Modelling the diffuse fraction of global solar radiation on a horizontal surface

For various applications it is necessary to know not only global solar radiation values, but also the diffuse and beam components. Because often only global values are available, there have been several models developed to establish correlations between the diffuse fraction and various predictors. These typically include the clearness index, but also may include the solar angle, temperature and humidity. The clearness index is the proportion of extraterrestrial radiation reaching a location, where the extraterrestrial value used in the calculation varies with latitude and time of year. These correlations have been developed using data principally from latitudes greater than 40°, often using only data from a few locations and with few exceptions have not used solar altitude as a predictor. Generally the data consist of hourly integrated values. A model has been developed using hourly data from a weather station set up at Deakin University, Geelong. Another model has also been developed for 15 minute data values in order to ascertain if the smoothing generated by using hourly data makes a significant difference to overall results. The construction of such models has been investigated, enabling an extension to the research, inclusive of other stations, to be performed systematically. A final investigation was carried out, using data from other Australian locations, to explain some of the considerable scatter by adding apparent solar time as a predictor, which proved to be significantly better than solar altitude.

Solar energy use for energy savings in dairy processing plants

New Zealand is one of the world’s largest producers of dairy products and has a climate with high levels of solar radiation; however, the use of solar energy in the dairy processing industry has received limited attention. An examination of historical records found that the annual peak in New Zealand milk production and processing occurs at a time when solar radiation levels are increasing markedly. An F-Chart analysis was used to simulate the performance of large-area arrays of solar collectors and to determine their suitability for heating and cooling in a dairy processing environment. For the study four types of solar collectors were analysed: glazed flat plates, evacuated tubes, evacuated tubes with CPC reflectors and a building-integrated solar collector under development at the University of Waikato (UoW). It was found that of these echnologies, both flat plate and evacuated tubes with CPC reflectors could make useful heating and cooling contributions. Furthermore, the solar fraction was determined mainly by the collector area to storage volume ratio. Finally, it was found that the UoW building-integrated solar collector could make a significant contribution to energy use in dairies and may be an attractive future technology for the industry.

Designing a low cost solar collector system for process industry applications

New Zealand is a large producer and processor of primary products and has a climate with high levels of solar radiation. However, the use of solar energy for heating and cooling in the processing industries has received limited attention.
For this study, the design of a low cost solar collector is analysed and discussed. Furthermore, the methods for integrating the collector into water heating and cooling systems in a hypothetical processing environment are examined. An F-Chart analysis is used to simulate the performance of large-area arrays of the solar collector and to determine its potential contribution to heating and cooling loads.
The study shows that for a storage-based system, the contribution of solar energy is determined mainly by the collector area to storage volume ratio. It is suggested that this low cost collector could make a significant contribution to energy use in processing plants and may be an attractive future technology.

Development of a mathematical model for solar module in photovoltaic systems

A mathematical model of a solar module is presented. This model takes into account solar model temperature and solar radiation. The experimental data of a solar module under natural environment condition (NEC) have been obtained to determine the model parameters. The experimental results are compared with those calculated by using a mathematical model. It shows that the mathematical model accurately simulates the current-voltage characteristics of the solar module under the NEC and therefore is suitable for photovoltaic system design and performance analysis.

A simple-to-use calculator for determining the total solar heat gain of a glazing system

Architects and designers could readily use a quick and easy tool to determine the solar heat gains of their selected glazing systems for particular orientations, tilts and climate data. Speedy results under variable solar angles and degree of irradiance would be welcomed by most. Furthermore, a newly proposed program should utilise the outputs of existing glazing tools and their standard information, such as the use of U-values and Solar Heat Gain Coefficients (SHGC’s) as generated for numerous glazing configurations by the well-known program WINDOW 6.0 (LBNL, 2001). The results of this tool provide interior glass surface temperature and transmitted solar radiation which link into comfort analysis inputs required by the ASHRAE Thermal Comfort Tool –V2 (ASHRAE, 2011). This tool is a simple-to-use calculator providing the total solar heat gain of a glazing system exposed to various angles of solar incidence. Given basic climate (solar) data, as well as the orientation of the glazing under consideration the solar heat gain can be calculated. The calculation incorporates the Solar Heat Gain Coefficient function produced for the glazing system under various angles of solar incidence WINDOW 6.0 (LBNL, 2001). The significance of this work rests in providing an orientation-based heat transfer calculator through an easy-to-use tool (using Microsoft EXCEL) for user inputs of climate and Solar Heat Gain Coefficient (WINDOW-6) data. We address the factors to be considered such as solar position and the incident angles to the horizontal and the window surface, and the fact that the solar heat gain coefficient is a function of the angle of incidence. We also discuss the effect of the diffuse components of radiation from the sky and those from ground surface reflection, which require refinement of the calculation methods. The calculator is implemented in an Excel workbook allowing the user to input a dataset and immediately produce the resulting solar gain. We compare this calculated total solar heat gain with measurements from a test facility described elsewhere in this conference (Luther et.al., 2012).

