Distribution Of Solar Radiation Research Articles

Influence of the building enclosed forms on thermal contribution of retro-reflective and high-reflective coatings

There are more high-density urban spaces and their forms prominently affect the regional thermal environment, especially for the spatial distribution of solar thermal radiation. Under this condition, the contribution efficiency of reflective coatings should be reevaluated to improve the regional thermal environment. Three typical forms of high-density buildings, namely the Determinant Form (d-Form), Three-Sided Enclosed Form (TSE-Form) and Four-Sided Enclosed Form (FSE-Form), were proposed. High-reflective coatings (HR-coatings) and retro-reflective coatings (RR-coatings) were employed with the different reflective mechanisms, while the albedo, wall temperature, and air temperature were monitored. Experimental results showed that the higher the enclosed degree of buildings covered by HR-coatings, the poorer the regional thermal environment and the higher the heat island efficiency. However, the opposite was true in enclosed buildings with RR-coatings. RR-coatings had a better thermal contribution than HR-coatings, and the higher the enclosure degree of buildings, the higher the improvement efficiency of RR-coatings. Compared with HR-coatings, RR-coatings increased the maximum and average regional albedos by 0.67 %∼3.42 % and 1.36 %∼5.59 %, respectively, and lowered the maximum and average temperatures by 0.26 °C∼7.05 °C and 0.02 °C∼4.83 °C for model walls and 0.59 °C∼4.41 °C and 1.80 °C∼3.06 °C for outdoor air, respectively.

Statistical Analysis and Distribution of Global Solar Radiation and Temperature Over Southern Nigeria

The intensity of solar energy that is received by a particular location is affected by most meteorological conditions including, the solar irradiance received by the location, precipitation, extreme heat as a result of the surface or ambient temperature, etc. We obtain the monthly global solar irradiation and ambient temperature for the three (3) eco-climatic zones in the south of Nigeria (17 locations) for 12 years (2005 - 2016) from the Photovoltaic Geographical Information System (PVGIS) Satellite. The goal of this study is to understand how regional meteorological conditions affect radiation and temperature reception. Monthly and annual trends were plotted and compared for both variables in each region to show the similarity or dichotomy in their trends. The Mann-Kendall (M-K) trend test has been adopted to reveal that the changes in the variations on an annual basis, and results showed that the trend were not significant for both variables. Box plots have been used to give a better description of the data, and compared to show similarities and differences. Finally, we adopted the Gaussian (normal) distribution to show, understand and compare the data distribution. Linear regression plots for each zone shows that the relationship between the solar irradiation and temperature is high. Results show that the climate and vegetation of a region contributes majorly to the variation of radiation and temperature. Inhomogeneityof data or results for locations in the same zones may be attributed to local meteorological conditions. The results obtained here will prove vital in decision making relating to the adoption of solar energy technologies in the region. Results show that the climate and vegetation of a region contributes majorly to the variation of radiation and temperature. Inhomogeneity of data or results for locations in the same zones may be attributed to local meteorological conditions.

<i>Orbital, the Box</i> – an Interactive Educational Tool for In-depth Understanding of Astronomical Climate Forcing

“Orbital, the Box” provides an interactive tool with graphical user interface (GUI) for stimulating active, visual learning for understanding of astronomical climate forcing. This cross-platform tool can be run locally on a personal computer using a standard web browser environment with no need for plugins, thus maximising accessibility for students and teachers alike. The tool facilitates in the development of a holistic and quantitative understanding of astronomical climate forcing by allowing students to independently vary orbital parameters, after which they can instantaneously see the resulting effect upon the seasonal and latitudinal distribution of solar irradiance arriving at the top of the Earth’s atmosphere. Such an approach follows a classic controlled experimental design whereby one parameter can be changed while all others are kept constant. This experimental tool can be deployed as a virtual laboratory, including within a flipped classroom setting, to promote active learning of traditionally challenging concepts such as the roles of eccentricity and precession in astronomical climate forcing, and in particular their interaction with Kepler’s second law and the subsequent consequences for season length.

