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Redundancies in Hydro Reservoir Elements and their Contributions to Electric Power Generation in the Jebba Hydel Power Reservoir, Nigeria
Abstract
Despite the over 100 years of electricity in Nigeria, power generation is still largely lagging behind its demand as all the hydro dams are still performing below installed capacities. The purpose of this paper is to expose the rates of redundancies in the contributions of reservoir elements to power generation in Jebba dam and to guide dam operators in designing reservoir rules. The data used in this study comprises of monthly power generated in mg/watts and monthly characteristics of 10 reservoir elements. These information were collected from 1990-1998. These data were obtained from the Hydrology Department of Power Holding Company of Nigeria, Jebba Business Distinct; Jebba North, Nigeria. The data were interpreted with statistical averages, simple percentages, graphs, while factormultiple regression and factor-stepwise regression were used as
reduce-rank models to estimate rates of redundancies on monthly basis. Altogether, 24 mathematical operations were carried out; which is a breakdown of 2 factor regression modelling operations per month (one each for factor-multiple and factor-stepwise regression). The percentages of explanation of factor analysis equations range from 79.2% in April to 92.7% in December, with percentages of redundancies ranging from 7.70% in December to 20.8% in April. The percentages of explanation of multiple regression also vary from 13.4% in April to 98.5% in February, while its monthly percentages of explanations outside the multiple regression equations range between 1.50% in February to 86.6% in April. Also, the percentages of explanations of stepwise regression equation range between 0.00% in April to 95.7% in February and it rates of redundancies range from 4.30 % in February to 100% in April. The results show that high rates of redundancies were exhibited in the various associations. Meanwhile, redundancies were patterned after the reservoir hydrology. For example, high redundancies were experienced in the period of low inflows such as April and November, while low redundancies were exhibited in periods of high inflows such as January, September and October. The paper has exposed that high level of redundancies are exhibited on monthly basis. The knowledge of the redundancies are important to designs of reservoir rules. The study further recommends that attempt should be made to control reservoir evaporation.
reduce-rank models to estimate rates of redundancies on monthly basis. Altogether, 24 mathematical operations were carried out; which is a breakdown of 2 factor regression modelling operations per month (one each for factor-multiple and factor-stepwise regression). The percentages of explanation of factor analysis equations range from 79.2% in April to 92.7% in December, with percentages of redundancies ranging from 7.70% in December to 20.8% in April. The percentages of explanation of multiple regression also vary from 13.4% in April to 98.5% in February, while its monthly percentages of explanations outside the multiple regression equations range between 1.50% in February to 86.6% in April. Also, the percentages of explanations of stepwise regression equation range between 0.00% in April to 95.7% in February and it rates of redundancies range from 4.30 % in February to 100% in April. The results show that high rates of redundancies were exhibited in the various associations. Meanwhile, redundancies were patterned after the reservoir hydrology. For example, high redundancies were experienced in the period of low inflows such as April and November, while low redundancies were exhibited in periods of high inflows such as January, September and October. The paper has exposed that high level of redundancies are exhibited on monthly basis. The knowledge of the redundancies are important to designs of reservoir rules. The study further recommends that attempt should be made to control reservoir evaporation.
