Automatic Voltage Regulation of Grid Connected Photovoltaic System Using Lyapunov Based Sliding Mode Controller: A Finite — Time Approach

Xie, Mingyang; Gulzar, Muhammad Majid; Tehreem, Huma; Javed, Muhammad Yaqoob; Rizvi, Syed Tahir Hussain

doi:10.1007/s12555-019-0563-x

Cited by 31 publications

(15 citation statements)

References 33 publications

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“…Howlader et al [17] Frequency-watt and volt-watt control techniques Less power loss Error stability is high Xie et al [18] Grid-tied PV method Tracking efficiency is high High expensive…”

Section: Conflict Of Interestmentioning

confidence: 99%

Novel Hybrid Optimization Maximum Power Point Tracking and Normalized Intelligent Control Techniques for Smart Grid Linked Solar Photovoltaic System

2021

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Introduction of photovoltaic (PV) systems in grid causes some complex power quality problems such as harmonics, voltage fluctuation, and load imbalance that can affect the grid coordinated PV system performance. Therefore, herein, a novel normalized reasoning‐based fuzzy neural adaptive (NRFNA) control technique is proposed for the double‐stage grid coupled solar PV system. In addition, the utmost power in a double‐stage PV system is tracked at dissimilar environmental states by the proposed novel hybrid krill herd spider monkey (HKHSM)‐based maximum power point tracking (MPPT) algorithm. The current computation control method preserves the grid current in unity power factor as sinusoidal for the system at point common coupling (PCC). The simulation of this proposed work is done on MATLAB/Simulink. Subsequently, the performance of the developed replica results is validated under dissimilar conditions of power quality. Furthermore, the proposed HKHSM‐based MPPT along with a normalized reasoning herd spider monkey (NRHSM) control technique in a grid coordinated solar PV system has achieved 1.70% load current harmonics and 3.7% grid current harmonics. Consequently, the simulation outcomes are compared with the various conventional methods for proving the significance of the proposed system.

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“…Howlader et al [17] Frequency-watt and volt-watt control techniques Less power loss Error stability is high Xie et al [18] Grid-tied PV method Tracking efficiency is high High expensive…”

Section: Conflict Of Interestmentioning

confidence: 99%

Novel Hybrid Optimization Maximum Power Point Tracking and Normalized Intelligent Control Techniques for Smart Grid Linked Solar Photovoltaic System

2021

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“…However, the main drawback of this method is its expensive controlling unit. For efficient control of PV/Wind system, sliding mode controller (SMC) is established in References 17, 18, which overcomes the inherit characteristics of SMC such as high frequency chattering problem.…”

Section: Introductionmentioning

confidence: 99%

Multi control adaptive fractional orderPIDcontrol approach forPV/wind connected grid system

Sibtain

Murtaza

Ahmed

et al. 2021

Int Trans Electr Energ Syst

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Summary This paper introduces a novel genetic optimize multi‐control adaptive fractional order PID (AFOPID) for Photovoltaic (PV) and Wind connected grid system. The proposed AFOPID controller is optimized by a genetic algorithm (GA) to initialize the controller parameters. The renewable energy sources are mathematically modeled using multi control approach (MCA). In the proposed work, the MCA involves the maximum power point tracking (MPPT), dc link voltage, and current control and quadrature axis modeling. Furthermore, the current control functionalities are performed through an adaptive approach of AFOPID, where the controlling parameters are updated by measured error at every instant. The idea behind the research is to improve the tracking efficiency by introducing better control in order to gain maximum power from the source with minimized total harmonic distortion (THD). The proposed control scheme is tested using computer‐aided experimentation by varying the output of renewable energy sources, inverter uncertainty, and grid voltage variations. The results are benchmarked against the conventional fuzzy logic controllers, fractional‐order PID, and PI controllers. Moreover, to evaluate the effectiveness of the proposed controller, the MCA‐AFOPID is compared with ant colony optimization (ACO) and particle swarm optimization (PSO) optimized FOPID controller respectively. The proposed controller outperforms as compared to other controller.

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“…Due to the nonlinearity of the power and voltage of PV, maximum power point tracking (MPPT) is applied to maximize the efficiency under variable conditions. 2 The classical perturbation technique has been used extensively in literature with small step size to achieve lesser oscillation and high settling time and large step size to achieve higher oscillations with lesser time to track the MPP, respectively. This leads to a trade-off among tracking speed and oscillations around MPP.…”

Section: Introductionmentioning

confidence: 99%

“…Photovoltaic (PV) power systems efficiency, cost, and power benefit depends on the variation of climatic conditions and ambient temperature. Due to the nonlinearity of the power and voltage of PV, maximum power point tracking (MPPT) is applied to maximize the efficiency under variable conditions 2 …”

Section: Introductionmentioning

confidence: 99%

Variable step size fractional incremental conductance for MPPT under changing atmospheric conditions

Khan

Gulzar

Sibtain

et al. 2020

Int J Numerical Modelling

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This paper presents a new modified variable step size Fractional Order Incremental Conductance (FOIC) with maximum power point tracking using Fractional Order PID controller tuned by bio-inspired Particle Swarm Optimization (PSO) to find optimal gain values of fractional integrator order (λ) and fractional derivative order (μ). The classical incremental conductance and FOIC show drawbacks under changing irradiance, oscillation around maximum power point (MPP) which decreases its convergence speed. To resolve these prone a variable step size FOIC is proposed to achieve an adaptive duty cycle via tuning of FOPID through PSO. The robustness of the proposed technique is judged by its steady-state and dynamic response with fast converges, less response time, overshoot, and ripples under changing environmental conditions. Furthermore, the performance of the proposed technique is evaluated by comparing it with a fixed step size conventional incremental conductance algorithm and FOIC.

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Automatic Voltage Regulation of Grid Connected Photovoltaic System Using Lyapunov Based Sliding Mode Controller: A Finite — Time Approach

Cited by 31 publications

References 33 publications

Novel Hybrid Optimization Maximum Power Point Tracking and Normalized Intelligent Control Techniques for Smart Grid Linked Solar Photovoltaic System

Novel Hybrid Optimization Maximum Power Point Tracking and Normalized Intelligent Control Techniques for Smart Grid Linked Solar Photovoltaic System

Multi control adaptive fractional orderPIDcontrol approach forPV/wind connected grid system

Variable step size fractional incremental conductance for MPPT under changing atmospheric conditions

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