What does Modelling Tells us on the Influence of Certain Weather Parameters on Oil Palm Production in Peninsular Malaysia

Background: Oil palm has been recognized as one of the most important crops especially in Southeast Asia and the rest of the world. Palm oil production has recently been lowered as a result of the influence of various factors, which include weather and climate. The distribution of temperature, wind speed, relative humidity, solar radiation and rainfall all influence the growth and development of palms, which later reflects in the production quantity of the fresh fruit bunches and palm oil. The objective of this study is to investigate the impacts of various weather factors especially (temperature, wind speed, relative humidity, solar radiation and rainfall) on oil palm production in Peninsular Malaysia. Methods: The Statistical Package for Social Sciences (SPSS) 20.0 version was used to analyse the data, which include descriptive statistics and multilinear regression (MLR). The MLR model evaluated the strength of the relationship between oil palm yield (as a dependent variable) and temperature, solar radiation, wind speed, relative humidity and precipitation. Temperature, wind speed, relative humidity, solar radiation and rainfall, on the other hand, have been shown to have little effect on oil palm production and yield. Result: According to the R2 value, the independent variables only explained 20.2% of the variation in palm oil production. This study recommends operating within a comprehensive framework that includes scientific research, planting improved varieties, enhancing regional intellectual and academic leadership, engaging the participation of private and public stakeholders, highlighting participatory initiatives with researchers in consumer countries and enhancing growers’ ability to adapt best agroecological practises.

New system designed for monitoring of solar radiation in urban areas

AbstractThis study describes the estimation of solar radiation from photovoltaic (PV) power generation in smart streetlights (SSL) with a heat transfer model. The distribution of solar radiation is important for managing PV power generation. In particular, the demand for electricity for air conditioners and lighting in urban areas is large, so it is a major target for reducing greenhouse gases by introducing PV power. Solar radiation data that includes information on building shadows and reflections can be obtained by high‐density sampling in urban areas using SSL. These data, which include the three‐dimensional effects of urban structures such as buildings, can help urban planning to incorporate PV power generation. Diverse monitoring data in addition to urban canopy top solar radiation data will accelerate the introduction of PV power. The thermal state of the PV panel is an uncertain factor that links solar radiation and PV power generation. Here, we investigate an hourly constant model, a steady‐state model, and two nonsteady state models with daily and monthly intervals for predicting solar radiation from PV power generation at two locations over one winter month. Solar radiation is estimated by evaluating solar cell temperature, except for the hourly constant model. For the nonsteady‐state model, two types of heat transfer model, which consider only wind speed or both wind speed and direction for convection, are used. The model that includes wind speed and direction calculated by a Joukowski transform is effective, and the highest model accuracy is a mean absolute percentage error of less than 6.3% for the monthly average.

New development of a solar electrochemical raceway pond reactor for industrial wastewater treatment

In this work, a solar electrochemical-raceway pond reactor (SEC-RPR) is used to treat textile industrial wastewater by solar photoelectron-Fenton (SPEF) at pilot plant scale for the first time. The SEC-RPR is composed of an electrochemical filter press-cell coupled to RPR, where H2O2 is electro-generated. A complete study about experimental variables such as current, catalyst concentration, pollutant load or liquid depth is conducted based on methyl orange removal, mineralization and decolorization. Validation of the SPEF process using SEC-RPR reached more than 80% of mineralization, as well as the complete decolorization of the solution. The good performance of the SPEF treatment in the new SEC-RPR led to quick degradation kinetics, mainly due to the synergetic action of solar radiation and good distribution of H2O2 electrogenerated in the photoreactor. 100% Methyl Orange degradation was achieved after 150, 60, 45, 30 and 20 min of reaction time applying current density equal to 5, 10, 20, 40 and 60 mA cm−2, respectively. However, the increase of current density decreased the mineralization current efficiency. Up to 10 aromatics intermediates and 5 short-chain carboxylic acids were identified by LC-MS and HPLC analysis and a reaction pathway for MO mineralization by SPEF is proposed. This study represents an essential preliminary step towards the development of the first SEC-RPR at demo scale.

