPV cell, thermal modelling and switching loss calculation of switching devices are discussed. The performance evaluation has been carried out for perturb-and-observe (P&O) and incremental conductance (IC)-based MPPT algorithms for various outputs of the SPV array, in terms of energy injected to grid, switching losses, junction temperature and sink temperature, for switching in the DC-DC boost converter. The results validated the effectiveness of the MPPT algorithm in increasing SPV output energy, decrease in the switching losses, junction and sink temperature. The results show that IC method is slightly better to P&O method in energy injected to the grid with lower switching losses, junction and sink temperature.