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Power system sensitivity to extreme hydrological conditions as studied using an integrated reservoir and power system dispatch model, the case of Ethiopia

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  • Demissie, Ashenafi A.
  • Solomon, A.A.

Abstract

Extreme weather events expose electricity industry to diverse risks. Global warming will increase vulnerability to extreme weathers, such as drought. In this paper, we examine the susceptibility of Ethiopian power systems to extreme hydrological conditions using an integrated hydro reservoir and power system dispatch model. The result shows that hydropower could help in achieving the least cost generation of electricity by 2017. However, the cost of electricity was found to significantly vary with various factors. It was found that, excluding cost of unserved energy, the low inflow scenario presents a situation where cost of electricity is approximately 4 times higher than the moderate inflow. Electricity price is currently cheap and stable due to governments pricing strategy. Consequently, the cost borne by the nation’s economy could be seen from annual cost of dispatch, which increases from approximately 1 billion USD per year at the reference scenario to about 4 Billion USD for the low inflow scenario. The dispatch cost will be above 8 folds if the cost of unserved energy is included. This shows that the power system is poorly resilient against climate change impact. Thus, we recommend that policymaking and planning focuses on transitioning to climate change adaptive system.

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  • Demissie, Ashenafi A. & Solomon, A.A., 2016. "Power system sensitivity to extreme hydrological conditions as studied using an integrated reservoir and power system dispatch model, the case of Ethiopia," Applied Energy, Elsevier, vol. 182(C), pages 442-463.
    • Handle: RePEc:eee:appene:v:182:y:2016:i:c:p:442-463
    DOI: 10.1016/j.apenergy.2016.08.106
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    6. Patro, Epari Ritesh & De Michele, Carlo & Avanzi, Francesco, 2018. "Future perspectives of run-of-the-river hydropower and the impact of glaciers’ shrinkage: The case of Italian Alps," Applied Energy, Elsevier, vol. 231(C), pages 699-713.
    7. Zhou, Yanlai & Guo, Shenglian & Chang, Fi-John & Xu, Chong-Yu, 2018. "Boosting hydropower output of mega cascade reservoirs using an evolutionary algorithm with successive approximation," Applied Energy, Elsevier, vol. 228(C), pages 1726-1739.
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