Hydropower forecast in Ethiopia using the HBV model - A case study in Omo-Gibe river basin

Abstract: Ethiopia produces 86% of its electricity from hydropower source, still they experience frequent power shortages. As they are part of the East African Power Pool, this power shortage is usually made up for by buying energy from other members of the pool. Forecasting the energy available for usage in the future allows Ethiopia to buy energy ahead of time when prices are low, but also to sell surplus electricity to neighboring countries. This is the degree project I was offered to investigate into at the company Refinitiv. To do so, a modified HBV model was used to predict the hydroelectricity, using as input one of the two weather datasets (CPCP and CFSR), both provided by the company, and a Q-target series against which the computed runoff is evaluated. The task of constructing a Q-target series meant that an extensive search for runoff data was necessary. After finding such data and entering the Q-target series in the model, the model’s performance was assessed during the calibration and validation parts. The model using CFSR data was found to perform better than CPCP’s by a substantial margin. Nonetheless, the results are promising for both models. Suggestions for further work in this subject relate to the quality of the runoff data used, as the data used in this project originated from a secondary source, and missing runoff data was filled in using unknown interpolation equations. For this reason, it is recommended to get the raw data from the primary source, namely the Ministry of Water, Irrigation and Energy. This would allow for greater flexibility during the construction of the Q-target series.