Power optimization for photovoltaic micro-converters using multivariable gradient-based extremum-seeking

Ghaffari, Azad; Seshagiri, Sridhar; Krstić, Miroslav

doi:10.1109/acc.2012.6314761

Cited by 23 publications

(27 citation statements)

References 19 publications

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“…For multivariable MPPT, the complexity of P&O algorithms increases dramatically with the size of the input vector. In contrast, ES trivially extends to multivariable MPPT, with only a few restrictions in selecting the probing frequencies [20]. Furthermore, with ES we have the option of employing the algorithm's Newton-based version to achieve transients that are symmetric relative to the peak of the MPP and uniform in speed for multiple modules [19].…”

Section: Introductionmentioning

confidence: 94%

“…Consequently, when applied to large PV arrays, the variability in environmental conditions and/or PV module degradation results in non-uniform transients in the convergence to the MPP. Using a multivariable gradient-based ES algorithm for the entire system instead of a scalar one for each PV module, while decreasing the sensitivity to the Hessian, does not eliminate this dependence [20]. We use the Newton-based ES algorithm that simultaneously employs estimates of the gradient and Hessian in the peak power tracking [19].…”

Section: Photovoltaic Systemsmentioning

confidence: 99%

“…As a model-free, real-time optimization approach, ES is well suited for systems with unknown dynamics or those that are affected by high levels of uncertainty or external dynamics, like WT and PV systems. Similar to P&O techniques, ES employs perturbations [9][10][11][12][13][14][15][16][17][18][19][20][21]. However, instead of employing a discrete step perturbation, ES uses a continuous oscillatory perturbation, also known as a "probing function."…”

Section: Introductionmentioning

confidence: 99%

“…ES has the dual benefit of rigorously provable convergence [9][10][11][12][13] and the simplicity of hardware implementation [14][15][16][17][18][19][20][21]. In addition to a probing signal, the ES algorithm employs only an integrator, as well as optional high-pass and low-pass filters.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Extremum seeking for wind and solar energy applications

Krstić

Ghaffari

Seshagiri

2014

Proceeding of the 11th World Congress on Intelligent Control and Automation

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Invented in 1922, extremum seeking (ES) is one of the oldest feedback methods. However, its purpose is not regulation but optimization. For this reason, applications of ES have often come from energy systems. The first noted publication on ES in the West is Draper and Li's application to spark timing optimization in internal combustion engines [1]. In the ensuing decades, ES has been applied to gas turbines and even nuclear fusion reactors. Renewable energy applications have brought a new focus on the capabilities of ES algorithms. In this article we present applications of ES in two types of energy conversion systems for renewable energy sources: wind and solar energy. In both areas the goal is maximum power point tracking (MPPT), i.e., the extraction of the maximum feasible energy from the system under uncertainty and in the absence of a priori modeling knowledge about the systems. For the wind energy conversion system (WECS) we perform MPPT by tuning the set point for the turbine speed using scalar ES. For the photovoltaic (PV) array system, we perform MPPT by tuning the duty cycles of the DC/DC converters employed in the system using multivariable ES. For the photovoltaic system we provide experimental results. (Abstract)

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Section: Introductionmentioning

confidence: 94%

Section: Photovoltaic Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Extremum seeking for wind and solar energy applications

Krstić

Ghaffari

Seshagiri

2014

Proceeding of the 11th World Congress on Intelligent Control and Automation

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“…The relation between voltage, current, and power supplied by the solar panel can be depicted in V-I curve (Voltage-Current) and V-P curve (Voltage-Power) which is a non-linier curve depending on irradiation and temperature. Both curves have a maximum peak which is often called as Maximum Power Point (MPP) [7]. The position of the MPP point is varied over time depending on the sun irradiation and temperature condition.…”

Section: Introductionmentioning

confidence: 99%

Solar Panel System for Street Light Using Maximum Power Point Tracking (MPPT) Technique

Wiedjaja

Harta

Josses

et al. 2014

EPJ Web of Conferences

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Abstract. Solar energy is one form of the renewable energy which is very abundant in regions close to the equator. One application of solar energy is for street light. This research focuses on using the maximum power point tracking technique (MPPT), particularly the perturb and observe (P&O) algorithm, to charge battery for street light system. The proposed charger circuit can achieve 20.73% higher power efficiency compared to that of non-MPPT charger. We also develop the LED driver circuit for the system which can achieve power efficiency up to 91.9% at a current of 1.06 A. The proposed street lightning system can be implemented with a relatively low cost for public areas.

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Global maximum power point tracking based on new extremum seeking control scheme

Bizon

2015

Progress in Photovoltaics

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A new perturbed-based extremum seeking control (PESC) scheme is proposed in this paper to track the global maximum power point (GMPP). The PESC scheme has two control loops based on power of the photovoltaic (PV) array: the first loop operates as usually to track the maximum power point and the second sweeps all local MPPs to locate the GMPP. Once the GMPP is located based on its uniqueness (after the PV pattern is quickly scanned many times, depending on the PV pattern's profile), the GMPP is accurately tracked based on first control loop. The used PV patterns have the profile of the PV power characteristics obtained for PV array under partially shaded conditions (PSCs). This PESC scheme is proposed to track the GMPP in the PV applications, but also in other multimodal problems from industry, being a good motif to revive the specialists' interest for the extremum seeking control field. The results obtained here are very promising for both search speed and tracking accuracy performances of the GMPP under different PSCs simulated on the PV array. Thus, the energy efficiency of PV array controlled with the proposed PESC scheme will increase with more than 1.2% in comparison with that obtained with the other MPP algorithms because of better performance shown by this PESC scheme. A 99.6% tracking accuracy is obtained here in comparison with a maximum 98.4% tracking accuracy reported in the literature. Furthermore, 100% hit and high search speed are obtained here for the GMPP localization.

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Power optimization for photovoltaic micro-converters using multivariable gradient-based extremum-seeking

Cited by 23 publications

References 19 publications

Extremum seeking for wind and solar energy applications

Extremum seeking for wind and solar energy applications

Solar Panel System for Street Light Using Maximum Power Point Tracking (MPPT) Technique

Global maximum power point tracking based on new extremum seeking control scheme

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