The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform

A. Garrigos - One of the best experts on this subject based on the ideXlab platform.

  • in site real time photovoltaic i v curves and maximum power Point Estimator
    IEEE Transactions on Power Electronics, 2013
    Co-Authors: J.m. Blanes, Sergio Montero, F J Toledo, A. Garrigos
    Abstract:

    This paper presents a practical implementation of a photovoltaic I-V curves and maximum power Point estimation algorithm (IVMPPE). The IVMPPE estimates the I-V curve and sets the operation of the solar panels at a voltage that extracts the maximum available power without tracking. The operation is based on solving the parameters of the solar array equivalent electrical model, in real time, only with the measurements of six voltage and current coordinates near the operating Point. Moreover, the strategy for selecting the measured Points and the discard procedures for incorrect estimated curves are also detailed. To validate the IVMPPE, it has been tested under different operating conditions, and its accuracy has been compared with the classical perturb and observe (P&O) technique. The distinguishing feature of the IVMPPE is that complete I-V model is obtained, not only the MPP, enlarging the capabilities to other fields, e.g., real-time monitoring and prediction.

  • In-Site Real-Time Photovoltaic I–V Curves and Maximum Power Point Estimator
    IEEE Transactions on Power Electronics, 2013
    Co-Authors: J.m. Blanes, Javier F. Toledo, Sergio Montero, A. Garrigos
    Abstract:

    This paper presents a practical implementation of a photovoltaic I-V curves and maximum power Point estimation algorithm (IVMPPE). The IVMPPE estimates the I-V curve and sets the operation of the solar panels at a voltage that extracts the maximum available power without tracking. The operation is based on solving the parameters of the solar array equivalent electrical model, in real time, only with the measurements of six voltage and current coordinates near the operating Point. Moreover, the strategy for selecting the measured Points and the discard procedures for incorrect estimated curves are also detailed. To validate the IVMPPE, it has been tested under different operating conditions, and its accuracy has been compared with the classical perturb and observe (P&O) technique. The distinguishing feature of the IVMPPE is that complete I-V model is obtained, not only the MPP, enlarging the capabilities to other fields, e.g., real-time monitoring and prediction.

  • Maximum power Point Estimator for photovoltaic solar arrays
    MELECON 2006 - 2006 IEEE Mediterranean Electrotechnical Conference, 2006
    Co-Authors: J.m. Blanes, A. Garrigos, J.a. Carrasco, E. Avila, E. Maset
    Abstract:

    A novel maximum power Point Estimator (MPPE) for photovoltaic solar arrays is proposed, evaluated and implemented. Unlike maximum power Point trackers (MPPT), the MPPE extracts the solar array maximum power with no tracking process. The operation is based on solving the solar array electronic equivalent model by a microcontroller in real time. Only four measured voltage and current coordinates are needed to obtain the actual solar array parameters and set its operation at maximum power in any conditions of illumination and temperature. Simulated and experimental results are presented to validate the concept

J.m. Blanes - One of the best experts on this subject based on the ideXlab platform.

  • in site real time photovoltaic i v curves and maximum power Point Estimator
    IEEE Transactions on Power Electronics, 2013
    Co-Authors: J.m. Blanes, Sergio Montero, F J Toledo, A. Garrigos
    Abstract:

    This paper presents a practical implementation of a photovoltaic I-V curves and maximum power Point estimation algorithm (IVMPPE). The IVMPPE estimates the I-V curve and sets the operation of the solar panels at a voltage that extracts the maximum available power without tracking. The operation is based on solving the parameters of the solar array equivalent electrical model, in real time, only with the measurements of six voltage and current coordinates near the operating Point. Moreover, the strategy for selecting the measured Points and the discard procedures for incorrect estimated curves are also detailed. To validate the IVMPPE, it has been tested under different operating conditions, and its accuracy has been compared with the classical perturb and observe (P&O) technique. The distinguishing feature of the IVMPPE is that complete I-V model is obtained, not only the MPP, enlarging the capabilities to other fields, e.g., real-time monitoring and prediction.

  • In-Site Real-Time Photovoltaic I–V Curves and Maximum Power Point Estimator
    IEEE Transactions on Power Electronics, 2013
    Co-Authors: J.m. Blanes, Javier F. Toledo, Sergio Montero, A. Garrigos
    Abstract:

    This paper presents a practical implementation of a photovoltaic I-V curves and maximum power Point estimation algorithm (IVMPPE). The IVMPPE estimates the I-V curve and sets the operation of the solar panels at a voltage that extracts the maximum available power without tracking. The operation is based on solving the parameters of the solar array equivalent electrical model, in real time, only with the measurements of six voltage and current coordinates near the operating Point. Moreover, the strategy for selecting the measured Points and the discard procedures for incorrect estimated curves are also detailed. To validate the IVMPPE, it has been tested under different operating conditions, and its accuracy has been compared with the classical perturb and observe (P&O) technique. The distinguishing feature of the IVMPPE is that complete I-V model is obtained, not only the MPP, enlarging the capabilities to other fields, e.g., real-time monitoring and prediction.

