Technical Consideration of the Effect of Solar Radiation on Nigeria
Chapter One
AIMS AND OBJECTIVES OF STUDY
The main aim of the study is to examine technical consideration of the effect of solar radiation. Other specific objectives of the study include;
- to determine the extent to which technical radiation affects solar radiation in Nigeria.
- to determine the impact of technical consideration on solar radiation in Nigeria.
- to determine the factors affecting technical consideration on solar radiation in Nigeria.
- to proffer possible solutions to the problems.
CHAPTER TWO
LITERATURE REVIEW
Introduction
Almost all the renewable energy sources originate entirely from the sun. The sun’s rays that reach the outer atmosphere are subjected to absorption, scattering, reflection and transmission processes through the atmosphere, before reaching the earth’s surface.
Solar radiation data at ground level are important for a wide range of applications in meteorology, engineering, agricultural sciences, particularly for soil physics, agricultural hydrology, crop modeling and estimation of crop evapo-transpiration, as well as in the health sector, in research and in many fields of natural sciences. A few examples showing the diversity of applications may include: architecture and building design (e.g. air conditioning and cooling systems); solar heating system design and use; solar power generation and solar powered car races; weather and climate prediction models; evaporation and irrigation; calculation of water requirements for crops; monitoring plant growth and disease control and skin-cancer research.
Satellite Observation Model
The accurate knowledge of solar radiation at the earth’s surface is of great interest in solar energy, meteorology, and many climatic applications. Ground solar irradiance data is the most important data required for characterizing the solar resource of a given site but the spatial density of such measuring meteorological stations is far low because of economic reasons. In this context, satellite-derived solar radiation estimation has become a valuable tool for quantifying the solar irradiance at ground level for a large area. Thus derived hourly values have proven to be at least as good as the accuracy of interpolation from ground stations at a distance of 25 km (Zelenka et al.[92]).
Several algorithms and models have been developed during the last two decades for estimating the solar irradiance at the earth surface from satellite images (Gautier et al.[93]; Tarpley[94]; Hay[95]). All of them can be generally grouped into physical and pure empirical or statistical models (Noia et al.[96]). Statistical models are simpler, since they do not need extensive and precise information on the composition of the atmosphere, and rely on simple statistical regression between satellite information and solar ground measurements. On the contrary, the physical models require input of the atmospheric parameters that model the solar radiation attenuation through the earth’s atmosphere. On the other hand, the statistical approach needs ground solar data and such models suffer from lack of generality.
Satellites observations of the earth can be grouped, according to its orbit. In polar orbiting satellites, with an orbit of about 800 km have high spatial resolution but a limited temporal coverage. The geostationary satellites, orbiting at about 36000 km, can offer a temporal resolution of up to 15 minutes and a spatial resolution of up to 1 km. Most of the methods (Shafiqur Rehman and Saleem
ANN Model
An Artificial Neural Network (ANN) is an interconnected structure of simple processing units. The functionality of ANN can graphically be shown to resemble that of the biological processing elements called the neurons. Neurons are organized in such a way that the network structure adapts itself to the problem being considered. The processing capabilities of this artificial network assembly are determined by the strength (weightage factor) of the connections between the processing units.
Haykin[98] states that: “A neural network is a massively parallel distributed processor that has a natural propensity for storing experiential knowledge and making it available for use. It resembles the brain in two respects:
- Knowledge is acquired by the network through a learning process;
- Interconnection strengths between neurons, known as synaptic weights or weights, are used to store knowledge”.
During the last two decades, ANN has proven to be excellent tools for research, as they are able to handle non-linear interrelations (non-linear function approximation), separate data (data classification), locate hidden relations in data groups (clustering) or model natural systems (simulation). Naturally, ANN found a fertile ground in solar radiation research. A detailed survey about the applicability of ANN to various Solar Radiation topics is given below.
Mohandes et al.[59] performed an investigation for modeling monthly mean daily values of global solar radiation on horizontal surfaces; they adopted a back-propagation algorithm for training several multi-layer feed- forward neural networks. Data from 41 meteorological stations in Saudi Arabia were employed in this research: 31 stations were used for training the neural network models; the remaining 10 stations were used for testing the models. The input nodes of the neural networks are: latitude (in degrees), longitude (in degrees), altitude (in meters) and sunshine duration.
