Control of Single-Phase Solar Photovoltaic Supply System

Pardhi, Pemendra Kumar; Sharma, Shailendra; Chandra, Ambrish

doi:10.1109/tia.2020.3024171

Cited by 20 publications

(6 citation statements)

References 30 publications

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“…The system consists of PV components, inverters, and loads (power grid), as shown in Figure 1. Usually multiple PV components are parallel-connected to be PV arrays (Mirhosseini et al, 2015;Zakzouk et al, 2017;Zhang and Ruan, 2019;Pardhi et al, 2020).…”

Section: Distributed Pv Power Generation Systems and Input String Typesmentioning

confidence: 99%

“…In the regular PV component array configuration process (Gonzalez et al, 2007;Abdalla et al, 2013;Mirhosseini et al, 2015;Sochor and Akagi, 2016;Zakzouk et al, 2017;Zhang and Ruan, 2019;Abe et al, 2020;Pardhi et al, 2020), when the connection mode in Figure 3A is adopted, if one panel is faulty or shaded, the power is affected, then reducing the benefits of power generation and reliability.…”

Section: Distributed Pv Power Generation Systems and Input String Typesmentioning

confidence: 99%

See 1 more Smart Citation

Research on Advanced Control Method of Multiple Photovoltaic Strings Input Type Recognition

Wang

Zhang

Zhang³

et al. 2022

Front. Energy Res.

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In order to decrease the performance effect of a single string in part of a photovoltaic (PV) array and increase the adaptive PV power generation, independent multiple series-connected PV strings are usually adopted in PV system projects to implement the input configuration. Besides, the conversion circuits with multipath inputs are required to be designed for the corresponding inverters to carry out the control algorithms. Since independent and parallel-connected modes exist for the PV string input in actual engineering projects, it is of great significance to effectively identify different PV inputs automatically for inverter inputs. In order to solve the problems of high hardware circuit requirements and complicated control algorithms in most of the existing control methods, a multiple PV string input type recognition method is proposed. Through the proposed software control algorithm, to realize automatically, accurately and quickly identify the external input connection type of the different photovoltaic strings under the external condition changes. The proposed method is free from increasing the inverter hardware cost, and it enhances the capability of identification and judgment. Moreover, experiments and engineering applications are implemented to verify the proposed control method.

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Section: Distributed Pv Power Generation Systems and Input String Typesmentioning

confidence: 99%

Section: Distributed Pv Power Generation Systems and Input String Typesmentioning

confidence: 99%

Research on Advanced Control Method of Multiple Photovoltaic Strings Input Type Recognition

Wang

Zhang

Zhang³

et al. 2022

Front. Energy Res.

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“…Upon designing the boost converter structure, the components' values should be selected properly. The boost converter inductor (L) is a function of VPV, d, fs, and lastly inductor ripple current ∆IL as follows [36]:…”

Section: B Control Structure Of Pv Energy Conversion Systemmentioning

confidence: 99%

Deep Learning-Aided Sensorless Control Approach for PV Converters in DC Nanogrids

2021

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In a microgrid, photovoltaic (PV) systems are broadly preferred with energy storage systems (ESSs) that form small-sized direct current (DC) microgrids. They are also termed local grids i.e., DC nanogrids, which feed the local consumers to some extent in the next decades. Therefore, ESSs enable the DC nanogrids more flexible and stable by preserving the intermittent nature of renewables. Yet still, feeding local consumers smoothly with PV-battery-based systems is exceedingly a considerable theme. In this context, proper control of power electronics converters as the main carrier of the system is essential. Besides, the rise of PV applications challenges possible issues upon integrating the conventional grid. Emerging possible issues and the ways of dealing with them have been developing day by day. Thus, it is inevitable that innovative methods will be put into practice. To achieve this goal, the deep learning aidedsensorless control approach is adopted. To validate the proposed control method, the training phase is presented elaborately with the help of the experimental setup of a DC nanogrid. From the obtained results, it is concluded that the deep learning-based approach reaches very small error values, captures the system dynamics with a high accuracy rate successfully, and allows the possibility to apply practically.INDEX TERMS Deep neural network (DNN), sensorless control, deep supervised learning, photovoltaics, power electronic converters, DC microgrid, DC nanogrid.

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“…The proposed control incorporates the grid connected and the islanded mode into a single control structure, and, with multiple functions, it is useful for helping in extracting maximum power from a PV system, injecting it to the grid, providing support to the grid, transferring to another mode smoothly, and maintaining load-following in islanded mode. As the PV power generation is susceptible to changes with environmental conditions [20,21], a battery is included to aid in smoothening the power output and for saving power when the local load is less than the local generation, providing power when local generation is less or not available. With the increased need of power quality enhancement [22], the smart PV control can be modified to include the function to work like a D-STATCOM.…”

Section: Introductionmentioning

confidence: 99%

Performance of Multifunctional Smart PV-Based Domestic Distributed Generator in Dual-Mode Operation

Chandrasekaran¹,

Sahayam²,

Thanasingh

et al. 2021

Machines

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This article briefs about a smart multifunctional single-phase inverter control for a domestic solar photo voltaic (PV)-based distributed generation that can work in both a grid-connected mode and an islanded mode by making the inverter mimic the operation of a synchronous generator. The control objectives were threefold: to provide the required active and reactive power for normal operating conditions and under varying operating conditions, to maintain the rated voltage and the rated frequency for the islanded mode, and to switch between the two modes of operation with the least amount of disturbance for the system while behaving as a virtual synchronous generator (VSG). The control structure is divided into three major loops: the outermost loop responsible for power control, the middle loop responsible for voltage control, and the innermost loop responsible for current control. The proposed control methodology incorporates the functionalities of the grid-connected and the islanded-mode control into a single complex structure and thus provides support to the grid under abnormal conditions while providing good-quality power to consumers under grid failure. The efficacy of the system is good. The operation under various modes were simulated in MATLAB Simulink, and the proportional integral (PI) controllers used for current controllers were tuned using particle swarm optimization (PSO). It can be concluded that the control structure becoming complex is benefitted by the added advantages of the smart PV system. The smart domestic PV system helps the prosumer to actively provide frequency support and voltage support, adding frequency support to the existing multifunctional PV systems.

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Control of Single-Phase Solar Photovoltaic Supply System

Cited by 20 publications

References 30 publications

Research on Advanced Control Method of Multiple Photovoltaic Strings Input Type Recognition

Research on Advanced Control Method of Multiple Photovoltaic Strings Input Type Recognition

Deep Learning-Aided Sensorless Control Approach for PV Converters in DC Nanogrids

Performance of Multifunctional Smart PV-Based Domestic Distributed Generator in Dual-Mode Operation

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