In this paper the impact of adjusting the optimal tilt angle of solar photovoltaic (PV) modules on monthly bases was studied and compared to that of the annually-fixed optimal tilt angle. PVSyst software was used to determine the optimal tilt angle for each month for a given case study site in Imo state in Nigeria. Mathematical models for computing the required PV array power to meet the daily energy demand of 100 kWh were presented. Addition parameters considered in the study were the PV array number of modules as well as PV array area and cost. For the case study 100 kWh daily energy demand, the selected PV module had a peak power rating of 100W, with a unit cost of N 18,000 and with dimensions that gave an area of 0.65945m^2. The results showed that there is about 4 % (annual average) reduction in the required PV array power when the monthly adjustment of the optimal tilt angle is used. December had the highest percentage reduction in the required PV array power. The reduction in the PV array power resulted in the corresponding reduction in the number of PV modules needed to provide the required power, as well as a reduction in PV array area and cost.
Contribution/Originality:This study is one of the very few studies which have investigated the impact of the optimal tilt angle on the solar photovoltaic array size and cost for the solar power system in Imo state, Nigeria.
Abstract:In this paper, evaluation of moving average model and autoregressive moving average model (ARMA) for prediction of industrial electricity consumption in Nigeria is presented. Industrial electricity consumption data obtained from Central Bank of Nigeria (CBN) Statistical Bulletin for the year 1979-2014 is used to determine the model parameters and prediction performance in terms of Root Mean Square Error (RMSE) and Coefficient of determination r 2 values. The results show that the Autoregressive Moving Average (ARMA) model with coefficient of determination value of 66.0% and RMSE value of 68.628 gives better prediction performance than the Moving Average with coefficient of determination value of 42.6% and value of 84.749. However, coefficient of determination value of 66% is not particularly adequate for acceptable prediction accuracy. In that case, for better prediction accuracy for the industrial electricity consumption in Nigeria, other models may need to be examined apart from the two models considered in this paper.
Contribution/Originality: This study is one of very few studies which have investigated the effect of variations in refractivity gradient on line of sight percentage clearance and single knife edge diffraction loss. The ideas presented can easily be used to study the effect of variations in atmospheric parameters on wireless signal quality.
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