CHAPTER THREE
RESEARCH METHODOLOGY
Data acquisition
Monthly data on solar radiation including other weather variables [air temperature (Ta), relative humidity (Rh), global radiation (Rs), sunshine hours (SS), and precipitation (P)] for three decades (1975-2006) were collected from the archives of the Nigerian Meteorology Agency positioned at over forty stations across Nigeria. The sites coverage for this study is comparatively large, fourteen stations were involved in this study in view of the dearth of data spanning from the coastal stations to the arid region in Nigeria
Method and Site description
The monthly data were averaged into annual time scale for the purpose of this study. The data collected were subjected to quality control check so as to ensure that all spurious data including omissions were diligently resolved before applying them for data analysis. The trend analysis for each variable was investigated using linear regression techniques. The significance of the each observed trend was evaluated using F-Test4,8.
The basic empirical equation used in this study was based on the fundamental Angstrom model27 defined as the linear relationship between the ratios of average daily global solar radiation and maximum possible sunshine duration to the corresponding value on a completely clear day and ratio of average daily sunshine duration to the maximum possible sunshine duration. Prescott28 put the equation in a more suitable form by replacing the average global radiation on a clear day with the extraterrestrial solar radiation. This is mathematically expressed as:
CHAPTER FOUR
RESULTS AND DISCUSSION
Trend analysis of the allied parameters
The method of Mann-Kendal tau_b was used to determine the trend analysis of the global solar radiation and all allied parameters (sunshine hours, relative humidity, air temperature and precipitation) on annual time scale (1975-2006) for all the stations except Akure, where time scale (1975-2002) was considered; while the significance of both the downward and upward trend was determined by using F-test and both results were presented in Table 2. For solar global radiation, 29% of all the stations exhibited decreasing trend, out of which two stations passed the F-test at 1% significant level while the upward trend at the rest two stations failed the F-test and hence, not significant. The technical consideration of the solar global radiation at the rest 71% showed increasing trend. For the increasing trend, five stations passed the F-test at 1% significant level while the upward trend in four stations was not significant as the observed trend failed F-test. The most significant upward trend is observed both for Benin and Jos.
CHAPTER FIVE
CONCLUSION AND RECOMMENDATION
Conclusion
The technical consideration of the effect of solar radiation alongside some allied meteorological variables was investigated in this study. It was found that most of the stations under this study exhibited an upward trend in the annual global solar radiation and about 50% of this passed F-test at 1% significant level. An upward annual technical consideration of sunshine hours was observed at most stations except at one station where a downward trend that passed the F-test at 1% significant level was noted. However, the observed positive technical consideration of sunshine hours failed the F-test at 2.5% significant test. The annual precipitation showed an insignificant upward trend at most stations across Nigeria during the period of study. Furthermore, the annual trend analysis for relative humidity indicated a little less than 50% of the coverage experienced negative trend in RH while the rest, larger per cent, exhibited positive trend but none was significant. Finally, the trend analysis also confirmed that larger part of the country experienced a significant upward trend in temperature, which may be assumed responsible for the upward trend in precipitation observed in most part of the country. The study, further, establishes good relationship between an increasing global solar radiation and increasing temperature. A signature of climate change is detected with both the upward increase in temperature and precipitation.
Recommendations
In this study, Angstrom model of the first order on annual scale was carried out and a weak empirical linear relationship was noted between global solar radiation and sunshine hour at most stations; this was found to be due to the short duration data which were used4. However, when the data for all the stations were combined together to generate an annual global radiation with the parameters ‘a’ and ‘b’ of the Angstrom model adjusted and expressed as functions of the longitude, latitude, and the elevation or/and precipitation, relative humidity and temperature, a tremendous improvement was obtained between Rs and SS.
In this study, the performance of each set of equations in terms of contributing effect of precipitation and relative humidity was also investigated. It was observed that equations involving relative humidity have better potential GSR prediction than other empirical equations involving precipitation as indicated by their respective NSE values and other statistical indicators. This suggests that both climatological and geographical factors should be considered significant in the development of any scheme for the simulation of global solar radiation. This modification on the Angstrom-Prescott model have brought a significant improvement on the accuracy of the simulated results as can be observed in this study (Table 4 and Fig. 3)
In conclusion, Eq. (27) when compared with other schemes, had been found to have the highest NSE value of 0.573, lowest standard deviation of 0.13978, and highest correlation coefficient of 0.75 and a low SEE of 0.0068. Hence, it is recommended for the simulation of annual global solar radiation in Nigeria
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