Periodic autoregressive forecasting of global solar irradiation without knowledge-based model implementation

The seemingly complex nature of river flow and the significant variability it exhibits in both time and space, have largely led to the development and application of the stochastic process concept for its modelling, forecasting, and other ancillary purposes. Towards this end, in this study, attempt was made at stochastic modelling of the daily streamflow process of the Benue River. In this regard, Autoregressive Moving Average (ARMA) models and its derivative, the Periodic Autoregressive (PAR) model were developed and used for forecasting. Comparative forecast performances of the different models indicate that despite the shortcomings associated with univariate time series, reliable forecasts can be obtained for lead times, 1 to 5 day-ahead. The forecast results also showed that the traditional ARMA model could not robustly simulate high flow regimes unlike the periodic AR (PAR). Thus, for proper understanding of the dynamics of the river flow and its management, especially, flood defense, in the light of this study, the traditional ARMA models may not be suitable since they do not allow for real-time appraisal. To account for seasonal variations, PAR models should be used in forecasting the streamflow processes of the Benue River. However, since almost all mechanisms involved in the river flow processes present some degree of nonlinearity thus, how appropriate the stochastic process might be for every flow series may be called to question.

The composition of the incident solar global ultraviolet B (UVB) radiation with regard to its beam and diffuse radiation fractions is highly relevant with regard to outdoor sun protection. This is especially true with respect to sun protection during leisure-time outdoor sun exposure at the shore and pools, where people tend to escape the sun under shade trees or different types of shading devices, e.g., umbrellas, overhangs, etc., believing they offer protection from the erythemal solar radiation. The degree of sun protection offered by such devices is directly related to the composition of the solar global UVB radiation, i.e., its beam and diffuse fractions. The composition of the incident solar global UVB radiation can be determined by measuring the global UVB (using Solar Light Co. Inc., Model 501A UV-Biometer) and either of its components. The beam component of the UVB radiation was determined by measuring the normal incidence beam radiation using a prototype, tracking instrument consisting of a Solar Light Co. Inc. Model 501A UV-Biometer mounted on an Eppley Solar Tracker Model St-1. The horizontal beam component of the global UVB radiation was calculated from the measured normal incidence using a simple geometric correlation and the diffuse component is determined as the difference between global and horizontal beam radiations. Horizontal and vertical surfaces positioned under a horizontal overhang/sunshade or an umbrella are not fully protected from exposure to solar global UVB radiation. They can receive a significant fraction of the UVB radiation, depending on their location beneath the shading device, the umbrella radius and the albedo (reflectance) of the surrounding ground surface in the case of a vertical surface. Shading devices such as an umbrella or horizontal overhang/shade provide relief from the solar global radiation and do block the solar global UVB radiation to some extent; nevertheless, a significant fraction of the solar global UVB radiation does penetrate this supposedly 'protective or comfort zone'. As a result, it is imperative to either apply sunscreen or cover up the exposed body surfaces even when under such shading devices.

In this paper, meteorology and satellite data are evaluated to estimate global and direct solar irradiance over Malaysia. The meteorology data consist of direct solar irradiance were for 2013 and the satellite data were global solar irradiance from year 2000 till 2004. The estimated global solar irradiance were then compared with observe satellite data and their performance were judge by using statistical indicators, including root mean squared error and mean percentage error. The 5 cities studied in Malaysia includes Kota Kinabalu (KK), Kuching (KC), Ipoh (IP), Alor Setar (AS) and Kuantan (KU). The yearly average of hourly solar irradiance for all 5 cities throughout a year lies between 193 W/m2 and 208 W/m2. The highest solar irradiance has been estimated at 216 W/m2 in the month of March due to the dry season, and the minimum solar irradiance is predicted in the month of December is 164 W/m2 that coincides with the rainy season in Malaysia. Results show that the proposed global and direct solar irradiance models present good regression coefficient (R2) value of 0.9661 and 0.9549 respectively. The average diffuse solar irradiance cast over these cities were 3.0% (correction factor) of global solar irradiance. Since Malaysian government are focusing on renewable and clean energy, these models and analyses will benefit the government and education department for further development in solar technologies.

