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The Distributed Maximum Power Point Tracking (DMPPT) approach is a promising solution to improve the energetic performance of mismatched PhotoVoltaic (PV) systems. However, there are still several factors that can reduce DMPPT energy efficiency, including atmospheric conditions, the efficiency of the power stage, constraints imposed by the topology...
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... without any loss of generality, we will refer to the second solution. A typical schematic representation of a grid-connected PV system with DMPPT is shown in Figure 1. The system, composed of a PV module with a dedicated DC/DC converter implementing the MPPT function, is indicated as PVU (PV unit). ...
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... the next phase, the whole system was assembled and a set of representative experiments was carried out. The experimental setup was realized in the Circuit Laboratory of the University of Naples Federico II and is shown in Figure 13. It is composed of three fundamental blocks: power, control, As highlighted in Figure 8, the core of the proposed PVU emulator is represented by an Arduino Mega 2560 microcontroller. ...
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... the next phase, the whole system was assembled and a set of representative experiments was carried out. The experimental setup was realized in the Circuit Laboratory of the University of Naples Federico II and is shown in Figure 13. It is composed of three fundamental blocks: power, control, and acquisition blocks. ...
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... block: During the acquisition process, the experimental data were stored and plotted in MATLAB through a commercial multichannel USB data acquisition system NI CompactDAQ, provided by National Instruments, with NI9215 modules characterized by 16-bit resolution and maximum sampling frequency of 100 kS/s). Figure 14a,b show a comparison between emulated I-V curves (shown in white) and theoretical curves (shown in black) in two cases. The two cases differ in the values assumed by S(t) and V dsmax . ...
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... order to fully exploit the potential of the proposed architecture, two Boost based PVU emulators were connected in parallel (series). The performance of this system is shown in Figures 15 and 16, in which the emulated I-V characteristics are shown together with the corresponding theoretical ones. The effectiveness of the obtained results highlights that the proposed emulator represents a useful tool to test the performance of shaded DMPPT PV systems. ...
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... order to fully exploit the potential of the proposed architecture, two Boost based PVU emulators were connected in parallel (series). The performance of this system is shown in Figures 15 and 16, in which the emulated I-V characteristics are shown together with the corresponding theoretical ones. The effectiveness of the obtained results highlights that the proposed emulator represents a useful tool to test the performance of shaded DMPPT PV systems. ...
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... order to fully exploit the potential of the proposed architecture, two Boost based PVU emulators were connected in parallel (series). The performance of this system is shown in Figures 15 and 16, in which the emulated I-V characteristics are shown together with the corresponding theoretical ones. The effectiveness of the obtained results highlights that the proposed emulator represents a useful tool to test the performance of shaded DMPPT PV systems. ...
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... vd is the small signal transfer function between the duty cycle and PV voltage. The expression of such a transfer function can be easily found by analyzing the small signal low-frequency equivalent circuit of a Boost based PVU and the load ( Figure A1). Energies 2020, 13, x FOR PEER REVIEW 15 of 17 Appendix A ...
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... µí°º is the small signal transfer function between the duty cycle and PV voltage. The expression of such a transfer function can be easily found by analyzing the small signal low-frequency equivalent circuit of a Boost based PVU and the load ( Figure A1). Hat symbols indicate small signal low-frequency variations [44] of the corresponding variables. ...
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... symbols indicate small signal low-frequency variations [44] of the corresponding variables. The resistance í µí± in Figure A1 is the differential resistance of the considered PV module [44]: Hat symbols indicate small signal low-frequency variations [44] of the corresponding variables. The resistance R MPP in Figure A1 is the differential resistance of the considered PV module [44]: ...
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... resistance í µí± in Figure A1 is the differential resistance of the considered PV module [44]: Hat symbols indicate small signal low-frequency variations [44] of the corresponding variables. The resistance R MPP in Figure A1 is the differential resistance of the considered PV module [44]: ...
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Citations
... In this context, Coppola et al. recently presented an MPPT distribution strategy, that is considered an alternative to the conventional approach for overcoming the shortcomings of MPPT regarding partial shading scenarios on the one hand and mitigating hot spot failure on the other hand. Thus, the DMPPT concept is achieved by including an MPPT optimizer along with a microinverter to extract the maximum power point for each PV unit independently (Balato et al., 2018;Balato et al., 2020). Nevertheless, the major drawback of such a configuration is the intensive use of sensors, particularly when the PV array size is large. ...
To date, several strategies have been developed to maximize photovoltaic (PV) energy production, notably the maximum power point tracking techniques (MPPTs). However, the performance of PV systems is limited owing to several factors, including partial shading (PS) and dust accumulation. In this regard, the current study proposes a practical procedure to effectively track the maximum power point (MPP) by applying multiple partial-shade scenarios to a (1 × 4) PV array to estimate the appropriate peak voltages, resulting in rapid MPP extraction. Furthermore, this assignment used the seven most well-known metaheuristic MPPT methodologies, including Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), Artificial Bee Colony (ABC), Horse Herd Optimization (HAO), Flying Squirrel Search Optimization (FSSO), and Salp Swarm Algorithm (SSA) to ensure robustness in terms of globality. Moreover, this investigation was accompanied by testing the methodologies on MATLAB® software and on the Raspberry Pi embedded board to guarantee real-world applicability. Finally, the authors highlight the suggested procedure’s advantages over other techniques on the one hand, and they encourage researchers to adopt the PSO, SSA, and GWO approaches as the most potent MPPT methodology on the other hand.