  • Maximum power Point Estimator for photovoltaic solar arrays
    MELECON 2006 - 2006 IEEE Mediterranean Electrotechnical Conference, 2006
    Co-Authors: J.m. Blanes, A. Garrigos, J.a. Carrasco, E. Avila, E. Maset
    Abstract:

    A novel maximum power Point Estimator (MPPE) for photovoltaic solar arrays is proposed, evaluated and implemented. Unlike maximum power Point trackers (MPPT), the MPPE extracts the solar array maximum power with no tracking process. The operation is based on solving the solar array electronic equivalent model by a microcontroller in real time. Only four measured voltage and current coordinates are needed to obtain the actual solar array parameters and set its operation at maximum power in any conditions of illumination and temperature. Simulated and experimental results are presented to validate the concept

Hubert Preissl - One of the best experts on this subject based on the ideXlab platform.

  • detection of uterine mmg contractions using a multiple change Point Estimator and the k means cluster algorithm
    IEEE Transactions on Biomedical Engineering, 2008
    Co-Authors: P S La Rosa, Arye Nehorai, Hari Eswaran, Curtis L Lowery, Hubert Preissl
    Abstract:

    We propose a single channel two-stage time-segment discriminator of uterine magnetomyogram (MMG) contractions during pregnancy. We assume that the preprocessed signals are piecewise stationary having distribution in a common family with a fixed number of parameters. Therefore, at the first stage, we propose a model-based segmentation procedure, which detects multiple change-Points in the parameters of a piecewise constant time-varying autoregressive model using a robust formulation of the Schwarz information criterion (SIC) and a binary search approach. In particular, we propose a test statistic that depends on the SIC, derive its asymptotic distribution, and obtain closed-form optimal detection thresholds in the sense of the Neyman-Pearson criterion; therefore, we control the probability of false alarm and maximize the probability of change-Point detection in each stage of the binary search algorithm. We compute and evaluate the relative energy variation [root mean squares (RMS)] and the dominant frequency component [first order zero crossing (FOZC)] in discriminating between time segments with and without contractions. The former consistently detects a time segment with contractions. Thus, at the second stage, we apply a nonsupervised K-means cluster algorithm to classify the detected time segments using the RMS values. We apply our detection algorithm to real MMG records obtained from ten patients admitted to the hospital for contractions with gestational ages between 31 and 40 weeks. We evaluate the performance of our detection algorithm in computing the detection and false alarm rate, respectively, using as a reference the patients' feedback. We also analyze the fusion of the decision signals from all the sensors as in the parallel distributed detection approach.

  • detection of uterine mmg contractions using a multiple change Point Estimator and k means cluster algorithm
    International Congress Series, 2007
    Co-Authors: P S La Rosa, Arye Nehorai, Hari Eswaran, Curtis L Lowery, Hubert Preissl
    Abstract:

    Abstract We propose a single-channel two-stage detector of uterine magnetomyogram (MMG) contractions during pregnancy. In the first stage, we assume that the measurements are modeled by a zero-mean Gaussian random variable with time-varying piecewise constant variance. Therefore, we apply a model-based segmentation procedure which detects multiple change Points in the variance values using the Schwarz information criterion (SIC) and a binary search approach. Then, in the second stage, we apply the K -means cluster algorithm to classify each time segment using the root-mean square (RMS) as a feature. We apply our algorithm to real MMG records obtained from five patients having contractions with gestational ages between 31 and 40 weeks.

Sergio Montero - One of the best experts on this subject based on the ideXlab platform.

  • in site real time photovoltaic i v curves and maximum power Point Estimator
    IEEE Transactions on Power Electronics, 2013
    Co-Authors: J.m. Blanes, Sergio Montero, F J Toledo, A. Garrigos
    Abstract:

    This paper presents a practical implementation of a photovoltaic I-V curves and maximum power Point estimation algorithm (IVMPPE). The IVMPPE estimates the I-V curve and sets the operation of the solar panels at a voltage that extracts the maximum available power without tracking. The operation is based on solving the parameters of the solar array equivalent electrical model, in real time, only with the measurements of six voltage and current coordinates near the operating Point. Moreover, the strategy for selecting the measured Points and the discard procedures for incorrect estimated curves are also detailed. To validate the IVMPPE, it has been tested under different operating conditions, and its accuracy has been compared with the classical perturb and observe (P&O) technique. The distinguishing feature of the IVMPPE is that complete I-V model is obtained, not only the MPP, enlarging the capabilities to other fields, e.g., real-time monitoring and prediction.

