An Improved Slant Path Attenuation Prediction Method in Tropical Climates

An improved method for predicting slant path attenuation in tropical climates is presented in this paper. The proposed approach is based on rain intensity data R_0.01 (mm/h) from 37 tropical and equatorial stations; and is validated by using the measurement data from a few localities in tropical climates. The new method seems to accurately predict the slant path attenuation in tropical localities, and the comparative tests seem to show significant improvement in terms of the RMS of the relative error variable compared to the RMS obtained with the SAM, Crane, and ITU-R prediction models

A steepest descent algorithm for the optimal control of a cascaded hydropower system

Optimal power generation along the cascaded Kainji-Jebba hydroelectric power system had been very difficult to achieve. The reservoirs operating heads are being affected by possible variation in impoundments upstream, stochastic factors that are weather-related, availability of the turbo-alternators and power generated at any time. Proposed in this paper, is an algorithm for solving the optimal release of water on the cascaded hydropower system based on steepest descent method. The uniqueness of this work is the conversion of the infinite dimensional control problem to a finite one, the introduction of clever techniques for choosing the steepest descent step size in each iteration and the nonlinear penalty embedded in the procedure. The control algorithm was implemented in an Excel VBA® environment to solve the ormulated Lagrange problem within an accuracy of 0.03%. It is recommended for use in system studies and control design for the optimal power generation in the cascaded hydropower system

A novel model for solar radiation prediction

Energy for fulfilling basic community/individual needs has come to constitute the first article of expectation in all contemporary societies. The exploitation of renewables notably solar in electricity generation has brought relief to the fulfilment of energy demand especially among susceptible communities. In this paper yearly minimum solar radiation of Kano (12.05°N; 08.2°E; altitude 472.5 m; 3 air density 1.1705 kg/m3) for 46 years is used to generate a prediction model that fits the data using autoregressive moving average (ARMA) and a new model termed autoregressive moving average process (ARMAP). Comparison between the ARMA and ARMAP models showed a tremendous improve in the sum of square error reduction between the actual data and the forecasted data by 47%

Investigation of the unified rain attenuation prediction method with data from tropical climates

The semi-empirical method recently proposed by Silva Mello and Pontes (SMP) for the prediction of rain attenuation in slant paths is investigated in this letter. The SMP method uses the simplified model of equivalent rain cell and the concept of an effective rain rate. However, substantial deviations were observed in SMP predictions when compared to the rain cell diameters derived from experimental data. The measured rain rates and attenuations were obtained from three tropical climates (Australia, and USM and IIUM both in Malaysia). The measured rain attenuation complementary cumulative distributions (CCDs) were also compared to SMP and the Rec. ITU-R P. 618-11. The test results show that the ITU-R model performs much better compared to SMP method in the three tropical climates

Using full rainfall rate distribution for rain attenuation predictions over terrestrial microwave links in Malaysia

The use of full rainfall rate distribution for the prediction of rain attenuation over terrestrial microwave links in Malaysia is presented in this letter. The experimental data consist of four-year measured rainfall rates and one-year rain attenuation measurements over six geographically spread DIGI MINI-LINKs operating at 15 GHz. The test results show that ITU-R model does not perform well for rain attenuation predictions in tropical Malaysian climate

Statistical evaluation of measured rain attenuation in tropical climate and comparison with prediction models

Substantial modifications have been made to the expressions for calculating distance factor and extrapolation techniques in the latest ITU-R P.530-14. However, its performance has not been rigorously evaluated in the tropical and equatorial climates. In this article, the new ITU-R method and three prediction models are validated using measurement data from tropical Malaysian climate. The data were collected on six geographically spread terrestrial microwave DIGI MINI-LINKs operating at 15 GHz. When tested against measurements, the Da Silva Mello model yields a significant improvement for the prediction of rain attenuation distributions. The prediction errors observed in the ITU-R model suggest the need for more data campaign in the afore-mentioned climates

A control model of the operating head dynamics of Jebba hydropower system

Electricity availability in Nigeria has been very poor over the years, underscoring the need for a better approach for managing generating resources. This paper presents the development of a dynamical model of the operating head of Jebba hydroelectric power plants for system studies and control system design. The mathematical model of the plant was developed from flow continuity conditions, some model parameters were obtained from the source while others were estimated from observations and analysis of the measured data. The developed dynamical equation was validated by comparing the response produced with values obtained by measurement. Upon integrating the model equation in Microsoft EXCEL VBA® environment, a deviation of 2% from measured values was observed. Operators can therefore use the model as a decision support system, while control engineers can find the model directly applicable for optimal and robust control system design for the station.Keywords: Control, Dynamical model, Hydropower, Inflow, Operating head

Statistical Evaluation of Measured Rain Attenuation in Tropical Climate and Comparison with Prediction Models

Abstract Substantial modifications have been made to the expressions for calculating distance factor and extrapolation techniques in the latest ITU-R P.530-14. However, its performance has not been rigorously evaluated in the tropical and equatorial climates. In this article, the new ITU-R method and three prediction models are validated using measurement data from tropical Malaysian climate. The data were collected on six geographically spread terrestrial microwave DIGI MINI-LINKs operating at 15 GHz. When tested against measurements, the Da Silva Mello model yields a significant improvement for the prediction of rain attenuation distributions. The prediction errors observed in the ITU-R model suggest the need for more data campaign in the afore-mentioned climates

An improved slant path attenuation prediction method in tropical climates

An improved method for predicting slant path attenuation in tropical climates is presented in this paper. The proposed approach is based on rain intensity data R0.01 (mm/h) from 37 tropical and equatorial stations; and is validated by using the measurement data from a few localities in tropical climates. The new method seems to accurately predict the slant path attenuation in tropical localities, and the comparative tests seem to show significant improvement in terms of the RMS of the relative error variable compared to the RMS obtained with the SAM, Crane, and ITU-R prediction models