Hybrid prediction method for solar power using different computational intelligence algorithms

Computational Intelligence (CI) holds the key to the development of smart grid to overcome the challenges of planning and optimization through accurate prediction of Renewable Energy Sources (RES). This paper presents an architectural framework for the construction of hybrid intelligent predictor for solar power. This research investigates the applicabil- ity of heterogeneous regression algorithms for 6 hour ahead solar power availability forecasting using historical data from Rockhampton, Australia. Real life solar radiation data is collected across six years with hourly resolution from 2005 to 2010. We observe that the hybrid prediction method is suitable for a reliable smart grid energy management. Prediction reliability of the proposed hybrid prediction method is carried out in terms of prediction error performance based on statistical and graphical methods. The experimental results show that the proposed hybrid method achieved acceptable prediction accuracy. This potential hybrid model is applicable as a local predictor for any proposed hybrid method in real life application for 6 hours in advance prediction to ensure constant solar power supply in the smart grid operation.

A pixel-based approach to estimation of solar energy potential on building roofs

Precise estimation of solar energy on building roofs plays a critical role in sustainable development and renewable energy consumption of high-density human habitats. Conventional solar radiation models based on costly Light Detection and Ranging (LiDAR) data are only adequate for existing buildings, not for future construction areas. In this paper, a pixel-based methodology is constructed for estimating solar energy potential over roofs. Buildings with flat roofs in a newly planned construction area are chosen as a case study. The solar radiation at a certain cell is mathematically formulated in the pixel unit, and its yields over a certain time period are calculated by considering multiple instantaneous solar irradiances and are visually presented by image processing. Significant spatial and temporal variations in solar radiation are measured. Within the study area, the maximum and minimum annual radiation yields are estimated at 4717.72 MJ/m2/year and 342.58 MJ/m2/year respectively. Radiation contour lines are then mapped for outlining installation ranges of various solar devices. For each apartment building, around 20% of roof areas can obtain 4500 MJ/m2/year or more solar radiation yields. This study will benefit energy investors and urban planners in accurately predicting solar radiation potential and identifying regions with high radiation over building roofs. The results can be utilised in government policies and urban planning to raise awareness of the use of renewable energy sources.

Landscape characteristics associated with species richness and occurrence of small native mammals inhabiting a coastal heathland: a spatial modelling approach

In the coastal region of south-western Victoria, Australia, populations of native small mammal species are restricted to patches of suitable habitat in a highly fragmented landscape. The size and spatial arrangement of these patches is likely to influence both the occupancy and richness of species at a location. Geographic Information System (GIS)-based habitat models of the species richness of native small mammals, and individual species  occurrences, were developed to produce maps displaying the spatial  configuration of suitable habitat. Models were generated using either generalised linear Poisson regression (for species richness) or logistic regression (for species occurrences) with species richness or  presence/absence as the dependent variable and landscape variables, extracted from both GIS data layers and multi-spectral digital imagery, as the predictor variables. A multi-model inference approach based on the Akaike Information Criterion was used and the resulting model was applied in a GIS framework to extrapolate predicted richness/likelihood of occurrence across the entire area of the study. A negative association between species  richness and elevation, habitat complexity and sun index indicated that richness within the study area decreases with increasing altitude, vertical vegetation structure and exposure to solar radiation. Landform  characteristics were important (to varying degrees) in determining habitat occupancy for all of the species examined, while the influence of habitat complexity was important for only one of the species. Performance of all but one of the models generated using presence/absence data was high, as indicated by the area under the curve of a receiver-operating characteristic plot. The effective conservation of the small mammal species in the area of concern is likely to depend on management actions that promote the protection of the critical habitats identified in the models.