  • In-Site Real-Time Photovoltaic I–V Curves and Maximum Power Point Estimator
    IEEE Transactions on Power Electronics, 2013
    Co-Authors: J.m. Blanes, Javier F. Toledo, Sergio Montero, A. Garrigos
    Abstract:

    This paper presents a practical implementation of a photovoltaic I-V curves and maximum power Point estimation algorithm (IVMPPE). The IVMPPE estimates the I-V curve and sets the operation of the solar panels at a voltage that extracts the maximum available power without tracking. The operation is based on solving the parameters of the solar array equivalent electrical model, in real time, only with the measurements of six voltage and current coordinates near the operating Point. Moreover, the strategy for selecting the measured Points and the discard procedures for incorrect estimated curves are also detailed. To validate the IVMPPE, it has been tested under different operating conditions, and its accuracy has been compared with the classical perturb and observe (P&O) technique. The distinguishing feature of the IVMPPE is that complete I-V model is obtained, not only the MPP, enlarging the capabilities to other fields, e.g., real-time monitoring and prediction.

Majid Khedmati - One of the best experts on this subject based on the ideXlab platform.

  • Identifying the time of a step change in AR(1) auto-correlated simple linear profiles
    Journal of Industrial Engineering International, 2015
    Co-Authors: Majid Khedmati, Seyed Taghi Akhavan Niaki
    Abstract:

    Assuming a first-order auto-regressive model for the auto-correlation structure between observations, in this paper, a transformation method is first employed to eliminate the effect of auto-correlation. Then, a maximum likelihood Estimator (MLE) of a step change in the parameters of the transformed model is derived and three separate EWMA control charts are used to monitor the parameters of the profile. The performance of the proposed change-Point Estimator is next compared to the one of the built-in change-Point Estimator of EWMA control chart through some simulation experiments. The results show that the proposed MLE of the change Point accurately estimates the true change Point and outperforms the built-in Estimator of EWMA chart for almost all shift values and auto-correlation coefficients, while the built-in Estimator of EWMA chart, in general, underestimates the true change Point.

  • monotonic change Point estimation of multivariate poisson processes using a multi attribute control chart and mle
    International Journal of Production Research, 2014
    Co-Authors: Seyed Taghi Akhavan Niaki, Majid Khedmati
    Abstract:

    In this paper, a new multi-attribute control chart is initially proposed to monitor multi-attribute processes based on a transformation technique. Then, the maximum likelihood Estimator of a multivariate Poisson process change Point is derived for unknown changes that are assumed to belong to a family of monotonic changes. Using extensive simulation experiments, the performance of the proposed change-Point Estimator is compared to the ones derived for step changes and linear-trend disturbances, when the true change types are step change, linear trends and multiple-step changes. We show when the type of the change is not known a priori, the proposed Estimator is an appropriate choice, since it accurately estimates the true time of the process changes, regardless of change type, shift magnitudes and process dimension.

  • change Point estimation of high yield processes with a linear trend disturbance
    The International Journal of Advanced Manufacturing Technology, 2013
    Co-Authors: Seyed Taghi Akhavan Niaki, Majid Khedmati
    Abstract:

    In this paper, the maximum likelihood Estimator (MLE) of the change Point in a high-yield process when a linear trend disturbance occurs in the proportion nonconformity of the process is first derived. Then, the performances of the proposed change Point Estimator in terms of both accuracy and precision are compared to the MLE of the change Point designed for step changes. The results of the comparison analysis that is performed using Monte Carlo simulation experiments show that not only the average estimates of the change Point Estimator designed for linear trends are closer to the real change Point, but also its mean square error is smaller than the one of the Estimator designed for step changes for almost all shifts. In addition, better precisions are obtained by the proposed Estimator than the ones obtained by the Estimator designed for step changes. In short, in the presence of a linear trend disturbance, the MLE of the change Point designed for linear trend disturbances outperforms the MLE of the change Point designed for step changes.

  • Identifying the change time of multivariate binomial processes for step changes and drifts
    Journal of Industrial Engineering International, 2013
    Co-Authors: Seyed Taghi Akhavan Niaki, Majid Khedmati
    Abstract:

    In this paper, a new control chart to monitor multi-binomial processes is first proposed based on a transformation method. Then, the maximum likelihood Estimators of change Points designed for both step changes and lineartrend disturbances are derived. At the end, the performances of the proposed change-Point Estimators are evaluated and are compared using some Monte Carlo simulation experiments, considering that the real change type presented in a process are of either a step change or a linear-trend disturbance. According to the results obtained, the change-Point Estimator designed for step changes outperforms the change-Point Estimator designed for linear-trend disturbances, when the real change type is a step change. In contrast, the change-Point Estimator designed for linear-trend disturbances outperforms the change-Point Estimator designed for step changes, when the real change type is a linear-trend disturbance.