# Assessment of Impacts of Climate Change on Hydropower-Dominated Power System--The Case of Ethiopia
## 2 Methods
#### Steps Used
Step 3: the open-source cost optimization tool, OSeMOSYS [25; 26], was applied for long-term energy planning and to assess the required electricity capacity and CO2 emissions. The objective of this tool is to identify the least-cost energy supply mix that meets the electric services demands. A model for Ethiopia included historical energy sector data and the year 2015 was considered as the starting year to forecast up to 2065. New Policy Scenario: The New Policy Scenario considers current energy policy and plans detailed in NEP-2 [1; 2; 31; 32], will be mostly accomplished and implemented as intended. It is assumed that infrastructure projects that are still in the planning stages will be completed. The scenario does not include the fundamental institutional or public sector reforms that would promote fast-paced and efficient growth as a relative status quo future. As a result, projects with recognized concerns, as well as related infrastructure projects facing similar risks, are delayed in their implementation and also considers country experiences of project completion and delays for various hydropower projects. With strong overall power demand growth, the scenario maintains a core level of optimism. The speed of change within society is slow, electrification proceeds, and national objectives are accomplished in this scenario, however the energy access agenda is not as ambitious as it could be [28]. Drought Scenario: Putting the above procedures into practice, the Drought Scenario considered in this article was developed and cloned with the New Policy Scenario assuming the foreseeable future climate change would reduce hydroelectric capacity by 50%. In the Drought Scenario, the same policy goals [1; 2; 31; 32] as that of the New Policy Scenario were considered to be implemented as intended. Given the expected negative impacts of climate change on precipitation, runoff, and water resources availability, as well as the expected low \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Fossil and Nuclear** & **Renewables** \\ \hline
**Centralized** & Diesel & Geothermal \\  & Heavy FuelOil & Biomass and waste CHP \\  & Natural Gas: OCGT, CCGT & Hydro: small, medium, large \\  & Coal & Wind: onshore \\  & Nuclear & Solar PV (utility scale) \\  & & Solar PV (roof top) \\  & & Solar PV with storage \\  & & CSP with storage \\  & & CSP without storage \\ \hline
**Decentralised** & Diesel Genest Micro Grid & Small Hydro Micro Grid \\  & (rural, urban) & (rural, urban) \\  & Diesel Genest Stand Alone & Solar PV Micro Grid (rural, urban) \\  & & urban \\  & & Solar PV 1–5 Stand Alone \\  & & (0.02 kW, 0.05 kW, 0.1 kW, 0.2 \\  & & kW, >0.2 kW; urban, rural) \\  & & Wind Micro Grid (rural, urban) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of centralized and decentralized technologies included in the model [28]. negative impacts of climate change on the wind, biofuels, solar irradiance, and geothermal resources [33], the analysis in this study is limited to climate change impacts on water resources and hydropower technology that uses this resource for electricity production. Additionally, in the Drought Scenario, the following assumption was considered: Between now and 2065, the capacity factor of hydroelectric technology was expected to drop by half (by 50%) compared to the baseline scenario-New Policy (a capacity reduction over the entire simulation period). The severity of the situation was worsened by probable drought. Finally, the results of the Drought Scenario were compared with the results of the New Scenario. The reason for comparing the two scenarios will provide detailed information about power generating capacity, renewable energy penetration, and the difference in hydropower technology generation due to severe drought.