Estimation of Global Solar Radiation on Horizontal Surface in Kano, Nigeria Using Air Temperature Amplitude.

The need for the renewable source of energy is inevitable due to uneven distribution of the fossil fuel, its transportation expenses, political and military invasions to control and manipulate the possession, carbon emission, highly depleted and non-renewable nature. Solar energy studies of a given geographical location require inputs such as solar radiation profile for the performance estimation and development of various solar technologies. Advance solar radiation measuring equipment such as pyranometer and pyrheliometer are normally installed at the selected locations to collect, measure and output data. However, many developing nations could not afford the cost and maintenance of such equipment and hence the need for modeling the global solar radiation using different estimating methods with appropriate daily or monthly climatic data from meteorological stations. The main objective of this work is to calibrate, validate and evaluate four air temperature-based models namely the Hargreavees model, Allen model, Bristow-Campbell model and the Samani model to estimate global solar radiation potentialities at the Kano Airport, Nigeria using air temperature as the sole parameter as the input because of its easiness in availability and accessibility and can be used for any location in Nigeria without the sunshine hour parameter data. Statistical performance analysis of each model was evaluated, the performance parameter values vary from one model to another Samani model has the best fit amongst the models, and is therefore recommended for global solar radiation estimation for the location under consideration

Wind and solar radiation potential assessment in Kano, Nigeria using Weibull and Samani models

clean, source free, environmentally friendly and renewable source of energy such as wind and solar energy can be used for providing sustainable power supply to remedy an epileptic and unreliable power supply systems. For decades, electric power supply situation in Kano, Nigeria has been a major source of serious concern. The epileptic power supply has hindered the socio-economic growth industrialization and, subsequently, increase air pollution due to individual stand-alone diesel generators. Various government incentives and policies have little or no effect to improve the availability and reliability of the electric power. The aviation industries especially the Navigation and communication equipment required, apart from availability, a reliable power sources because of their sensitivity to reliable and safe Aircraft navigation. The need for an alternate renewable energy system (RES) of power supply away from the National grid and diesel generator is inevitable at Kano. This paper proposes an assessment of wind and solar energy potentialities at Kano in Nigeria using Weibull distribution methods and the Samani model to determine the wind features and estimate global solar radiation potentials respectively for power supply generation. A six years (2009-2014) monthly mean wind speed data measured at 10 m height was collected and extrapolated to 50 m height level for statistical analysis, while 22 years monthly solar radiation, temperature amplitude and relative humidity of the location were obtained from NASA web to calibrate, validate and evaluate the Samani model, ten years (2003-2012) maximum and minimum temperature were then used to predict the global solar radiation on horizontal surface of the location. The minimum Weibull average wind speed was found to be 8.60 m/s and the maximum average wind speed was 11.24 m/s while the minimum power density was 440.03 W/m2 and the highest was 947.26 W/m2 at the 10 m height level. The lowest average global solar radiation on the horizontal surface was 17.96 MJ/m2/d and highest average global solar radiation on the horizontal surface was 26.38 MJ/m2/d. The site has been found to have great potentials for wind and solar utility power generation capacity

Monte-carlo based robust analytical method for optimal sizing and reliability of hybrid renewable energy system

The need for a more reliable power from the utility grid and ever-increasing concerns on Greenhouse Gas (GHG) emission effect has globally promoting Renewable Energy Sources (RES). RES is increasingly being adopted in complementing traditional fossil fuels in the energy power supplies. Hybrid Renewable Energy (HRE) systems incorporating wind and solar sources offers lower costs, higher reliability, reduced investment risks, fuel diversification etc. However, wind speed and solar radiation are characterized by their limitations of inherent intermittency and variability. These limitations have led to the concept of optimal sizing and reliability assessments to maintain a balance between generated power and the system loads. Nonetheless, RES reliability assessment studies are site-specific, but existing studies are inexhaustive given the capacity availability and reliability requirements of various sites as well as their performance evaluations. This thesis presents the optimal sizing and reliability assessment of a hybrid solar and wind energy systems for a selected location. Weibull statistical method and air temperature amplitude based statistical models are adopted for wind and solar energy potential assessments of the selected site. The Weibull parameters were estimated using standard deviation method for wind energy potential assessment. Moreover, the air temperature based models of Hargreaves and Samani; Allen; Samani; and Bristow-Campbell models were used for solar energy potential assessment. Simulation of the uncertainty in the wind speed and its probability distribution is performed by using Auto-Regressive Moving Average (ARMA) model to improve wind speed normal distribution. In this approach, the best normal distribution for the simulated wind speed for the reliability analysis is chosen. To improve the performance of the Photovoltaic (PV) module, a single diode six parameter model is developed. First, the P-V and I-V curves were used to generate the required constraints. These constraints were then used to obtain the solution vector of the six parameters using MATLAB and System Advisor Model (SAM). Also, the system’s capacity availability and reliability was assessed using Monte Carlo (MC) simulation. Finally, the result of the MC reliability assessment is later served as Loss of Power Supply Probability (LPSP) constraints to Artificial Bee Colony (ABC) algorithm for the system’s optimal sizing and enhanced reliability assessment. Results from the study show that both wind and solar energy potential of the selected site is high and can generate power at utility level. The ARMA simulated wind speed shows an improvement of 21.8% in standard deviation over the measured wind speed. The adoption of the negative components in the ARMA model transformation resulted in least error of 23.34% in the final wind simulation. Results obtained based on the six parameter solution vector gives improved performance of the PV module. Using the developed MC technique, capacity availability of 100% and LPSP of zero is achieved. The developed ABC algorithm resulted in system reliability improvement of 98.92% when the MC results are constraint into the ABC for the optimal sizing. Various results were validated at appropriate sections and finally, the optimal sizing results of PV/battery RES power system is found to give the best reliability. Such a system has great reliability and can be implemented in facilities requiring constant power supplies such as critical infrastructure