Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Hydrokinetic Energy Assessment in Unregulated River for Hydrokinetic Performance Analysis Studies in East Malaysia

Version 1 : Received: 27 April 2018 / Approved: 27 April 2018 / Online: 27 April 2018 (08:39:22 CEST)

How to cite: Mohd Saupi, A.F.; Mailah, N.F.; Mohd Radzi, M.A.; Ahmad, S.Z.; Che Soh, A. Hydrokinetic Energy Assessment in Unregulated River for Hydrokinetic Performance Analysis Studies in East Malaysia. Preprints 2018, 2018040357. https://doi.org/10.20944/preprints201804.0357.v1 Mohd Saupi, A.F.; Mailah, N.F.; Mohd Radzi, M.A.; Ahmad, S.Z.; Che Soh, A. Hydrokinetic Energy Assessment in Unregulated River for Hydrokinetic Performance Analysis Studies in East Malaysia. Preprints 2018, 2018040357. https://doi.org/10.20944/preprints201804.0357.v1

Abstract

Electrification coverage in Sarawak is the lowest at 78.74%, compared to Peninsular Malaysia at 99.62% and Sabah at 82.51%. Kapit, Sarawak with its 88.4% populations located in rural areas and mostly situated along the main riverbanks has great potential to generate electrical energy by hydrokinetic system. Yearly water velocity data is the most significant parameter to perform hydrokinetic analysis study. Nevertheless, the data retrieved from local river databases are inadequate for river energy analysis, thus hindering its progression. Instead, flow rates and rainfall data had been utilised to estimate the water velocity data. This signifies no estimation of water velocity in an unregulated river by using water level data had been made. Therefore, a novel technique of estimating the daily average water velocity data in unregulated rivers is proposed. The modelling of regression equation for water velocity estimation was performed and two regression model equations were generated to estimate both water level and water velocity on-site and proven to be valid as the coefficient of determination values had been R2 = 87.4% and R2=87.9%, respectively. The combination of both regression model equations can be used to estimate long-term time series water velocity data for type-C unregulated river in remote areas.

Keywords

hydrokinetic; energy assessment; unregulated river; daily water velocity estimation; daily water level estimation; IBM statistical package for social sciences (SPSS); regression analysis; east malaysia

Subject

Engineering, Control and Systems Engineering

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