Simplified estimation modeling of land surface solar irradiation: A comparative study in Australia and China

Solar irradiation maps are fundamental geospatial datasets that have been used in a variety of research fields. However, it is difficult to estimate the continuous distribution of solar irradiation over large areas accurately by using conventional interpolation or extrapolation methods based on only a few observation stations. To tackle this problem, this study proposed a method to estimate spatially continuous land surface solar irradiation based on four machine learning models, namely, Gradient Boosting Machine (GBM), Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron (MLP). Clear-sky solar irradiation data were computed based on time and location, cloud optical thickness (COT) and aerosol optical thickness (AOT) that significantly influence solar irradiation were retrieved from Himawari-8 meteorological satellite images, and land surface solar irradiation data were obtained from observation stations for training and evaluation. To explore the weather effects on land surface solar irradiation, air temperatures, humidity, wind, and atmospheric pressure were also quantified and integrated into the models. As a comparative study, this study collected six-year historical data and estimated solar distribution at a 5-km spatial resolution in Australia and China. Based on the coefficient of determination (R2), normalized Root Mean Square Error (nRMSE), normalized mean bias error (nMBE), and consumption of time (t), the results show that GBM achieved the highest accuracy with R2>0.7 at all stations, followed by RF, SVR, and MLP. It suggests that the proposed method can provide an accurate and reliable estimation of land surface solar irradiation, compared with the theoretical solar irradiation without the obstacle of the atmosphere. The annual solar distribution maps created by the built methods indicate that the proposed method is simple and effective for large geographical regions and can be used worldwide when similar datasets are obtained.

The Zonation of Mountain Frozen Ground under Aspect Adjustment Revealed by Ground-Penetrating Radar Survey—A Case Study of a Small Catchment in the Upper Reaches of the Yellow River, Northeastern Qinghai–Tibet Plateau

Permafrost distribution is of great significance for the study of climate, ecology, hydrology, and infrastructure construction in high-cold mountain regions with complex topography. Therefore, updated high-resolution permafrost distribution mapping is necessary and highly demanded in related fields. This case study conducted in a small catchment in the northeast of the Qinghai Tibet Plateau proposes a new method of using ground-penetrating radar (GPR) to detect the stratigraphic structure, interpret the characteristics of frozen ground, and extract the boundaries of permafrost patches in mountain areas. Thus, an empirical–statistical model of mountain frozen ground zonation, along with aspect (ASP) adjustment, is established based on the results of the GPR data interpretation. The spatial mapping of the frozen ground based on this model is compared with a field survey dataset and two existing permafrost distribution maps, and their consistencies are all higher than 80. In addition, the new map provides more details on the distribution of frozen ground. In this case, the influence of ASP on the distribution of permafrost in mountain areas is revealed: the adjustment of ASP on the lower limit of continuous and discontinuous permafrost is 180–200 m, the difference in the annual mean ground temperature between sunny and shady slopes is up to 1.4–1.6 °C, and the altitude-related temperature variation and uneven distribution of solar radiation in different ASPs comprehensively affect the zonation of mountain frozen ground. This work supplements the traditional theory of mountain permafrost zonation, the results of which are of value to relevant scientific studies and instructive to engineering construction in this region.

Joint probability distribution of air temperature and global solar radiation for outdoor design conditions based on copula approach

In the common method of compiling outdoor design conditions by annual cumulative frequency of occurrence, the probability of simultaneous occurrence of the selected meteorological elements is not considered, which may lead to an overestimation of air-conditioning equipment capacity design. This paper aims at developing a novel approach for producing the outdoor design conditions, taking into consideration the dependency between the air temperature and global solar radiation, which have a strong influence on the HVAC capacity design. These two meteorological elements are analyzed for specific simultaneous occurrence probability based on the joint distribution. For this purpose, the copula approach which can describe the dependence between these two meteorological elements is used for modeling the joint distribution function. We investigated copula family selection for air temperature and global solar radiation at each hour of hourly weather data for 10 years from 2001 to 2010 in Osaka, Japan. The Joe-Frank copula has the best fitting results for the dependence between the air temperature and global solar radiation. According to the comparison of original exceeding probability and simultaneous occurrence probability, the results show that the design conditions based on the common method can significantly exceed that of the simultaneous occurrence probability method. Practical Application: Outdoor design conditions are used in the building design stage to estimate building performance and select the appropriate air conditioning equipment capacity. Excessive air-conditioning capacity may lead to a large amount of unnecessary energy wastage. Insufficient capacity may lead to not meeting the desired indoor environment conditions of utilization in extreme weather conditions, especially for large office buildings. Therefore, this paper provides a new approach to generate more realistic meteorological conditions for air-conditioning design to improve building energy efficiency.

