Statistical analysis of the performance and simulation of a two-axis tracking PV system

The energy produced by a photovoltaic system over a given period can be estimated from the incident radiation at the site where the Grid Connected PV System (GCPVS) is located, assuming knowledge of certain basic features of the system under study. Due to the inherently stochastic nature of solar radiation, the question “How much energy will a GCPVS produce at this location over the next few years?” involves an exercise of prediction inevitably subjected to a degree of uncertainty. Moreover, during the life cycle of the GCPVS, another question arises: “Is the system working correctly?”. This paper proposes and examines several methods to cope with these questions. The daily performance of a PV system is simulated. This simulation and the interannual variability of both radiation and productivity are statistically analyzed. From the results several regression adjustments are obtained. This analysis is shown to be useful both for productivity prediction and performance checking exercises. Finally, a statistical analysis of the performance of a GCPVS is carried out as a detection method of malfunctioning parts of the system

solaR: Solar Radiation and Photovoltaic Systems with R

The solaR package allows for reproducible research both for photovoltaics (PV) systems performance and solar radiation. It includes a set of classes, methods and functions to calculate the sun geometry and the solar radiation incident on a photovoltaic generator and to simulate the performance of several applications of the photovoltaic energy. This package performs the whole calculation procedure from both daily and intradaily global horizontal irradiation to the final productivity of grid-connected PV systems and water pumping PV systems. It is designed using a set of S4 classes whose core is a group of slots with multivariate time series. The classes share a variety of methods to access the information and several visualization methods. In addition, the package provides a tool for the visual statistical analysis of the performance of a large PV plant composed of several systems. Although solaR is primarily designed for time series associated to a location defined by its latitude/longitude values and the temperature and irradiation conditions, it can be easily combined with spatial packages for space-time analysis

Resolving inconsistencies in utility measurement under risk: Tests of generalizations of expected utility

This paper explores biases in the elicitation of utilities under risk and the contribution that generalizations of expected utility can make to the resolution of these biases. We used five methods to measure utilities under risk and found clear violations of expected utility. Of the theories studies, prospect theory was most consistent with our data. The main improvement of prospect theory over expected utility was in comparisons between a riskless and a risky prospect(riskless-risk methods). We observed no improvement over expected utility in comparisons between two risky prospects (risk-risk methods). An explanation why we found no improvement of prospect theory over expected utility in risk-risk methods may be that there was less overweighting of small probabilities in our study than has commonly been observed.Utility Measurement, Nonexpected Utility, Prospect Theory, Health., Leex

Analysis and synthesis of the variability of irradiance and PV power time series with the wavelet transform

The irradiance fluctuations and the subsequent variability of the power output of a PV system are analysed with some mathematical tools based on the wavelet transform. It can be shown that the irradiance and power time series are nonstationary process whose behaviour resembles that of a long memory process. Besides, the long memory spectral exponent α is a useful indicator of the fluctuation level of a irradiance time series. On the other side, a time series of global irradiance on the horizontal plane can be simulated by means of the wavestrapping technique on the clearness index and the fluctuation behaviour of this simulated time series correctly resembles the original series. Moreover, a time series of global irradiance on the inclined plane can be simulated with the wavestrapping procedure applied over a signal previously detrended by a partial reconstruction with a wavelet multiresolution analysis, and, once again, the fluctuation behaviour of this simulated time series is correct. This procedure is a suitable tool for the simulation of irradiance incident over a group of distant PV plants. Finally, a wavelet variance analysis and the long memory spectral exponent show that a PV plant behaves as a low-pass filter