Runoff absorption potential of roofing materials

The main objectives of this work are to establish a relationship between solar radiation and equivalent temperatures for the radiation heat source (oven) to be used in the laboratory and to determine the impact of solar radiation on the absorption and evaporation potential of roofing tiles (glazed and unglazed). Based on the results obtained, it is justifiable to conclude that solar radiation do affect the evaporation and absorption potential of the glazed and unglazed tiles. There is a trend of decrease in both the absorption and evaporation potential of both tiles when exposed to decreasing solar radiation. The evaporation potential of the roof tiles is much higher than its absorption potential. This is clearly displayed in both types of tiles.

Urban heat island and its impact on building energy consumption

Urban areas tend to have higher air temperatures than their surroundings as a result of man-made aiterations. This phenomenon is known as the urban heat island (UHI) effect. UHI is considered to he one of the major problems encountered by the human race this century. Solar radiation that is absorbed during the day by buildings is re~emitted after sunset creating high temperatures in urban areas. Also, anthropogenic heat sources such as air conditioners and road traffic add to the rise in temperatures, A number of
studies have indicated that UHI has a significant effect on the energy use of buildings. In mid- and low-latitude cities, heat islands contribute to urban dwellers' summer discomfort and significantly higher air-conditioning loads. This chapter summarizes and reviews the latest research methodologies and findings about the effect of increased temperatures on the energy consumption of buildings. The latest developments in the heat island mitigation strategies are remarkable, However, more attention needs to be
given to the implementation and testing of these strategies in full-scale buildings.

Building surfaces and their effect on the urban thermal environment

Use of high reflectance surfaces reduces the amount of solar radiation absorbed through building envelopes and urban structures and thus keeping their surfaces cooler. The cooling energy savings by using high reflectance surfaces have been well documented. Higher surface temperatures add to increasing the ambient temperature as convection intensity is higher. Such temperature increase has significant impacts on the air conditioning energy utilization in hot climates. This study makes use of numerical simulations to analyze the effect of commonly used building materials on the air temperature. A part of the existing CBD (Central Business District) area of Singapore was selected for the study. A series of Computational Fluid Dynamics (CFD) simulations have been carried out using the software CFX-5.6. It was found that at low wind speeds, the effect of materials on the air temperature was significant and the temperature at the middle of a narrow canyon increased up to 2.5[degrees]C with the facade material having lower reflectance.

Effect of materials on the urban thermal environment a CFD simulation approach

Use of high albedo materials reduces the amount of solar radiation absorbed through building envelops and urban structures and thus keeping their surfaces cooler. The cooling energy savings by using high albedo materials have been well documented. Higher surface temperatures add to increasing the ambient temperature as convection intensity is higher. Such temperature increase has significant impacts on the air conditioning energy utilization in hot climates. This study makes use of a parametric approach by varying the temperature of building facades to represent commonly used materials and hence analyzing its effect on the air temperature through a series of CFD (Computational Fluid Dynamics) simulations. A part of the existing CBD (Central Business District) area of Singapore was selected for the study. Series of CFD simulations have been carried out using the software CFX-5.6. Wind tunnel experiments were also conducted for validation. It was found that at low wind speeds, the effect of materials on the air temperature was significant and the temperature at the middle of a narrow canyon increased up to 2.52°C with the façade material having lowest albedo.

Simultaneous presentation of measured and calculated environmental results

Continuous measurement of internal and external environmental parameters is critical to our understanding of how buildings perform. Yet, the quantity and variety of time-series data can be quite overwhelming as well as onerous to decipher and present. In addition to this, is the fact that several of the collected data are useless in their raw format unless processed through algorithms to obtain identifiable and meaningful results.
These circumstances challenge the conventional way we present accumulated data and their processed outputs in order to get a better understanding of how and why the environmental performance occurred. It would be ideal if all of the collected and processed data could be presented in a simultaneous, yet, useful format. It is exactly the intention of this paper to suggest and present such a process as well as its format.
An example case study is provided where several parameters (air velocity, mean radiant temperature, humidity and air temperature) are measured periodically to calculate a time-series of internal comfort performance. However, external conditions of solar radiation and solar position as well as air temperature drive the interior building surface temperatures and help to explain the end result of internal comfort.
A program has been written to present the various sets of data graphically, in an integrated manner, animated as a function of time. The animation shows solar position, a cursor scanning weather data, the changing infra-red image and a representation of the resulting internal comfort performance throughout the
monitored period.