Relevant meteorological files are needed by simulation software to assess the energy performances of buildings or efficiency of renewable energy systems. This paper adopts the Sandia method to generate typical meteorological year (TMY), using a 35-year hourly measured meteorological dataset from four stations in the northern region of Nigeria. The cumulative distribution function (CDF) for each year was compared with that of the long-term composite of all the years in the period for the seven major weather indices made up of relative humidity, wind speed, minimum temperature, global solar radiation, precipitation, mean temperature and maximum temperature. The 12 typical meteorological months (TMMs) selected from the different years were used for formulation of a TMY for the zone. In addition, performance assessment of a 72-cell polycrystalline solar PV module using the generated TMY and long-term (LT) values was also conducted. Two statistical indicators, the mean percentage error and the root mean square error, were adopted to evaluate the performance of each TMY with the LT mean, and also that of the PV energy system. Findings show that the TMMs are evenly spread within the data periods across the sites while closest fit between the long-term mean and TMY are obtained with the global solar radiation followed by the mean temperature in all the sites especially in Bida and Minna. From the energy system analysis carried out, it was found that TMY data are able to predict the performance of the PV system to within 5% of the LT data.

Geospatial and multi-criteria decision-making techniques are applied to process and analyse datasets for determining suitable areas for multiple utilityscale solar photovoltaic farms in the city of Akure, Ondo State, southwestern Nigeria. Data processed include local electric power distribution system data, Shuttle Radar Topographic Mission elevation data, Landsat 8 and solar global horizontal irradiance. Multi-criteria decision-making techniques adopted are the analytical hierarchy process, reclassification, and overlay. These techniques were carried out considering criteria for siting solar photovoltaic farms. Criteria considered in this study are climate, topography, economic, environmental impact operational and technical while sub-criteria are solar global horizontal irradiance, slope, proximity and land cover. The outcome of the study shows that the study area covering a total extent of ~33,200 ha, 15%, 8%, 13% and 64% are highly suitable, suitable, moderately suitable, and unsuitable respectively for siting utility-scale solar photovoltaic farms within the study area. The study reveals the potential of multiple utility-scale solar photovoltaic farms in the study area. However, the proportions of areas suitable for solar photovoltaic farms are quite lower compared to findings from similar studies conducted in northwestern Nigeria. The study recommends solar photovoltaic sources as an alternative energy source in and around the study area.

Generation of meteorological year for the assessment of photovoltaic systems performance in Togo, West Africa

The precise assessment and evaluation of global solar radiation (GSR) is crucial for designing effective solar energy systems. However, in developing countries like Ethiopia, the cost and maintenance of measuring devices are inadequate. As a result, researchers have explored alternative methods such as empirical models to estimate GSR. This article proposes using artificial neural networks (ANN) to predict daily and monthly averaged horizontal GSR (HGSR) around Fiche town of Ethiopia, using various network types. The input variables were divided into training (70%) and testing (30%) sets to evaluate the network types, with the sigmoid function used as the activation function at the hidden layer and a linear function for the output layer. The predicted mean daily and monthly HGSR ranges from 3.282 kWh/m2/day to 6.967 kWh/m2/day and 4.628 kWh/m2 to 6.613 kWh/m2 respectively. The values obtained were compared to those provided by NASA observation data and were found to be within acceptable limits. Statistical metrics of MAPE, MSE, and RMSE show that CFBP, FFBP, LR, and EBP are better network types for estimating mean daily HGSR, while EBP, FFBP, CFBP, and LR are better for estimating mean monthly HGSR. Overall, all network types of ANN accurately predicted the mean daily and monthly HGSR. In general, the findings of this study indicated that the location had promising solar energy for producing electricity and for various uses.