Optimización de una planta de producción

[CASTELLÀ] El proyecto consiste en la optimización del proceso de producción en la empresa HITECSA, localizada en Vilanova i la Gelrú y que desarrolla su actividad en la manufactura de equipos de aire acondicionado de mediano y gran tamaño. Para ello, se comenzará analizando el proceso productivo de manera general en toda la empresa y se tomarán y analizarán los tiempos de trabajo del proceso de ensamblaje para posteriormente identificar las desigualdades entre las cargas de trabajo de los operarios. Una vez halladas estas desigualdades, se tratará de eliminarlas mediante la implementación de una nueva célula de ensamblaje de subconjuntos y mediante la subcontratación de una parte del proceso productivo a una empresa externa. Por otra parte, se implementará la metodología de las 5S de manera total o parcial en distintas células de trabajo con tal de mejorar el entorno del operario, de mejorar su productividad y consecuentemente disminuir el tiempo de entrega del producto.[ANGLÈS] The project consists in the optimization of the production process in the company HITECSA, located in Vilanova i la Gelrú and that develops its activity in the manufacture of air conditioning equipment of medium and large size. To this end, the production process will be analysed in a general way throughout the company and the working times of the assembly process will be taken and analysed in order to subsequently identify the inequalities between the workloads of the operators. Once these inequalities have been found, an attempt will be made to eliminate them by implementing a new cell for the assembly of subassemblies and by subcontracting part of the production process to an external company. On the other hand, the 5S methodology will be implemented in a total or partial way in different work cells in order to improve the environment of the operator, to improve his productivity and consequently to reduce the delivery time of the product

Data-Driven ECG Denoising Techniques for Characterising Bipolar Lead Sets along the Left Arm in Wearable Long-Term Heart Rhythm Monitoring

Abnormal heart rhythms (arrhythmias) are a major cause of cardiovascular disease and death in Europe. Sudden cardiac death accounts for 50% of cardiac mortality in developed countries; ventricular tachycardia or ventricular fibrillation is the most common underlying arrhythmia. In the ambulatory population, atrial fibrillation is the most common arrhythmia and is associated with an increased risk of stroke and heart failure, particularly in an aging population. Early detection of arrhythmias allows appropriate intervention, reducing disability and death. However, in the early stages of disease arrhythmias may be transient, lasting only a few seconds, and are thus difficult to detect. This work addresses the problem of extracting the far-field heart electrogram signal from noise components, as recorded in bipolar leads along the left arm, using a data driven ECG (electrocardiogram) denoising algorithm based on ensemble empirical mode decomposition (EEMD) methods to enable continuous non-invasive monitoring of heart rhythm for long periods of time using a wrist or arm wearable device with advanced biopotential sensors. Performance assessment against a control denoising method of signal averaging (SA) was implemented in a pilot study with 34 clinical cases. EEMD was found to be a reliable, low latency, data-driven denoising technique with respect to the control SA method, achieving signal-to-noise ratio (SNR) enhancement to a standard closer to the SA control method, particularly on the upper arm-ECG bipolar leads. Furthermore, the SNR performance of the EEMD was improved when assisted with an FFT (fast Fourier transform ) thresholding algorithm (EEMD-fft)

PV power forecast using a nonparametric PV model

Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%

solaR: geometría, radiación y energía solar en R

The solaR package includes a set of functions to calculate the solar radiation incident on a photovoltaic generator and simulate the performance of several applications of the photovoltaic energy. This package performs the whole calculation procedure from both daily and intradaily global horizontal irradiation to the final productivity of grid connected PV systems and water pumping PV systems. The package stands on a set of S4 classes. The core of each class is a group of slots with yearly, monthly, daily and intradaily multivariate time series (with the zoo package ). The classes share a variety of methods to access the information (for example, as.zooD provides a zoo object with the daily multivariate time series of the corresponding object) and several visualisation methods based on the lattice andlatticeExtra packages

On the calculation of energy produced by a PV grid-connected system

This study develops a proposal of method of calculation useful to estimate the energy produced by a PV grid-connected system making use of irradiance-domain integrals and denition of statistical moment. Validation against database of real PV plants performance data shows that acceptable energy estimation can be obtained with rst to fourth statistical moments and some basic system parameters. This way, only simple calculations at the reach of pocket calculators, are enough to estimate AC energy