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This research proposes a method for detecting subtle faults named snail trails for their visual similarity with the trail of a snail in photovoltaic modules. Snail trails do not significantly reduce panel performance but they are the main cause of serious panel deterioration such as microcracks and delamination and can go so far as to set the panel on fire. To detect these faults, this research uses an ensemble learning framework, named ensemble learning for diagnosis, which combines several complementary learning algorithms, namely Support Vector Machines, K-Nearest Neighbors, and Decision Trees. A set of features is obtained by extracting the time–frequency characteristics and statistics from the photovoltaic current signal of the photovoltaic panel. This is followed by a feature selection and dimensionality reduction step that delivers the input to the learning algorithms. The approach presented in this study is experimentally validated, independently for the 4 seasons of the year, with data from a real photovoltaic string of 16 panels. The results demonstrate that the proposed approach can efficiently classify healthy panels and panels with snail trails efficiently. Interestingly, the method only requires the electrical current signal, measured on panels with data acquisition systems that are standard in the photovoltaic industry. The genericity of the approach makes it a good candidate for detecting other photovoltaic faults and for solving diagnosis problems in other domains. [Display omitted] • This approach provides a learning framework that is efficient with little data. • It is easily embeddable approach in commercial monitoring devices of PV systems. • It has high performance under low irradiation conditions. • It gains efficiency by organizing the learning step into temporal slices that capture characteristic variations. [ABSTRACT FROM AUTHOR]

To track the inductor current in high-frequency dc/dc converters is not effortless, particularly when high output currents and low output voltages are demanded by the load. This paper proposes a simple technique to obtain a good accuracy in the inductor current measurement in voltage regulator module (VRM) applications. The main idea is to obtain an equivalent volt- age image which can be used for the high-frequency pulsewidth modulation controller to generate the converter control law. This strategy of measurement is generic, and it has been previously validated by simulations. Afterward, some experimental results are obtained by using several prototypes of dc/dc converters delivering a very low output voltage and owning several loads from 10-mA to 100-A currents. This wide range covers the power requirements of portable and embedded VRM applications. Moreover, this sense technique has also been validated in a digital high-frequency current-mode-controlled dc/dc converter. [ABSTRACT FROM AUTHOR]

In this paper, the problem of paralleling dc-dc switching converters is solved by means of power gyrators. The key element of the parallel connection is a buck converter with input filter acting as a power gyrator of type G with controlled output current, i.e., with its dc output current being proportional to its dc input voltage, electromagnetic interference minimization, current distribution among converters, stability, and voltage regulation are ensured by this approach. It is shown that a voltage regulator based on the parallel operation of power gyrators with democratic current sharing is always stable regardless of the number of connected modules. Experimental results of a dc-dc voltage regulator based on the parallel connection of three power gyrators with democratic current sharing are in perfect agreement with the theoretical predictions. [ABSTRACT FROM AUTHOR]

Basic configurations employed in the design of power architectures can be efficiently implemented by means of power gyrators. A modular architecture for a dc bus based on the connection of N g-gyrators and one r-gyrator is proposed to perform source splitting and achieve voltage regulation. Source splitting can pro. vide high power, and it is implemented by paralleling the N output ports of the g-gyrators whose corresponding input ports are ex- cited by independent voltage sources. Output voltage regulation is provided by the r-gyrator stage, which is connected in cascade with the source splitting configuration. Experimental results in an 80-W prototype are in good agreement with the theoretical predictions. [ABSTRACT FROM AUTHOR]

This paper presents the analysis and design of a min-type strategy to control a synchronous boost converter in continuous conduction mode. The strategy uses a nonlinear switching surface to establish the change of topology in the converter and is analyzed by means of a sliding-mode control approach. Subsequently, the min-type strategy is modified by a hybrid control formulation, which introduces a hysteresis width and a dwell-time to obtain a finite switching frequency in the start-up and steady-state, respectively. The hybrid control formulation is implemented digitally by means of a microprocessor which processes the samples of inductor current and capacitor voltage to provide the control signal that activates the power switch. Experimental results in a prototype validate the proposed control strategy and show its potential in transient time and steady-state. [ABSTRACT FROM AUTHOR]

