Statistical analysis of wind speed for electrical power generation in some selected sites in northern Nigeria

In this paper, statistical analysis is carried out to determine the accurate frequency distribution that fits wind speed data. The frequency distributions used include Weibull, Rayleigh and Gamma distribution functions. The performances of the probability distributions are based on the error evaluations between the predicted and the theoretical wind power densities of the site. The Results show that Weibull distribution modelled the wind speed better compared to other distribution functions. According to the European Wind Energy Association, most of the sites are suitable for the generation of electrical energy. Also, the results have shown that Jos, Kano and Minna fall in class 4 and therefore suitable for both off grid and grid connected modes. In addition, the effects of c and k parameters on the probability distribution functions have been presented.Keywords: Wind speed - probability - density function – wind energy conversion system- statistical analyse

Replacement Model for Street Lighting Systems

Replacing failed bulbs of streetlights in a location can be very tasking and expensive if the optimal time for replacement is not determined. In this paper, a model has been developed that helps to establish the optimal time for the replacement of streetlight bulbs. Burnt-out bulbs are replaced individually when they fail, and group replacement is carried out on all bulbs after a specified time. The costs for both individual replacement and group replacement are determined. The developed model was applied to locally sourced data from a field survey of a streetlight installation at the University of Ilorin, Ilorin, North-central Nigeria. The model gave the optimum replacement time of burnt-out bulbs as the eighteenth week when applied to the data used in this work. The optimum replacement time will be dependent on the dataset used. This makes the developed model useful in establishing the optimal replacement time of any stochastically failing items that are in large quantities. The model will help to reduce maintenance costs for facility managers

Interference management techniques in cellular networks: A review

In modern times, communications technologies serve as the drivers of social, economic and political developments. But, interference in the communication networks comes as undesirable nuisance. In this work, techniques employed in the management of interference encountered in cellular networks are reviewed. Propositions by different Authors include intermodulation solutions, frequency planning methods, genetic algorithms, Simulated annealing models, ordering heuristic, ant colony and multi-agent optimization, artificial neural networks model, evolutionary strategy approach (EAs), and hybrid EAs. While many techniques work more effectively in some areas of operations, others show strong performances in other areas. For instance, the technique of weak cooperation among base station proposed by some authors offer significant network performance when employed as it provides framework for optimal performances of adjacent base stations under some performance objectives. Also evolutionary strategy approach employed by some other authors shows proficiency in the management of channels allocation aimed at minimizing the problems of interference, which can manifest as call blocking or dropping. Furthermore, some authors designed hybrid EAs integrating local search and constraint programming into evolutionary operators, which was shown to speed up performance. Despite all efforts, challenges of interference still abound in communication networks. Among several techniques available to address interference networks, EAs has been given wider applications and the results show good performance of this technique. Meanwhile, genetic algorithm is also efficient where applied, but to reduce interference to the minimum in the current and future mobile communication networks, this review proposes synchronization of reduction techniques, where traffic-driven factors are considered