Binding data mining and expert knowledge for one-day-ahead prediction of hourly global solar radiation

Abstract. In this paper, we evaluate the performance of two global horizontal solar irradiance (GHI) estimates, one derived from Meteosat Second Generation (MSG) and another from the 1-day forecast of the Regional Atmospheric Modeling System (RAMS) mesoscale model. The horizontal resolution of the MSG-GHI is 3 × 5 km2 over Italy, which is the focus area of this study. For this paper, RAMS has the horizontal resolution of 4 km.The performances of the MSG-GHI estimate and RAMS-GHI 1-day forecast are evaluated for 1 year (1 June 2013–31 May 2014) against data of 12 ground-based pyranometers over Italy spanning a range of climatic conditions, i.e. from maritime Mediterranean to Alpine climate.Statistics for hourly GHI and daily integrated GHI are presented for the four seasons and the whole year for all the measurement sites. Different sky conditions are considered in the analysisResults for hourly data show an evident dependence on the sky conditions, with the root mean square error (RMSE) increasing from clear to cloudy conditions. The RMSE is substantially higher for Alpine stations in all the seasons, mainly because of the increase of the cloud coverage for these stations, which is not well represented at the satellite and model resolutions. Considering the yearly statistics computed from hourly data for the RAMS model, the RMSE ranges from 152 W m−2 (31 %) obtained for Cozzo Spadaro, a maritime station, to 287 W m−2 (82 %) for Aosta, an Alpine site. Considering the yearly statistics computed from hourly data for MSG-GHI, the minimum RMSE is for Cozzo Spadaro (71 W m−2, 14 %), while the maximum is for Aosta (181 W m−2, 51 %). The mean bias error (MBE) shows the tendency of RAMS to over-forecast the GHI, while no specific behaviour is found for MSG-GHI.Results for daily integrated GHI show a lower RMSE compared to hourly GHI evaluation for both RAMS-GHI 1-day forecast and MSG-GHI estimate. Considering the yearly evaluation, the RMSE of daily integrated GHI is at least 9 % lower (in percentage units, from 31 to 22 % for RAMS in Cozzo Spadaro) than the RMSE computed for hourly data for each station. A partial compensation of underestimation and overestimation of the GHI contributes to the RMSE reduction. Furthermore, a post-processing technique, namely model output statistics (MOS), is applied to improve the GHI forecast at hourly and daily temporal scales. The application of MOS shows an improvement of RAMS-GHI forecast, which depends on the site considered, while the impact of MOS on MSG-GHI RMSE is small.

The power capacity of solar photovoltaics (PVs) in Korea has grown dramatically in recent years, and an accurate estimation of solar resources is crucial for the efficient management of these solar PV systems. Since the number of solar irradiance measurement sites is insufficient for Korea, satellite images can be useful sources for estimating solar irradiance over a wide area of Korea. In this study, an artificial neural network (ANN) model was constructed to calculate hourly global horizontal solar irradiance (GHI) from Korea Communication, Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) images. Solar position variables and five COMS MI channels were used as inputs for the ANN model. The basic ANN model was determined to have a window size of five for the input satellite images and two hidden layers, with 30 nodes on each hidden layer. After these ANN parameters were determined, the temporal and spatial applicability of the ANN model for solar irradiance mapping was validated. The final ANN ensemble model, which calculated the hourly GHI from 10 independent ANN models, exhibited a correlation coefficient (R) of 0.975 and root mean square error (RMSE) of 54.44 W/m² (12.93%), which were better results than for other remote-sensing based works for Korea. Finally, GHI maps for Korea were generated using the final ANN ensemble model. This COMS-based ANN model can contribute to the efficient estimation of solar resources and the improvement of the operational efficiency of solar PV systems for Korea.

In this paper, we address the problem of modeling data with periodic autoregressive (PAR) time series and additive noise. In most cases, the data are processed assuming a noise-free model (i.e., without additive noise), which is not a realistic assumption in real life. The first two steps in PAR model identification are order selection and period estimation, so the main focus is on these issues. Finally, the model should be validated, so a procedure for analyzing the residuals, which are considered here as multidimensional vectors, is proposed. Both order and period selection, as well as model validation, are addressed by using the characteristic function (CF) of the residual series. The CF is used to obtain the probability density function, which is utilized in the information criterion and for residuals distribution testing. To complete the PAR model analysis, the procedure for estimating the coefficients is necessary. However, this issue is only mentioned here as it is a separate task (under consideration in parallel). The presented methodology can be considered as the general framework for analyzing data with periodically non-stationary characteristics disturbed by finite-variance external noise. The original contribution is in the selection of the optimal model order and period identification, as well as the analysis of residuals. All these findings have been inspired by our previous work on machine condition monitoring that used PAR modeling.