View Factors in Horizontal Plane Fixed-Mode Solar PV Fields

In solar PV fields, solar photovoltaic panels are typically arranged in parallel rows one after the other. This arrangement introduces variations in the distribution of solar irradiance over the entire field, compared to measurements recorded at meteorological weather stations and data obtained from climatic database platforms. This is due to the difference in the view factors between the rows of the solar PV field and a single surface, as well as the presence of shade on rear sides and in the space separating the rows. These phenomena combined will reduce the intensity of solar irradiance incident on the PV solar field; consequently will reduce the energy yields. Accurate estimation of solar radiation on solar fields requires knowledge of the sky, ground, and rear side of the preceding row view factors, and an estimation of the time and space occupied by the row’s shadow. Prior literature has addressed this issue using two-dimensional (2-D) techniques such as the crossed-strings method (CSM). This study developed a novel three-dimensional (3-D) analysis in addition to numerical analysis to determine the view factors associated with solar fields. The study uses both isotropic and anisotropic transposition analyses to determine solar irradiance incident on the solar field with varying tilt angles of solar panels and distance separating the rows (distance aspect ratio) for several latitudes. The present research also tested the validity of the CSM for wide ranges of distance separating rows and length aspect ratios, the obtained results show that the CSM shows good agreements in both sky and ground view factor in the range of length aspect ratio greater than one. But the CSM fails in rear-side view factor in the design ranges of PV solar fields, where the error rate was found about 11%, this result is important in the case of bifacial PV solar systems. Also, the present work compared the solar irradiance calculated for a single surface with that incident on a PV solar field for wide range of sky conditions and latitudes. The obtained results ensure the accuracy of using the solar irradiance incident on a single surface data for low latitudes and for most sky conditions for PV rooftop solar systems as well as PV solar fields. While it has remarked a large error in the case of cloudy skies, where the error rate exceeded 17% in the case of aspect ratio equals to 1.5 and about 15.5% in the aspect ratio of 2.0.

Tinjauan Potensi dan Kebijakan Energi Surya di Indonesia

<p class="Abstract">The need for electrical energy in Indonesia is always increasing from year to year. The State Electricity Company in Indonesia (PLN), said that the national electricity demand in 2018 was 232,296 TWh and will increase 5.1% every year. However, energy sources are still dominated by coal and fossil fuels at 59.6%. The potential for renewable energy from solar energy is currently not widely used, even though the potential for renewable energy is very large, especially in Indonesia. This paper purpose to provide information about the potential of solar energy that can be utilized especially as a power plant and the policies and constraints of solar power plants in Indonesia. Indonesia has a fairly stable distribution of solar radiation throughout the year. The government has targeted the installed capacity of solar energy for power plant to reach 0.87 GW by 2025. Realization of Solar Power Plants (PLTS) in 2020 reached 0.15 GWp from the potential of solar energy in Indonesia of 207.8 GWp. Researchers, academics, and the government also continue to develop and innovate of solar energy technology in Indonesia and are expected to maximize the use of Renewable Energy. Some of the obstacles experienced are the high investment costs that must be incurred, causing the price of electricity produced from renewable energy to become uneconomical.</p>

Analysis, evaluation and integration of modular natural illumination system using a rectangular Fresnel lens for high performance

