Clear-sky Direct Normal Irradiance Research Articles

A new approach to the real-time assessment of the clear-sky direct normal irradiance

In a context of sustainable development, interest for concentrating solar power and concentrating photovoltaic technologies is growing rapidly. One of the most challenging topics is to improve solar resource assessment and forecasting in order to optimize power plant operation. Since clear sky defines the nominal operating conditions of the plants, improving their management requires the use in real-time of clear-sky direct normal irradiance (DNI) models. Typically, accuracy is best achieved by considering water vapor and aerosol concentrations in the atmosphere separately. However, measuring such physical quantities is not easy and requires a weather station close to the considered site. When these data are not available, the attenuating effects can be modeled by atmospheric turbidity factors which can be obtained from DNI under clear-sky conditions. So, the main purpose of the present paper is to propose an efficient approach to assess the clear-sky DNI in real time. This approach combines an existing empirical model, proposed by Ineichen and Perez, with a new methodology for the computation of atmospheric turbidity. It takes advantage of the fact that changes in atmospheric turbidity are relatively small throughout the day in comparison to changes in DNI, even when the sky is free of clouds. In the present study, we considered data from two experimental sites (Golden, in the USA, and Perpignan, in France) and used a wavelet-based multi-resolution analysis as a clear-sky DNI detection tool. In addition, we compared the proposed approach with several combinations of empirical models and ways of computing atmospheric turbidity. The first model is a polynomial of the cosine of the solar zenith angle, whereas the two other models use atmospheric turbidity as an additional input. Regarding its calculation, monthly and daily mean values have been considered. Moreover, we defined a procedure in order to evaluate the accuracy of all the considered approaches. This procedure allows changes in DNI caused by clouds to be simulated using a noisy signal applied to clear-sky periods. In both sites, our approach to the real-time assessment of the clear-sky DNI outperforms the other approaches. In the worst case, the mean absolute error is reduced by 8 W m−2 in comparison to the approaches based on monthly mean values of atmospheric turbidity, and reduced by about 30 W m−2 when taking the polynomial-based model as a reference.

Improved methodology to evaluate clear-sky direct normal irradiance with a multi-pyranometer array

An improved methodology to estimate the clear-sky direct normal irradiance based on an anisotropic clear-sky model using a Multi-Pyranometer Array (MPA) is analyzed in this paper. The MPA is a static platform with four sensors on surfaces at different tilt and azimuth angles, which measured solar irradiance can be used to estimate the normal incident component without the tracking devices that involve more detailed installation and maintenance. The array’s sensors are of the photovoltaic type, which require both the spectral and angle-of-incidence corrections.Based on the general expressions for the solar radiation on each of the MPA sloped surfaces and using a hybrid model that includes an anisotropic sky diffuse component, in this work an improved procedure is presented that estimate the normal direct solar irradiance by grouping two expressions of a couple of MPA sensors and analytically look for a satisfactory solution; one set for the horizontal and south sensors, and another for the east and west sensors. The solution for the east and west sensors is expanded to two new solutions by mirroring their readings according to the solar noon. A final switching scheme based on the expressions denominator size provides the satisfactory direct normal irradiance estimation. The analysis of the results for the analyzed days showed that the root mean square error (RMSE) decreased by around 14–43% in comparison with previous results reported in the literature. The proposed methodology is a promising new approach for MPA.

Impact of local broadband turbidity estimation on forecasting of clear sky direct normal irradiance

Clear-sky modeling is of critical importance for the accurate determination of Direct Normal Irradiance (DNI), which is the relevant component of the solar irradiance for concentrated solar energy applications. Accurate clear-sky modeling of DNI is typically best achieved through the separate consideration of water vapor and aerosol concentrations in the atmosphere. Highly resolved temporal measurements of such quantities is typically not available unless a meteorological station is located in close proximity. When this type of data is not available, attenuating effects on the direct beam are modeled by Linke turbidity-equivalent factors, which can be obtained from broadband observations of DNI under cloudless skies. We present a novel algorithm that allows for a time-resolved estimation of the average daily Linke turbidity factor from ground-based DNI observations under cloudless skies. This requires a method of identifying clear-sky periods in the observational time series (in order to avoid cloud contamination) as well as a broadband turbidity-based clear-sky model for implicit turbidity calculations. While the method can be applied to the correction of historical clear-sky models for a given site, the true value lies in the forecasting of DNI under cloudless skies through the assumption of a persistence of average daily turbidity. This technique is applied at seven stations spread across the states of California, Washington, and Hawaii while using several years of data from 2010 to 2014. Performance of the forecast is evaluated by way of the relative Root Mean Square Error (rRMSE) and relative Mean Bias Error (rMBE), both as a function of solar zenith angle, and benchmarked against monthly climatologies of turbidity information. Results suggest that rRMSE and rMBE of the method are typically smaller than 5% for both historical and forecasted CSMs, which compare favorably against the 10–20% range that is typical for monthly climatologies.

Atmospheric Turbidity Forecasting using Side-by-side ANFIS

In a context of sustainable development, enthusiasm for CSP technologies is increasing. In addition, the CSPIMP (Concentrated Solar Power efficiency IMProvement) European project has been recently initiated to achieve a better competitiveness of the CSP plants. Its main objective is to develop a new procedure to improve the steam turbine start up cycles, maintenance activities and advanced plant control schemes. A challenge in the project is to forecast the solar resource with the aim of improving the management of CSP plants. A key parameter when trying to estimate or forecast solar radiation is atmospheric turbidity. Indeed, the Direct Normal Irradiance (DNI) under clear sky conditions can be expressed as a function of extraterrestrial irradiation, altitude and atmospheric turbidity. So, this paper focuses on forecasting atmospheric turbidity at different time horizons (up to 3hours) using side-by-side Adaptive Network-based Fuzzy Inference Systems (ANFIS). First, a Multi-Resolution Analysis (MRA) based on the discrete wavelet transform allowed clear sky DNI values to be extracted from the NREL database. In addition, a Principal Component Analysis (PCA) has been considered in order to develop the forecasting model using uncorrelated input variables and reduce its complexity (and, as a consequence, computation time). Finally, the results we obtained about atmospheric turbidity forecasting are satisfactory and validate the proposed approach.