Modeling, control and analysis of cascaded inverter based grid-connected photovoltaic system

Kumar, Nayan; Saha, Tapas Kumar; Dey, Joykrishna

doi:10.1016/j.ijepes.2015.11.092

Cited by 36 publications

(21 citation statements)

References 22 publications

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“…4, unlike the proposed controllers in [9], [20], and [32], none of the voltage or current components need to be transformed to the "dqo" frame and all of the computations can be performed in "abc" coordinates. This reduces the computational burden in the proposed controller and increases the speed of the computation.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Some of these have focused on analyzing the CMI structure in terms of harmonic contents and voltage stress across the switches [14][15][16], and others have introduced new advanced controllers to compensate reactive power for grid tied PV systems [17][18][19][20], to compensate the unequal voltages of separate PV modules [21,22], for the voltage control of the floating dc capacitors [23,24] and to track the maximum power point (MPP) in PV based CMI systems [25][26][27].…”

Section: Single Phase MMC Structurementioning

confidence: 99%

“…1, the individual arms in each leg are the same, so |i pj |=|i nj |. By summing equations (15) and (16) and by simplifying, we can calculate d/dt(i cirj ) for each leg as follows: (17) (19) So we can rewrite (18) as follows: (20) …”

Section: Extracting Circuit Equationsmentioning

confidence: 99%

“…Based on the model predictive control (MPC) in [30] and [31], equation (20) can be rewritten as follows:…”

Section: Model Predictive Controlmentioning

confidence: 99%

“…Based on the model predictive control (MPC) in [30] and [31], equation (20) can be rewritten as follows: (21) where T S is the switching period (T S =1/f S ). According to equation (21), the instantaneous switching signal for each phase can be calculated as follows: (22) In (22), i cirj is the circulating current in each phase which is equal to: (23) Also, i cirj ref is the reference value of the circulating current which can be considered equal to 0.…”

Section: Model Predictive Controlmentioning

confidence: 99%

See 4 more Smart Citations

Novel Control of a Modular Multilevel Converter for Photovoltaic Applications

Shadlu¹

2017

Transactions on Electrical and Electronic Materials

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The number of applications of solar photovoltaic (PV) systems in power generation grids has increased in the last decade because of their ability to generate efficient and reliable power in a variety of low installation in domestic applications. Various PV converter topologies have therefore emerged, among which the modular multilevel converter (MMC) is very attractive due to its modularity and transformerless features. The modeling and control of the MMC has become an interesting issue due to the extremely large expansion of PV power plants at the residential scale and due to the power quality requirement of this application. This paper proposes a novel control method of MMC which is used to directly integrate the photovoltaic arrays with the power grid. Traditionally, a closed loop control has been used, although circulating current control and capacitors voltage balancing in each individual leg have remained unsolved problem. In this paper, the integration of model predictive control (MPC) and traditional closed loop control is proposed to control the MMC structure in a PV grid tied mode. Simulation results demonstrate the efficiency and effectiveness of the proposed control model.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Single Phase MMC Structurementioning

confidence: 99%

Section: Extracting Circuit Equationsmentioning

confidence: 99%

“…Based on the model predictive control (MPC) in [30] and [31], equation (20) can be rewritten as follows:…”

Section: Model Predictive Controlmentioning

confidence: 99%

Section: Model Predictive Controlmentioning

confidence: 99%

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Novel Control of a Modular Multilevel Converter for Photovoltaic Applications

Shadlu¹

2017

Transactions on Electrical and Electronic Materials

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A sliding mode control and artificial neural network based MPPT for a direct grid‐connected photovoltaic source