Ground-source heat pumps are more energy-efficient, especially when compared to their water and air source counterparts. However, when operating and design conditions are vastly different, the expected gains in efficiency could be easily negated. Under such scenarios, measures to improve energy performance are explored through performing mathematical optimization on the appropriate model of the system. Components of a heat pump system are often operated at pre-defined setpoints or independently optimized, disregarding the overall performance. Formulation of a holistic optimization problem which expresses the system in its tuneable variables, while capturing the tight-coupling between its components results in a complex mixed-integer non-linear program. Our paper concerns itself with the mathematical modeling and optimization of the hourly operation of a ground-coupled heat pump system for improving energy and operating cost. We judiciously abstracted and decoupled the component models of the system, so that the problem could be formulated as a mixed-integer linear program. This vastly benefited the solvability of the optimization problem. For illustration, we implemented this methodology on a system in the ADREAM building of the LAAS-CNRS laboratory in Toulouse, France. Four case studies are defined in the lead up to holistic optimization, allowing the results to be easily understood. The results reveal significant limitations, which prompted the hybridization of the system with a hypothetical water-to-air heat exchanger. Results indicated electricity and cost savings of up to 35.0% and 12.7% respectively, depending on the objective function. Our findings postulate that the additional investment is recoverable within five years. • Adapted framework for the holistic optimization of the hourly operation of ground-sourced heat pump systems. • Optimization of hybrid ground source heat pump systems considering changes in ground temperatures and energy storage systems. • Component models calibrated with raw data. • Application of system-level optimization on a case study for illustration purposes. • Discussion of solutions which suggest electricity and cost savings of up to 35% and 12.7% respectively. [ABSTRACT FROM AUTHOR]

Diagnosis aims at predicting the health status of components and systems. In photovoltaic systems, it is vital to guarantee energy production and extend the useful life of photovoltaic power plants. Multiple prediction and classification algorithms have been proposed for this purpose in the literature. The accuracy of these algorithms depends directly on the quality of the data and the features with which they are tuned or trained. In this paper, an innovative approach for predicting the health status of photovoltaic systems is proposed, which includes a feature selection stage. This approach first discriminates severely affected photovoltaic panels using basic electrical features. In a second step, it discriminates the other faulty panels using more elaborated time–frequency features and selecting the most relevant features through correlation and variance analysis. Finally, the approach predicts the health status of photovoltaic panels using a nonlinear regression method named partial least squares. This later is then combined with linear discriminant analysis and compared. The approach is validated with real current data from a photovoltaic plant composed of twelve photovoltaic panels with power between 205 and 240 Wp in three health states, namely broken glass, healthy, and big snail trails. The results obtained show that the proposed approach efficiently predicts the three health states. It determines the level of degradation of the panels, which indicates priorities to corrective and predictive maintenance actions. Furthermore, it is cost-effective since it uses only electrical measurements that are already available in standard photovoltaic data acquisition systems. Above all, the approach is generic and it can be easily extrapolated to other diagnosis problems in other domains. [ABSTRACT FROM AUTHOR]

A new digital robust control law for dc-dc converters is analyzed and implemented in this paper. The robust control QFT technique, which has been successfully used with analog implementations, has been adapted to the digital domain. Concretely, this paper considers the design of a power conditioning unit, which must take into account the uncertainty of the converter, as the conduction mode, the load, the input voltage or the storage elements while assuring that the specifications of a well-known standard are met. The robust control has been implemented by means of a digital device. The sampling frequency is a critical parameter for this kind of system which exhibits fast dynamics. The paper shows a procedure to analyze the minimum sampling frequency of the regulation loop. The procedure consists of transforming an standard analog QFT design to a digital controller by means of an accurate transformation from the s to z domain. After this transformation, we assure the robust stability of the converter by means of the Kharitonov theorem. This approach allows the designer to avoid iterations while finding an appropriate sampling frequency. The experimental prototype has been implemented by means of a FPGA device where the sampling frequency is 100 kHz for a buck power stage with a switching frequency of 200 kHz. The experimental results that are in good agreement with theoretical derivations. [ABSTRACT FROM AUTHOR]

The integration of passive components on silicon for future dc–dc converter applications is still a challenging area of research. This paper reports the microfabrication of a fully integrated filter containing a spiral inductor on top of a 3-D capacitor. A thin magnetic shielding layer is introduced between the two components demonstrating that losses caused by the inductor in the capacitor area are reduced, thus increasing the maximum working frequency of the whole component. The fabricated filter was characterized in a test circuit (buck-type converter). [ABSTRACT FROM AUTHOR]

Fourth-order converters with both input and output filters are analyzed in self-oscillating sliding mode. The boost converter with output filter and the Cuk converter are shown to have stable dynamics and an equilibrium point with transformer characteristics. The analytical predictions are verified by experimental results. [ABSTRACT FROM AUTHOR]

This paper presents the study of a simplified approach to model and analyze the performance of partially shaded photovoltaic modules using the shading ratio. This approach integrates the characteristics of shaded area and shadow opacity into the photovoltaic cell model. The studied methodology is intended to improve the description of shaded photovoltaic systems by specifying an experimental procedure to quantify the shadow impact. Furthermore, with the help of image processing, the analysis of the shading ratio provides a set of rules useful for predicting the current–voltage behavior and the maximum power points of shaded photovoltaic modules. This correlation of the shading ratio and shading patterns can contribute to the supervision of actual photovoltaic installations. The experimental results validate the proposed approach in monocrystalline and polycrystalline technologies of solar panels. [ABSTRACT FROM AUTHOR]