太阳总辐射逐时模型

采用时间序列分析法建立了联合使用确定性模型和随机性模型的太阳总辐射逐时模型,其预报精度优于常用的确定性模型。     

太阳辐射逐时模型的建立

讨论了性确定性与模型与随机模型联合使用方法，建立了太阳总辐射ＡＲＩＭＡ逐时模型，该模型可用于模拟逐时太阳辐射，提供建筑能耗分析用的逐时太阳辐射参数，还可用于预报，控制等。     

湍流对辐射传递的影响

本文通过对辐射传递方程的雷诺时均处理，分析了燃烧室内湍流对辐射传递过程的影响。通过对基于时均温度计算的自身辐射与自身辐射的时均值比较，指出了建立湍流辐射模型的重要性。最后，通过对Ｔｆｖ，ｆｖＩ，Ｔ等脉动关联项的模拟分析，提出一种建立湍流辐射模型的可能途径。     

太阳辐射的计算机模型

本文提出了以太阳总辐射作为大气衰减因子的综合指标，建立各辐射波段与总辐射的函数，关系，从而设计出云层条件下太阳辐射的计算机模型。     

太阳日总辐射量的Box-Jenkins模型

基于天文辐射和日照率数据,采用系统辨识的方法建立了模拟太阳日总辐射量的BJ(Box-Jenkins)模型。该模型与传统的ngstrm的日总辐射量的计算公式相比,模拟和预测效果更好。     

日太阳散射辐射月均值的估算

建筑物空调系统的全年或季节能耗分析和太阳能系统的设计分析,需要已知太阳总辐射和散射辐射数据。我国大多数地区只有总辐射观测,没有直接辐射或散射辐射观测,因此需要有一种散射辐射的估算方法。根据全国8个典型城市的实测数据．分析了日散射辐射和日总辐射与日照时长的关系,分别建立了日散射月均值的多项式拟合模型。经过郑州地区数据的检验认为,模型有很好的拟合性能,该模型可以作为通用模型。     

基于小波变换的组合随机模型及其在径流随机模拟中的应用

首先对原始水文序列施行A Trous小波分解，得到各分过程，再对分过程进行分析与识别，确定它们所具有的主要成分。然后分别建立适当的随机模型，最后运用A Trous重构算法得到原水文序列的组合随机模型。以屏山站年径流过程为例进行随机模拟研究。结果表明该法概念清晰，结构简单，方便实用。     

联合分布网络的随机约束模型及其应用

针对随机约束的联合分布网络模型是一种复杂的非线性模型,当工序数较多时难以求解,假设用一组单独的随机约束近似取代联合随机约束,则可得到某种确定性的线性等价模型.实例应用结果表明,采用线性等价法求解随机约束的联合分布网络模型,可得到较精确的网络参数.     

日太阳总辐射月均值的估算

通过对中国8个典型城市日太阳总辐射实际观测月均值的分析,得到了较为近似的日太阳总辐射月均值模型,并用该模型对郑州地区的数据进行了预测,预测值与实测值吻合良好,表明该模型具有很好的通用性,为中国太阳能的利用提供了科学依据.     

内燃机辐射噪声三维计算模型

应用声边界元理论建立了内燃机辐射声场三维计算模型，开发了计算程序，利用复式声强测量得到的空间粒子速度分布作为书籍边界条件计算了Ｌ１９５柴油标定工况的辐射声功率及其辐射声场分布。试验结果表明，本内燃机辐射噪声计算模型和计算程序准确可靠，声边界元方法是内燃机辐射声场计算的一种有效方法，为低噪声内燃机设计奠定了基础。     

Stochastic modelling of daily global solar radiation measured in Marrakesh, Morocco

Two stochastic models are presented of the daily global solar radiation obtained from three years of data measured on a horizontal surface in Marrakesh, Morocco (latitude 31°37′N, longitude 08°02′W, elevation 463 m). The development of these models is based on the removal of the annual periodicity and seasonal variation of solar radiation using two types of normalisation. The first model is developed using a classical decomposition of the daily radiation as the sum of two components: a trend component and a stochastic component. This model is most useful for long simulated sequences. The second model is developed using a non-dimensional variable, the clearness index, which is modelled as a stochastic process after a preliminary transformation leading to a stationary time series. Both models have satisfactorily passed validation tests for forecasting and simulation of daily global solar radiation data.     

Methodology for generating daily clearness index index values Kt starting from the monthly average daily value . Determining the daily sequence using stochastic models

The facility to generate weather data from limited inputs and independently of specific locations would allow simulations of energetic systems to be run at locations for which detailed weather records do not exist. This article presents a methodology to calculate synthetic daily solar radiation values and describes how sequences of daily global radiation can be generated using as input the monthly average radiation. A stochastic model, ARIMA(1,1,1) is presented, as well.     

Testing for nonlinearity in solar radiation time series by a fast surrogate data test method

Recently, various time series models have been proposed to predict solar radiation, for instance the ARIMA (autoregressive integrated moving average) model and neural networks. Before building a model for the data, however, it is advisable to check whether the data suggest this type of modeling. More specifically, a nonlinearity test is suggested before further analysis with the linear or nonlinear tools are to be applied. In this paper, we test the presence of nonlinearity in the solar radiation time series by the method of surrogate data. The surrogate test method used in this paper is based on evaluation of the differences between the original time series and the linear model that best approximates it. Nonlinearity tests are carried out for four data sets including 5-min, hourly, daily and monthly global solar radiation time series from the UO (University of Oregon) Solar Radiation Monitoring Laboratory. The test statistics show that the 5-min, hourly, daily global solar radiation time series exhibit apparently nonlinearity while the monthly time series does not.     