... However, no experimental tests have been described in that paper. The authors have also recently proposed a flexible DMPPT emulator able to reproduce the output (I-V) characteristics of a Boost-based [35] DMPPT system, not only at different irradiance levels but also as a function of the maximum voltage that can be applied across the drain and source terminals (V Dsmax ) of the adopted silicon devices under turn-off conditions. However, in the paper the emulator was adopted only to explore the performance of the Boost-based DMPPT approach. ...
... In the considered network topology, in order to identify the configuration that represents the best compromise between efficiency and reliability, it will also be considered a possibility to exclude one or several SCPVMs; in particular, each SCPVM may belong to one of the identified series or parallel clusters or be disconnected. The only constraint, called string voltage constraint, is to ensure that the Optimal String Voltage Range (OSVR), which depends not only on the considered atmospheric conditions, in terms of irradiance and temperature values, but also on the topology [35], must exhibit an intersection (no-zero intersection) with the Optimal Working Range of the Inverter (OWRI). This means that the following condition must be satisfied: ...
... Once the N series configuration clusters have been identified, and the Maximum Series Cluster Extractable Power (MSCEP i ) has been calculated for each of them, it is also necessary to evaluate the Optimal Series Cluster Voltage Range (OSCVR i ) and the Optimal Series Cluster Current Range (OSCIR i ), which are the optimal voltage (and current) range at which they have to operate in order to ensure optimal energetic performances. They can be calculated as [35] follows: ...
Mismatching operating conditions affect the energetic performance of PhotoVoltaic (PV) systems because they decrease their efficiency and reliability. The two different approaches used to overcome this problem are Distributed Maximum Power Point Tracking (DMPPT) architecture and reconfigurable PV array architecture. These techniques can be considered not only as alternatives but can be combined to reach better performance. To this aim, the present paper presents a new algorithm, based on the joint action of the DMPPT and reconfiguration approaches, applied to a reconfigurable Series-Parallel-Series architecture, which is suitable for domestic PV application. The core of the algorithm is a deterministic cluster analysis based on the shape of the current vs. voltage characteristic of a single PV module combined with its DC/DC converter to perform the DMPPT function. Experimental results are provided to validate the effectiveness of the proposed algorithm and to demonstrate evidence of its major advantages: robustness, simplicity of implementation and time-saving.
... Іншою бажаною характеристикою перетворювачів, застосовуваних в архітектурі DMPPT, є висока ефективність, однак один з основних недоліків -висока вартість через велику кількість використовуваних перетворювачів [8,9]. ...
One of the most important purpose of photovoltaic power plants is to obtain the maximum possible energy. The analysis of converters controlling only a part of the output power in photovoltaic systems was carried out. The architecture of distributed maximum power tracking is one of the most promising solutions to overcome the shortcomings associated with the reduction of the energy efficiency of photovoltaic panels. It was determined that in order to obtain greater flexibility regarding the number of photovoltaic panels in a photovoltaic circuit, a voltage converter is needed that can both increase and decrease the output voltage. The topology of the autotransformer DC converter for photovoltaic panels is given. The main component of the topology of the forward converter is the autotransformer. The principle of operation of the converter and the flow of current in the circuit during switching are presented. The power generated by photovoltaic panels was calculated depending on the state of their shading. Assuming that all PV panels generate maximum power regardless of the shading condition, the input voltage and power of the converter are established. The method of calculating the output power of the converter in the DMPPT architecture with a series connection, in which the circuit voltage is fixed by the central inverter, depends on the generated power of the photovoltaic panels connected to one circuit, is obtained. Regardless of the inverter topology, the higher the percentage of shaded PV panels, the less power can be produced. Increased converter efficiency means that more power can be produced in a solar power plant by using an autotransformer step-up converter. The main features of the proposed converter are high efficiency and the ability to both increase and decrease the output voltage relative to the input voltage.
... Differently from the Centralized approach of Figure 1, DMPPT uses a MPPT Module Dedicated DC/DC Converter realizing the MPPT for each PV module. Nevertheless, there are still several factors limiting such performance, including the efficiency of the power stage, constraints imposed by the topology, the finite rating of silicon devices, atmospheric conditions, and the suboptimal value of string voltage [39]- [43]. The fact that many of these factors are not under our control represents a severe restriction in conducting experimental test activities when real DMPPT PV systems are considered. ...
span lang="EN-GB">Distributed control strategyrepresents the most promising solution to enhance the lackluster energetic performance of mismatched PhotoVoltaic (PV) systems. Moreover, many factors that contribute to such poor performance are still to be explored. To fully understand the advantages offered by the Distributed Maximum Power Point Tracking (DMPPT) approach, the implementation of a DMPPT emulator is necessary. Based on the above needs, this paper describes the realization and use of a Buck based DMPPT emulator and shows its high flexibility and potential. The realized device is capable to emulate the output current vs. voltage (I-V) characteristics of many commercial PV modules with a dedicated Buck DC/DC converter not only in controlled atmospheric conditions but also with different currents rating of the switching devices. The system implementation is based on a commercial power supply controlled by a low-cost Arduino board. Data acquisition is performed through a low-cost current and voltage sensor by using a multichannel board by National Instruments. Experimental results confirm the validity and potential of the proposed DMPPT emulator.</span