Touil

Boudjerda

Boubakir

et al. 2019

Asian Journal of Control

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A robust sliding mode controller for a grid-connected photovoltaic source is proposed in this paper. The objective of the presented control scheme is to force both the output voltage of the photovoltaic PV source and the power factor at the inverter output to follow a certain trajectory reference. The main idea is to apply the robust sliding mode controller directly to the nonlinear state model of the system composed of the PV source and the inverter with its input and output filters. In order to operate the PV system at the maximum power point and to satisfy the environmental factors, such as solar irradiance and temperature, we included a rigorous maximum power point tracker based on an artificial neural network. Simulation results are presented to illustrate the performance of the proposed control scheme. In addition, we show that the grid current satisfies the harmonic limits of the IEEE standard for interconnecting distributed energy sources with electric power systems. KEYWORDS artificial neural network, grid connection, harmonic distortion, maximum power point tracker, photovoltaic source, sliding mode control 1 | INTRODUCTIONRenewable energy sources are candidates for future electric energy due to their independence from fossil and nuclear fuels and given their low impact on the environment. Nowadays, photovoltaic (PV) sources contribute more and more in the generation of electric energy around the world. Photovoltaic power generation converts the sun's irradiation directly into electrical energy. To avoid the problems common in autonomous systems, such as costly and bulky batteries that require regular maintenance, it is necessary to operate the PV system in gridconnected mode; this allows injecting energy excess and covering for demand where production is not sufficient [1].Currently, grid-connected PV systems are the subject of many research works. The most important points of study are: the maximum power point tracking (MPPT) of solar arrays [2][3][4][5], the control of reactive energy injected in the network using suitable control techniques [2,4,5] and the reduction of harmonic pollution of the network by means of appropriate power electronic converters [4,5]. Commonly, grid connected PV sources use two cascaded power electronic converters: a DC-DC converter allows the control of the maximum power point (MPP) of the PV source and a DC-AC converter allows the control of the output voltage and the power factor as well as the reduction of the harmonic pollution of the output current [1,2,6].In [7], a basic proportional-integral (PI) controller is used to investigate the performance of a grid connected PV system by means of two cascaded DC-DC and DC-AC converters. The use of powerful control techniques ---

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Experimental investigation of Harris Hawk optimization‐based maximum power point tracking algorithm for photovoltaic system under partial shading conditions

Gali

Babu

Mutluri

et al. 2021

Optim Control Appl Methods

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An integrated quasi Z‐source DC–DC converter (qZSC) along with Harris Hawk Optimization (HHO)‐based maximum power point tracking (MPPT) algorithm is proposed in this paper to increase the efficiency of photovoltaic (PV) system. The qZSC‐based PV system experiences more voltage and current stress during partial shading conditions (PSCs), which causes overheat on qZSC components hence, degrade the efficiency and reliability of the system. Conventional swarm intelligence‐based MPPT algorithms track the GMPP during PSC, but these take longer convergence time and fail to settle at GMPP. This uncertainty of finding the GMPP leads to fluctuations at output of qZSC, hence more stress on the converter components. HHO in tracking the Gmpp eliminates premature local MPPs, enhances convergence speed by expanding the search space for finding the GMPP. The proposed system is developed in MATLAB/Simulink environment and verified the results by developing prototype model in the laboratory by using C2000™ Piccolo™ Launch Pad™, LAUNCHXL‐F28027 controller. The tracking performance of the proposed HHO‐based MPPT algorithm is tested under fast changing and PSCs in comparison with perturb & observe (P&O), particle swarm optimization (PSO), and artificial bee colony (ABC)‐based MPPT algorithms. The simulation and experimental results show that the proposed HHO‐based MPPT algorithm is robust, tracks maximum power point in minimum convergence time in comparison with P&O, PSO and ABC‐based MPPT algorithms. Hence, voltage and current fluctuations at the output of qZSC are reduced. Therefore, voltages and current stress on qZSC components are reduced and the efficiency of the system is improved.

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Modeling, control and analysis of cascaded inverter based grid-connected photovoltaic system

Cited by 36 publications

References 22 publications

Novel Control of a Modular Multilevel Converter for Photovoltaic Applications

Novel Control of a Modular Multilevel Converter for Photovoltaic Applications

A sliding mode control and artificial neural network based MPPT for a direct grid‐connected photovoltaic source

Experimental investigation of Harris Hawk optimization‐based maximum power point tracking algorithm for photovoltaic system under partial shading conditions

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