Adaptive Observer Based Control for Rooftop Solar PV System

Shah, Priyank; Singh, Bhim

doi:10.1109/tpel.2019.2898038

Cited by 28 publications

(20 citation statements)

References 40 publications

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“…Despite the overburdened grids in most of the countries, there is not much demand of solar energy systems even in developed countries. The three important reasons for this issue are: discontinuous availability of sun radiation in the cloudy days and night time, expensive cost, and lack of awareness of people about the potential solar energy [1]- [2]. There are two main methods for maximizing power.…”

Section: Introductionmentioning

confidence: 99%

Designing an Intelligent Maximum Power Point Tracking (MPPT) for a Rooftop Solar Array

Balali¹

2021

IJMTST

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By considering the limitation of the size of houses, the permanent inaccessibility of the solar radiation energy, and also the low efficiency of solar cells, a PV system requires the maximum power point tracking(MPPT). The main issue with using solar cells is to reach its maximum power, which is intensified by change in the temperature and radiation. In this paper, among MPPT methods, the Perturb and Observe (P&O) method, has been designed which has high reliability and traceability. However, due to the output power oscillation around the operating point in P&O method, an optimization fuzzy/bee algorithm is used for maximum power point tracking so that without the need for temperature and light sensors, reduction of output power oscillations can be achieved. Simulation results indicate that by using the fuzzy/ bee method, in addition to reducing the fluctuation around the operating point, the speed of reaching to the optimal point is maximized.

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Section: Introductionmentioning

confidence: 99%

Designing an Intelligent Maximum Power Point Tracking (MPPT) for a Rooftop Solar Array

Balali¹

2021

IJMTST

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“…[30] or lead to lots of parameter to tune e.g. [31], [32] (3 × n parameters to tune, where n is the number of harmonic components). All techniques mentioned so far use closed-loop technique to estimate the parameters.…”

Section: Introductionmentioning

confidence: 99%

Frequency Adaptive Parameter Estimation of Unbalanced and Distorted Power Grid

Ahmed

Benbouzid

Ahsan³

et al. 2020

IEEE Access

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Grid synchronization plays an important role in the grid integration of renewable energy sources. To achieve grid synchronization, accurate information of the grid voltage signal parameters are needed. Motivated by this important practical application, this paper proposes a state observer-based approach for the parameter estimation of unbalanced three-phase grid voltage signal. The proposed technique can extract the frequency of the distorted grid voltage signal and is able to quantify the grid unbalances. First, a dynamical model of the grid voltage signal is developed considering the disturbances. In the model, frequency of the grid is considered as a constant and/or slowly-varying but unknown quantity. Based on the developed dynamical model, a state observer is proposed. Then using Lyapunov function-based approach, a frequency adaptation law is proposed. The chosen frequency adaptation law guarantees the global convergence of the estimation error dynamics and as a consequence, ensures the global asymptotic convergence of the estimated parameters in the fundamental frequency case. Gain tuning of the proposed state observer is very simple and can be done using Matlab commands. Some guidelines are also provided in this regard. Matlab/Simulink based numerical simulation results and dSPACE 1104 board-based experimental results are provided. Test results demonstrate the superiority and effectiveness of the proposed approach over another state-of-the art technique.

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“…However, the procedure of calculating the Kalman gain vector in the LKF-FLL imposes a high computational burden, which limits its application. Some approaches to reduce the computational burden of the LKF-FLL can be found in [27,28].Observer-based method is another recent addition in the grid synchronisation [29][30][31]. In observer-based approach, using parameterised dynamical model, Luenberger observers are used to estimate the frequency of the grid voltage signal.…”

Section: Introductionmentioning

confidence: 99%

Synchronous reference frame single‐phase phase‐locked loop (PLL) algorithm based on half‐cycle DFT

Xia

Zhang

Tan

et al. 2020

IET Power Electronics

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In single-phase power and energy applications, sliding discrete Fourier transform (SDFT) filter based quadrature signal generation is a well-known tool for designing advanced phase-locked loops (PLLs), particularly for applications where high disturbance rejection ability is demanded. The SDFT-based PLL, nevertheless, has a limited ability in achieving fast response (a response time more than one cycle of the nominal frequency). To deal with this problem, a synchronous reference frame PLL based on half-cycle DFT (HCDFT) is proposed, enabling a fast and accurate synchronisation even in distorted grid. In this study, the fundamental voltage of the PLL input signal is obtained by a HCDFT filter. Then, phase, frequency and amplitude can be detected by the improved synchronous reference frame phase-locked loop (SRF-PLL). Besides, in order to solve the phase error when the frequency changes, a phase compensator is used. The HCDFT-based SRF-PLL method proposed in this study is compared, through experimental results, with a number of conventional methods, showing that the phase can be estimated under grid voltage disturbances accurately and quickly, which verifies the effectiveness and superiority of the proposed algorithm.

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Adaptive Observer Based Control for Rooftop Solar PV System

Cited by 28 publications

References 40 publications

Designing an Intelligent Maximum Power Point Tracking (MPPT) for a Rooftop Solar Array

Designing an Intelligent Maximum Power Point Tracking (MPPT) for a Rooftop Solar Array

Frequency Adaptive Parameter Estimation of Unbalanced and Distorted Power Grid

Synchronous reference frame single‐phase phase‐locked loop (PLL) algorithm based on half‐cycle DFT

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