This paper presents a new maximum power point tracking (MPPT) method based on the measurement of temperature and short-circuit current, in a simple and efficient approach. These measurements, which can precisely define the maximum power point (MPP), have not been used together in other existing techniques. The temperature is measured with a low cost sensor and the solar irradiance is estimated through the relationship of the measured short-circuit current and its reference. Fast tracking speed and stable steady-state operation are advantages of this technique, which presents higher performance when compared to other well-known techniques.
Maximum power point tracking (MPPT) is essential in off-grid and grid-tied photovoltaic (PV) applications to extract the maximum available power. This study presents a new MPPT technique named irradiance and temperature (I&T) method. This technique uses the estimation of irradiance and measurement of temperature to define the MPP. It is based on the observation of irradiance effects in PV module current and temperature dependency of PV module voltage. The irradiance will be evaluated through the measurement of short-circuit current. In addition, temperature reading is employed to determine its effects in temperature-dependent variables, thus providing higher efficiency to the I&T method. Good stability in steady state and fast tracking speed, in different conditions of irradiance and temperature, are important features of this technique. Experimental tests compared the performance of the I&T method with conventional and parameter-based methods. The performed tests highlight the effectiveness of the proposed method at uniform and dynamic weather conditions. V PV PV output voltage V T thermal voltage V T,ref thermal voltage at T ref V temp temperature gradient ΔI ref reference current variation
A method for electrocardiogram (ECG) feature extraction is presented for automatic classification of heartbeats, using values of RR intervals, amplitude and Hjorth parameters. Hjorth parameters have been used in a variety of research areas, but their application to ECG signal processing is still little explored. This paper also introduces a new approach to heartbeat segmentation, which avoids mixing information from adjacent beats and improves classification performance. The proposed model is validated in the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia database and presents an overall accuracy of 90.4%, better than other state-of-the-art methods. There is an improvement over other models in positive predictivity for class S (66.6%) of supraventricular ectopic beats, and sensitivity for class N (93.0%). Results obtained indicate that the techniques used in this study can be successfully applied to the problem of automatic heartbeat classification. In addition, this new approach has low computational cost, which allows its later implementation in hardware devices with limited resources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.