Daylighting using natural illumination system (NILS) is gaining popularity due to transition to the renewable and non-conventional energy resources. In the proposed work, optomechanical design, numerical analysis, experimentation and integration of a modular Fresnel lens for NILS to effectively harness the sunlight is discussed. The modular and integrated design delivers uniform light at the receiving area of the daylight transportation system. This modular Fresnel lens is a combination of linear Fresnel lenses designed to offer a moderate concentration ratio to avoid hot spots. The distribution of solar radiation on the focal plane/entry section of the plastic optical fibre bundle (daylight transportation system) is simulated using the ray-trace technique for a lens system with a concentration ratio of 81. The irradiance distributions at the focal plane were found uniform with a radiometric and photometric transmission efficiency of 72.45% and 85.96%, respectively, for the lens element. The overall photometric transmission efficiency of the system with 10 m long plastic/acrylic optical fibre cable was found as 40.97%.

Prediction of daily global solar radiation and air temperature using six machine learning algorithms; a case of 27 European countries

The prediction of global solar radiation in a region is of great importance as it provides investors and politicians with more detailed knowledge about the solar resource of that region, which can be very beneficial for large-scale solar energy development. In this sense, the main objective of this study is to predict the daily global solar radiation data of 27 cities (Brussels, Paris, Lisbon, Madrid…), located in 27 countries, which have mostly different solar radiation distributions in Europe. In this research, six different machine-learning algorithms (Linear model (LM), Decision Tree (DT), Support Vector Machine (SVM), Deep Learning (DL), Random Forest (RF) and Gradient Boosted Trees (GBT)) are used. In the training of these algorithms, daily air temperature(Ta), wind speed(Va), relative humidity(RH) and solar radiation of these cities are used. The data is supplied from the Meteonorm tool and cover the last years grouped in two periods (1960–1990; 2000–2019). To decide on the success of these algorithms, four different statistical metrics (Average Relative Error (ARE), Average absolute Error (AAE), Root Mean Squared Error (RMSE), and R2 (R-Squared)) are discussed in the study. In addition, the forecasting of air temperature and global solar radiation of these cities in 2050 and 2100 were made using three of the most recent Intergovernmental Panel on Climate Change (IPCC) scenarios (RCP2.6; RCP 4.5, and RCP 8.5). The results show that ARE, R,2 and RMSE values of all algorithms are ranging from 0.114 to 6.321, from 0.382 to 0.985, from 0.145 to 2.126 MJ/m2, respectively. By analysing all the algorithms, it is noticed that the Decision tree exhibited the worst result in terms of R,2 and RMSE metrics. Among the six prediction algorithms, the DL was recognized as the only algorithm that exceeded the t-critical value (The t-critical value is the cutoff between retaining or rejecting the null hypothesis). Globally, all the six machine learning algorithms used in this research can be applied to predict the daily global solar radiation data with good accuracy. Despite this, the SVM model is the best model among all the six models used. It is followed by the DL, LM, GB, RF and DT, respectively.

Application of luminous efficacies for daylight illuminance data generation in subtropical Hong Kong

PurposeDaylight plays a crucial role in the attainment of building energy savings. Harnessing daylight in building designs will require the need for daylight illuminance data. However, daylight illuminance data are scarce due to few measuring stations. Aside from being sparse, illuminance measuring stations can be expensive to set up, thus making the luminous efficacy model a better alternative. Hence, this study attempted to model horizontal luminous efficacies under the 15 Commission internationale de l'éclairage (CIE) standard skies. Therefrom, daylight illuminance was estimated from a proposed vertical luminous efficacy model.Design/methodology/approachMeasured solar irradiance, daylight illuminance and luminance distribution data were gathered from the local measuring station in Hong Kong. The luminance distribution data were used to classify the skies into the 15 CIE standard skies. Next, the solar irradiance and daylight data were used to derive the horizontal luminous efficacies under each standard sky. Furthermore, a vertical luminous efficacy model developed using the measured data was described, and this was used to predict vertical illuminance.FindingsIt was observed that Skies 1, 8 and 13 seem to be predominant in Hong Kong. Also, the result showed that constant luminous efficacies could be used for deriving illuminance data. Furthermore, horizontal luminous efficacy ranged from 40 to 190lm/W, indicating that daylight can provide sufficient visibility during working hours. The vertical luminous efficacy model proves to offer reasonable estimations of vertical illuminance data.Research limitations/implicationsFurther work needs to be done with more measured data to cover for spring seasons. The described model still needs to be fitted with different world climates to ascertain its universal applicability. The evaluations need to be done under obstructed sky conditions to cater for dense and clustered urban centres.Practical implicationsThe discussed luminous efficacy model could be used to derive illuminance data in the absence of measured daylight illuminance data, especially in the subtropical region. Also, the comparative advantage of daylight over artificial lighting was highlighted in this study.Originality/valueUnlike previous studies, this paper discusses the luminous efficacies of global, direct and diffuse components under the 15 CIE standard skies. Furthermore, the described luminous efficacy analysis provides an approach for deriving vertical and horizontal illuminance data. Such vertical data will be required for analysing building lighting requirements, sensible heat from electric lighting, and energy savings from daylighting controls. Also, the information on horizontal luminous efficacies will help evaluate solar roof and skylight designs.

