Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method

Lin, Chia Hung; Huang, Cong; Du, Yi; Chen, Jian Liung

doi:10.1016/j.apenergy.2011.06.024

Cited by 159 publications

(80 citation statements)

References 17 publications

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“…In Taiwan's subtropical outdoor environment, the average solar radiation and temperature are approximately 0.20 -0.80 kW/m 2 and 30 -40°C, respectively, during the summer season. For various radiation and temperature values, the MPPT algorithm [1][2][3][18][19] can be employed to control the DC-DC boost converter until the desired MOP and output voltage is reached. In this study, an ICM based method [1,3] is used to estimate the desired output and adjust the boost converter's duty ratio to match the maximum point.…”

Section: Resultsmentioning

confidence: 99%

“…For various radiation and temperature values, the MPPT algorithm [1][2][3][18][19] can be employed to control the DC-DC boost converter until the desired MOP and output voltage is reached. In this study, an ICM based method [1,3] is used to estimate the desired output and adjust the boost converter's duty ratio to match the maximum point. The MPPT is used to track the MOP by adjusting the voltage as solar radiation and temperature increase from 0.2 kW/m 2 to 1.0 kW/m 2 and from 30°C to 45°C, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…A MPPT algorithm, such as the incremental conductance method (ICM) [1][2] or ICM based method [3], is used . .…”

Section: Maximum Output Power Estimation and Fault Feature Extractionmentioning

confidence: 99%

“…PV energy conversion systems use a solar tracking system with maximum power point tracking (MPPT) methods to improve output performance and battery charge solutions [1][2][3]. There are different sized PV systems, ranging from small, rooftop, or building-integrated systems with capacities > 10 kilowatts to those with capacities of > 100's of megawatts in concentrated solar, heating/ cooling systems, and home power supplies.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multiple Fault Location in a Photovoltaic Array Using Bidirectional Hetero-Associative Memory Network in Micro-distribution Systems

Chang¹,

Pai²,

Chou³

et al. 2018

Preprint

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Abstract:In manual maintenance inspections of large-scaled photovoltaic (PV) or rooftop PV systems, several days are required to survey the entire PV field. To improve reliability and shorten the amount of time involved, this study proposes an electrical examination based method for locating multiple faults in the PV array. The maximum power point tracking (MPPT) algorithm is used to estimate the maximum power of each PV panel; this is then compared with metering the output power of PV array. Power degradation indexes are parameterized to quantify the degradation between maximum power and metered output power. Bidirectional hetero-associative memory (BHAM) networks are then used to locate multiple faults within the entire PV field. For a rooftop PV system with two strings, experimental results demonstrate that the proposed model has computational efficiency for real-time applications and that its algorithm is easily implemented in a mobile intelligent vehicle.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…A MPPT algorithm, such as the incremental conductance method (ICM) [1][2] or ICM based method [3], is used . .…”

Section: Maximum Output Power Estimation and Fault Feature Extractionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multiple Fault Location in a Photovoltaic Array Using Bidirectional Hetero-Associative Memory Network in Micro-distribution Systems

Chang¹,

Pai²,

Chou³

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Such non-linear and non-minimum phase characteristics further confuse the MPPT of the boost converter [5]. To overcome these problems, different conventional and intelligent MPPT algorithms have been proposed such as Incremental Conductance (IC) [6][7][8], Open Circuit Voltage (OCV) [9], Short Circuit Current (SCC) [10], Perturb and Observe (P&O) [11], fuzzy logic [12][13][14][15], feedback linearization [16], neural network [17][18][19][20][21][22], neuro-fuzzy [23][24][25] and sliding mode [26,27]. Nevertheless, there still remains the concern of fast and accurately determining the locus of the MPP during high weather variations and external load changes occurring.…”

Section: Introductionmentioning

confidence: 99%

Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems

Hassan

Kamal

et al. 2017

Energies

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An intelligent control of photovoltaics is necessary to ensure fast response and high efficiency under different weather conditions. This is often arduous to accomplish using traditional linear controllers, as photovoltaic systems are nonlinear and contain several uncertainties. Based on the analysis of the existing literature of Maximum Power Point Tracking (MPPT) techniques, a high performance neuro-fuzzy indirect wavelet-based adaptive MPPT control is developed in this work. The proposed controller combines the reasoning capability of fuzzy logic, the learning capability of neural networks and the localization properties of wavelets. In the proposed system, the Hermite Wavelet-embedded Neural Fuzzy (HWNF)-based gradient estimator is adopted to estimate the gradient term and makes the controller indirect. The performance of the proposed controller is compared with different conventional and intelligent MPPT control techniques. MATLAB results show the superiority over other existing techniques in terms of fast response, power quality and efficiency.

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Control of Grid Connected Photovoltaic Systems with Microinverters: New Theoretical Design and Numerical Evaluation

Yahya

Fadil

Oulcaid

et al. 2017

Asian Journal of Control

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This paper addresses the problem of controlling grid connected photovoltaic (PV) systems that are driven with microinverters. The systems to be controlled consist of a solar panel, a boost dc–dc converter, a DC link capacitor, a single‐phase full‐bridge inverter, a filter inductor, and an isolation transformer. We seek controllers that are able to simultaneously achieve four control objectives, namely: (i) asymptotic stability of the closed loop control system; (ii) maximum power point tracking (MPPT) of the PV module; (iii) tight regulation of the DC bus voltage; and (iv) unity power factor (PF) in the grid. To achieve these objectives, a new multiloop nonlinear controller is designed using the backstepping design technique. A key feature of the control design is that it relies on an averaged nonlinear system model accounting, on the one hand, for the nonlinear dynamics of the underlying boost converter and inverter and, on the other, for the nonlinear characteristic of the PV panel. To achieve the MPPT objective, a power optimizer is designed that computes online the optimal PV panel voltage used as a reference signal by the PV voltage regulator. It is formally shown that the proposed controller meets all the objectives. This theoretical result is confirmed by numerical simulation tests.

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Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method

Cited by 159 publications

References 17 publications

Multiple Fault Location in a Photovoltaic Array Using Bidirectional Hetero-Associative Memory Network in Micro-distribution Systems

Multiple Fault Location in a Photovoltaic Array Using Bidirectional Hetero-Associative Memory Network in Micro-distribution Systems

Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems

Control of Grid Connected Photovoltaic Systems with Microinverters: New Theoretical Design and Numerical Evaluation

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