Global solar radiation is of great significance to the balance of ground surface radiation, the energy exchange between the Earth’s surface and atmosphere, and the development of weather and climate systems in various regions. In this study, the monthly global radiation recorded at 23 stations over the Qinghai–Tibetan Plateau (QTP) was utilized to estimate global solar radiation (Q) from sunshine duration and to obtain improved fits to the variation coefficients of the monthly Angstrom–Prescott model (APM). The modeling results were evaluated by calculating the statistical errors, including mean bias error, mean absolute error, root mean square error, and mean relative error. We demonstrate that the monthly Q values can be predicted accurately by APM over the QTP. We also assess the variations of Q values at 116 meteorological stations by APM over the QTP during 1961–2000. The analysis shows that the annual mean sunshine duration amounted to more than 3,000 h over the whole plateau, implying promising prospects for economic applications of solar energy. During the past 40 years, the mean global solar radiation has been relatively high in the western QTP, extending northward to the Inner Mongolian Plateau. Although its decadal variations in the QTP and surrounding regions were inconsistent, the anomaly values of global solar radiation were generally positive during the 1960s and 1970s, indicating that the QTP’s global solar radiation has increased during those periods. The anomaly values were negative during the 1980s and 1990s, showing that the plateau’s global solar radiation has decreased during those periods. Global solar radiation over the QTP is negatively proportional to latitude but positively proportional to altitude and relative sunshine duration. Three factors, the sunshine duration, latitude, and altitude, exert great influence on global surface radiation, of which sunshine duration is most significant. A high-variation-coefficient zone of global solar radiation occurred in the western part of the QTP but, on average, the variation coefficient of the plateau’s global solar radiation was only 0.031, suggesting that the variation in global radiation was relatively stable over the whole QTP.

Parameters characterizing the properties of the local climate, among them the solar irradiance, as part of the so-called Typical Meteorological Year – TMY, are often averaged and modeled. To determine the actually available solar conditions, it is beneficial to perform additional studies of climate factors in specific locations. The article presents the analysis of the solar irradiance measurements results for Częstochowa, carried out in June, July and August, in different years, in comparison to data from typical meteorological year for this period. TMY developed in Poland as well as TMY from PVGIS databases were used. Due to the occurrence of significant discrepancies in the values of solar irradiance, in the considered large data sets, it was found necessity to update the currently used TMY PL for Częstochowa, which were determined on the basis of data from the years 1971–1991. The analysis also included local sunshine duration and its summer anomalies. In addition, the dependence of solar conditions on the particulate matter PM10 content in the air, which is rarely considered in the summer, is presented.

With the overall aim of quantifying urban atmospheric effects on different parts of the solar spectrum, a multi year analysis of data collected at Łódź was undertaken. UV (290–400 nm) and global solar radiation measured by means of a Kipp and Zonen CUV3 radiometer and a Kipp and Zonen CM11 pyranometer in the center of Łódź between 1997 and 2001 are analysed. The mean annual sum of global and UV solar radiation equaled 3710.8 MJ m−2 and 154.1 MJ m−2, respectively. The minimum monthly total of solar energy occurred in December (48.7 M Jm−2—global; 2.1 MJ m−2—UV); however, the maximum monthly total occurred atypically in May (620.9 MJ m−2—global; 25.3 MJ m−2—UV). UV clearness index (Kuv) is approximately half of the clearness index of the global solar radiation, indicating greater attenuation of that part of the spectrum (Kuv 0.14 in December to 0.26 in May). A linear regression model was fitted to the daily values of UV and global (g) solar irradiation (Duv = a + Dgb). The slope coefficient b and the coefficient of determination equal 0.039 and 0.98, respectively. Cloudiness exerts an important control on the solar radiation flux at the ground level and for the relation between UV and global solar radiation. The convective clouds caused an increase of global and UV solar irradiance by about 10–20% compared to clear days, the enhancement resulting from reflections. On clear days, UV comprises 3.3–4% of global solar irradiance (10‐min values) on average, while during cloudy weather it increases to 8%. The results presented have implications for understanding the radiative transfer of UV and global solar radiation in the atmosphere over an urban area and the influence of clouds on transmission of solar radiation flux. Copyright © 2009 Royal Meteorological Society

Analysis of solar irradiation measurements at Beer Sheva, Israel from 1985 through 2013