A multivariate qualitative model for the prediction of daily global radiation from three hourly global radiation values

A new model for the prediction of daily global radiation using three hourly radiation values is proposed. This model is obtained by multivariate regression analysis. The hourly clearness index and various qualitative variables are used as independent variables. The hourly values are obtained from net ground measures of hourly global radiation corresponding to the hours in which Meteosat secondary images are available over Europe. The qualitative variables allow us to include additional non-numerical information, specifically, the season of the year. The proposed model is the same for all the locations analysed. This model can be used for the prediction of daily global radiation based on hourly global radiation data obtained from satellite images.     

Analysis of residuals in daily solar radiation time series

The Box-Jenkins approach is applied to daily solar radiation data from four different locations in Malaysia. The deterministic annual component is obtained by Fourier analysis. The stochastic component of the time series is fitted to three models, ARMA (1,0), ARMA (2,0) and ARMA (1,1). Random shocks from these models are tested by Box-Pierce statistic and Ljung-Box for whiteness of residuals. Skewness and kurtosis coefficients are tested for normality.     

Automatic modelling and simulation of daily global solar radiation series

This paper presents a new model to generate simulated daily global solar radiation (DGSR) sequences. A DGSR value is the product of two factors: a seasonal low-frequency component, principally due to the sun's periodic movement, and a random component due to rapid fluctuations of the atmospheric environment. Methods are provided to automatically separate and estimate both components from the available (generally short) DGSR records. Hence, other series describing the sun-position evolution or any kind of atmospheric conditions are not necessary. An illustrative example is included which results in a good global agreement between simulated and original sequences.     

An assessment of a revised Olmo et al. model to predict solar global radiation on a tilted surface at Beer Sheva,Israel

A model to convert horizontal solar global radiation to that on a tilted surface is presented. It is based upon a relatively simple model proposed by [Olmo FJ, Vida J, Foyo I, Castro-Diez Y, Alados-Arboledas L. Prediction of global irradiance on inclined surfaces from horizontal global irradiance. Energy 24 (1999) 689–704]., which requires only measurements of horizontal solar radiation but was found to produce significant errors when tested with data from another site. The present model assumes the availability of databases for at least two of the three solar radiation types, viz., global, beam and diffuse. The horizontal global radiation is converted to that on a tilted surface by applying the Olmo model to the diffuse component, whereas the beam component is converted by using the geometrical relationship between the two surfaces. The original Olmo anisotropic radiation correction factor is now assumed to be a function of sky conditions. The solar radiation databases were converted to subsets corresponding to clear, partially cloudy and cloudy sky based upon clearness index values. The three anisotropic correction factors were determined by fitting to a 12-months database. The present model was then tested by applying it to a second database consisting of 24-months not involved in the model development. It was found to give better results than three highly regarded more complex models.     

Simple model for the generation of daily global solar-radiation data in Turkey

Modelling, performance analysis, and designing of solar energy systems depend on solar radiation data. In this study, a simple model for estimating the daily global radiation is developed. The model is based on a trigonometric function, which has only one independent parameter, namely the day of the year. The model is tested for 68 locations in Turkey using the data measured during at least 10 years. It is seen that predictions from the model agree well with the long-term measured data. The predictions are also compared with the data available in literature for Turkey. It is expected that the model developed for daily global solar radiation will be useful to the designers of energy-related systems as well as to those who need to estimates of yearly variation of global solar-radiation for any specific location in Turkey.     

A comparative study of solar irradiation models on various inclined surfaces for India

This paper presents a statistical approach for the estimation of the diffuse/global irradiation on various inclined surfaces from the measured data of horizontal surface. In fact diffuse solar radiation on an inclined plane consists of two components: sky diffuse radiation and reflected radiation from the ground. For analyzing estimation of the daily tilted sky diffuse component from the daily horizontal diffuse irradiance, we have considered six models Badescu, Circumsolar, Skartveit and Olseth, Hay, Klucher and Liu and Jordan (Isotropic). All these models except Badescu adopted the same methodology for estimating the ground-reflected radiation component, therefore, only sky diffuse component was analyzed at Lucknow (latitude 26.75°, longitude 80.50°), India location. Statistical analysis showed that the Skartveit and Olseth model gives good prediction for the low inclination angle however; Klucher model gave better performance for highly inclined south-facing surfaces. The Root Mean Square Errors (% RMSE) value varies from 3.45% to 24.15% except for Badescu and Circumsolar model which predict worse results. In general, Klucher’s model provides close agreement with the measurements.     

Simulation of global solar radiation based on cloud observations

A stochastic model for simulating global solar radiation on a horizontal surface has been developed for use in power systems reliability calculations. The importance of an appropriate model for global solar radiation has increased with the increased use of photovoltaic power generation. The global solar radiation shows not only regular yearly and daily variations but also a random behaviour. The yearly and daily variations can be described in a deterministic way while the random behaviour has a high correlation with the state of the atmosphere. The astronomic effects can easily be described mathematical with only some minor simplifications but the atmospheric effects are more complicated to describe. The transmittivity of solar radiation in the atmosphere depends on various factors, e.g. humidity, air pressure and cloud type. By using cloud observations as input for the simulations, the local meteorological conditions can be accounted for. The model is usable for any geographical location if cloud observations are available at the location or at locations with similar climatological conditions. This is especially useful for development countries where long-term solar radiation measurement can be hard to obtain. Cloud observations can be performed without any expensive equipment and have been a standard parameter for many years throughout the world. Standard observations are done according to the Oktas-scale. It is the interval between observations that sets the resolution of the simulation: the observations are normally only every hour or every third hour. The model can easily be combined with cloud coverage simulations, has been proposed, for a more general model. For some calculations higher resolution may be needed. This can be obtained by including a stochastic model for the short-term variations and simple model has been proposed. Errors and limitations of the model are estimated and discussed.