Mixed Convection of Hybrid Nanofluid in Inclined Annulus Subjected to Solar Radiation

The problem investigated in this paper consists of the mixed convection of the Ag–ZnO (50%–50%)/water hybrid nanofluid in an inclined annular space; the upper part of the outer wall is exposed to solar radiation. Based on experimental data, new temperature-dependent expressions have been developed in this work to calculate dynamic viscosity and thermal conductivity. The governing equations were solved using the Fluent solver based on the finite volume method. Results show that Ag–ZnO/water has the highest Nu number compared to pure water and ZnO/water for all studied values of Ri number (0.3, 0.7, 1, 1.3, 1.7, 2) and volume concentration (0.01 and 0.02). However, the volume concentration effect on the friction coefficient is negligible for less than 0.15. Inhomogeneous solar radiation distribution at the wall has a very strong effect on the variation of the dynamic and thermal quantities. Temperature variations are more important above the horizontal diameter. In addition, the secondary flow has a direct impact on velocity variations. This effect results in the appearance of two symmetric vortices above the horizontal diameter. Vortices velocity increases with the Ri number increase. Considering tilt angle, obtained results show that its effect on dynamic quantities is more important.

An economically feasible optimization of photovoltaic provision using real electricity demand: A case study in New York city

Solar farming has been experiencing explosive development in recent years. However, developing solar farming in urban areas is challenged by the heterogeneous distribution of solar irradiation in spatial and degradation of photovoltaic (PV) efficiency that make the economic performance uncertain. To tackle this problem, this study develops a spatio-temporal analytic model and a techno-economic assessment model to optimize PV provision to ensure that a PV system can meet the electricity demand and obtain reasonable profit simultaneously. Specifically, based on the estimation of solar potential on three-dimensional urban envelopes, the study determines PV favorable locations that are quantitatively large and spatially concentrated. Then, PV capacities in two comparative architectures, i.e., self-reliance relying on own building surfaces and external-support seeking supports from external rooftops, are planned to meet real electricity demand. Furthermore, the PV capacity is optimized, constrained by a constant electricity rate without Feed-in Tariff, a decreasing PV efficiency, and an increasing cost for maintenance. A case study in New York City suggests that the optimized PV installation can significantly offset household electricity consumption. In addition, the estimated net profit is significant even in rigorous conditions, which is inspiring for promoting distributed solar harvesting and competing with the local electricity market. • Optimized PV capacity to meet real electricity demand and obtain net profit. • Developed spatio-temporal data analysis and spatial-aware techno-economic assessment. • The estimated net profit in New York City is significant even in strict conditions. • Inspiring for applying the method to promote distributed PV systems in global cities.

Solar parabolic dish collector for concentrated solar thermal systems: a review and recommendations.

