New model to estimate daily global solar radiation over Nigeria

This study focussed on developing an appropriate model for estimating daily global solar radiation for any location in Nigeria. Data for the study were obtained from the Nigeria Meteorological Agency, covering 12 sites, spread across the six geopolitical zones, for a period between 1987 and 2010. Various statistical methods were employed to determine the performance and accuracy of the model. A multivariate model that expresses global solar irradiance in terms of location latitude, daily relative sunshine, maximum daily temperature, daily average relative humidity, and cosine of day number was developed. The inclusion of the maximum daily temperature and daily mean relative humidity makes the model much more sensitive to climatic and weather changes. Also, the seasonal fluctuations of the humid tropical region are also well captured in the model. The analysis showed a good agreement between the measured data and computed results. Thus the model can be used to predict the global solar irradiance over Nigeria with minimum error. Further to this, the global solar radiation intensity values produced by this approach can be used in the design and estimation of the performance of solar applications

Estimation of Effective Day Length at Any Light Intensity Using Solar Radiation Data

The influence of day length on living creatures differs with the photosensitivity of the creature; however, the possible sunshine duration (N0) might be an inadequate index of the photoperiod for creatures with low light sensitivity. To address this issue, the authors tried to estimate the effective day length, i.e., the duration of the photoperiod that exceeds a certain threshold of light intensity. Continual global solar radiation observation data were gathered from the baseline surface radiation network (BSRN) of 18 sites from 2004 to 2007 and were converted to illuminance data using a luminous efficiency model. The monthly average of daily photoperiods exceeding each defined intensity (1 lx, 300 lx, … 20,000 lx) were calculated [defined as Ne(lux)]. The relationships between the monthly average of global solar radiation (Rs), N0, and Ne(lux) were investigated. At low light intensity (<500 lx), Ne(lux) were almost the same as N0. At high light intensity (>10,000 lx), Ne(lux) and Rs showed a logarithmic relationship. Using these relationships, empirical models were derived to estimate the effective day length at different light intensities. According to the validation of the model, the effective day length for any light intensity could be estimated with an accuracy of less than 11% of the mean absolute percentage error (MAPE) in the estimation of the monthly base photoperiod. Recently, a number of studies have provided support for a link between day length and some diseases. Our results will be useful in further assessing the relationships between day length and these diseases

Variations of PV module parameters with irradiance and temperature

© 2017 The Authors. Published by Elsevier Ltd. This paper presents a comparison of common and well-documented methods for varying the single-diode model parameters extracted at standard test conditions (STC) of a PV module to suit varying operating conditions of irradiance and temperature. To perform such a comparison, accurate values of the single-diode parameters at STC are required. These were obtained using well-established numerical and iterative methods. The Newton-Raphson method was found to be most accurate for obtaining these parameters at STC. Consequently, these parameters were used to compare the methods of varying the single-diode model parameters with temperature and irradiance. MATLAB software has been developed to evaluate the performance of each method using the Shell SQ150 PV module. Results are compared with measured data and discussion of the accuracy of various methods is presented. .Published versio

Empirical models for estimating monthly global solar radiation: a most comprehensive review and comparative case study in China

Global solar radiation is a core component of scientific research and engineering application across a broad spectrum. However, its measurement is limited by a small number of stations due to the technical and financial restricts. Estimating solar radiation with the meteorological variables using empirical models is of benefit to obtain solar radiation data at global scale. Yet, there are various options of available empirical models to select the most suitable one. This study conducted a most comprehensive collection and review of empirical models employing the commonly measured meteorological variables and geographic factors. A total of 294 different types of empirical models were collected and classified into 37 groups according to input attributes. Such collection built an empirical model library providing an overall overview of the developed empirical models in literatures. Furthermore, the collected models were calibrated and evaluated at three meteorological stations in the Three Gorges Reservoir Area in China. This study suggests that these model-comparing processes can assist the governments, scientists and engineers in tailoring the most fitted model for specific applications and in particular areas

Investigation of Wind Characteristics in the Southern Region of Algeria

AbstractBefore an investment in wind turbines takes place in a given site, it is important to know several fundamental properties such as wind behavior, availability, continuity, and probability in the proposed region. To make decisions with those properties, statistical and dynamic characteristics of wind of the site should be found out using wind observations and statistical wind evaluation.In this paper a preliminary examination of wind potential of two sites in the southern region of Algeria is dealt with. Wind measured data of a period of 18 years are collected from these two weather stations. Wind speed is studied to find the adequate probability distribution which fits the best the measured data. By performing the χ 2 test we find that the Weibull distribution function is the most adapted. The corresponding parameters were estimated using two methods. These are the quick and the least squares methods. Although that the first method is more practical, the obtained results by both methods can be used to estimate the Weibull parameters for both sites and good agreement is obtained with the measured data