T.R. Ayodele

Optimum selection of photovoltaic modules using probabilistic approach based on capacity factor estimation

ABSTRACT In this paper, the optimum selection of photovoltaic module using probabilistic techniques based on capacity factor estimation is proposed. The approach entails modelling the solar irradiance characteristics of the site by fitting probability distributions to the irradiance data for different hours of a typical day in each month of the year. The parameters of the probability distribution that best fits the solar irradiance data for a particular hour are thereafter used to estimate the capacity factor of different designs of PV modules. The module with the highest average capacity factor across all the months is identified as the best suited module for the given site. The proposed technique is investigated using 5 years data (2008–2012) of solar irradiance and temperature. The choice of the year of observation of the data was due to accuracy and completeness of the data for the period. The data sheets of 10 commercially available PV modules were also obtained from different manufacturers. The proposed method is simple, easy to use, and can be applied to any solar regimes around the world.

Temperature based model for estimating the daily average global solar irradiation of Ibadan, Nigeria

This paper presents the temperature based models for predicting the daily average global solar radiation of Ibadan. The data used in developing the models consist of daily average global solar radiation, minimum and maximum daily average temperature collected over a period of 9 years at International Institute of Tropical Agriculture (IITA) located in Ibadan. Different variations of temperature model are derived and compared. The suitability of the models is ascertained using standard statistical tests: Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), and Correlation Coefficient (R). One of the key results shows that a quadratic temperature model present the overall best model for predicting the global solar radiation of Ibadan with MBE of 1.86 MJm-2day-1, RMSE of 2.7, MAPE of 9.34% and R of 0.68.

On the adaptation of South Africa experience to combine solar energy and Smart Grid in Namibia

The challenging and vitiated situation of electricity in Namibia is addressed in this paper. The country is importing about 53% of its electricity from the neighbouring countries such as South Africa, Botswana, Zimbabwe and Zambia. This has caused high price of electricity in the country and by extension imposes financial burden on the citizen. In order to alleviate this problem and reduce high dependence on imported electrical power, several solar energy pilot projects have been implemented in the country. On the other hand South Africa is among the countries with experience in Smart Grids. Based on the experience of a residential house with a monthly load greater than 500 kWh using Smart Metering and a solar Photovoltaic panel connected to the grid in South Africa, this paper shows that this experience is feasible and can be successfully adapted in Namibia.

On the most suitable sites for wind farm development in Nigeria

The increasing demand for energy and the need for clean and affordable energy in Nigeria have necessitated the need for renewable energy resource assessment and subsequent determination of suitable sites within the country. One of the promising renewable energy resources with good potentials of meeting the energy requirements is wind. One of the main challenges of wind power development in Nigeria is lack of scientific data for policy formulation and decision making that will aid the development of wind power utilization. The data presented in this article were obtained with proper evaluation of the wind resource while taking into consideration environmental, social, and economic factors. The information from the data could be useful for taking optimal site selection decision by the policy makers, government, engineers etc. This will ensure optimal investment and return on investment for wind farm developers.

Dynamic performance of wind-driven self-excited reluctance generator under varying wind speed and load

This paper presents the dynamic performance of a wind-driven self-excited reluctance generator (WDSERG) to obtain a desired output voltage under a stochastic wind speed variation and changing load. The dynamic model of SERG is developed and utilised to simulate the WDSERG in the MATLAB-Simulink environment. A stochastic wind speed profile is generated using weibull distribution. The excitation capacitance required to maintain the output voltage at a desired level is computed for each wind speed and load. The obtained capacitance value is utilised to provide the required excitation for the self-excited reluctance generator (SERG). Different scenarios of load conditions are considered and an optimal capacitance value is determined and selected for each load cases. The results show that in spite of the variation in wind speed or load, a desired output voltage level within predetermined limits is obtained. This illustrates that variable excitation capacitance can be utilised to follow the wind speed in order to produce a desired output voltage level under any given operating conditions of wind speed and terminal load, within the steady state limits of the SERG. Therefore, this can offer an effective and low-cost solution for output voltage control of WDSERG, particularly in remote locations.