Energy demand in the present scenario is rising to meet the increasing demands of energy usage. On the other hand, the use for renewable energy sources now becomes essential to mitigate the climate change as well as to reduce gradual depletion of fossil fuels. Among these renewable energy sources, solar energy particularly solar thermal systems have phenomenal scope in present and future research. In solar thermal systems, concentrators are used to extract the energy from solar irradiation and convert it into useful form. Among different types of solar concentrators, the parabolic dish solar concentrator is preferred as it has high efficiency, high power density, low maintenance, and potential for long durability. In this paper, a detailed review has been carried out on the design parameters like focal length, concentration ratio, and rim angle of the parabolic dish solar concentrator system for achieving higher overall efficiency. The effects of different geometrical shapes of receivers on the overall heat transfer rates are discussed in this paper. Conical shaped receiver is having high overall optical and thermal efficiency comparing with other shapes of receivers. This study also shows that how the thermal performance of the receiver gets enhanced by 10-13% using nanofluids in place of general heat transfer fluids. The paper highlights different models using ray-tracing method for estimation and evaluation of the solar irradiation distribution on the receiver surface. The empirical relations for the design of parabolic dish solar concentrator system are derived for estimating overall concentrator efficiency and heat available at the receiver are given in this review. From the literature, the thermal performance of the receiver affecting the overall performance of the system is observed. Thermal losses due to geometrical properties and ordination of the receiver are explained in the observation section.

Modelling and forecasting for solar irradiance from solarimetric station

This paper proposes two approaches for modeling solar irradiance time series. The first is an exploratory analysis and second is a periodic forecast model for solar irradiance data from solarimetric station in a country city of Bahia, Brazil. Two normality hypothesis tests were applied, Anderson-Darling and Shapiro-Wilk. The shape and symmetry of the data were also analyzed using boxplot and histograms to investigate the extreme points, as well as great asymmetry in the distribution of data at different times. Through adherence tests, the normal distribution of solar irradiance in most hours within the annual periodic is rejected. A study by season was carried out, which showed a different behavior in relation to the symmetry of the data, with autumn being the most uniform and spring being the most stochastic. Spring and summer presented better conditions for installation of photovoltaic plates, due to the high solar irradiance rates, and autumn and winter presented satisfactory solar irradiance to maintain this form of generation throughout the year.The second approach is a forecast to solar irradiance in photovoltaic generation systems. The importance of this forecast type is to favor the routine of planning, operation and maintenance of these types of systems, in addition to serving as a basis for feasibility studies and expansion of solar generation. Given a stochastic resource and the periodic behavior of solar irradiance data, a periodic autoregressive model was considered; the statistics were used by the maximum likelihood method, based on hourly measurements of irradiance over a period of one year.

Analysis of Influence Mechanism of Spatial Distribution of Incoming Solar Radiation Based on DEM

Analysis of Influence Mechanism of Spatial Distribution of Incoming Solar Radiation Based on DEM

Diverging water-saving potential across China's potato planting regions

China ranks the first in total planting area and production of potato (Solanum tuberosum L.) over the world. However, high potato yield depends on a large amount of irrigation that raises a series of environment problems. Assessing the water-saving potential across China’s potato planting regions is of importance for maintaining sustainable development of potato production. In this study, we firstly evaluated the potential yields, rainfed yields, and their gaps of potato across different potato planting regions, and then presented optimal agronomic management options (planting date, cultivar maturity, and irrigation schedule) by considering both yield and water use efficiency of potato under the limitation of available water resources with validated APSIM-Potato model. Along the distribution of growth period solar radiation, potential yield of potato was highest in the North Single planting region (NS), followed by the Central Double planting region (CD), Southwest Mixed planting region (SWM), and South Winter planting region (SW). However, rainfed yield of potato was highest in CD followed by NS, SW, and SWM along the distribution of the reproductive growth period precipitation. Under the limitation of available water resources, most potato planting regions should select middle−late maturing cultivars while optimal planting dates varied among regions with earlier planting in north China and later planting in south China compared with normal planting date. Based on the optimization of planting date, cultivar maturity, and irrigation schedule, there is a large water-saving potential in China’s potato planting regions. Average irrigation amount could be decreased by 66% in SW, 49% in SWM, 40% in NS, and 29% in CD, respectively, relative to irrigation quota. Our study suggests that optimizing planting date, cultivar maturity, and irrigation management could realize win-win of yield and water use efficiency and provide a scientific support for water-saving irrigation of potato production in China.