# Assessment of Impacts of Climate Change on Hydropower-Dominated Power System--The Case of Ethiopia
## 2 Methods
#### Steps Used  
This paper tried to build on an already developed scenario (New Policy Scenario) in the model developed for the PATHWAYS project, which is then used here as a baseline in order to compare with a Drought Scenario, which shows the effect of climate change in Ethiopia's Power Generation System and Environment. The study [28] developed different scenarios including the New Policy Scenario targeting the requirement of electric supply and CO2 emissions within an energy system modelling framework. The steps used are as follows:  
Step 1: It starts with energy demand development, driven by the aforementioned factors, which consist of gathering data for energy demand projections, primary energy resources and transmission and distribution system collected from 18 different offices under the Ministry of Water Irrigation and Energy (MoWIE), Minister for Mines, Petroleum and Natural Gas (MoMNG) and a literature survey. Step 2: To estimate the generation capacity, the generation mix, and the CO2 emission, some basic modelling assumptions were considered. Some of them are:  
* The modelling period was from 2015 to 2065, with one-year intervals. * The electric demand includes the electricity demand of the current electrified people in the residential sector as well as the demand of the rest of the sectors (industry, commercial and public services)
* In accordance with the national policy plan, an 18% reserve margin was contemplated. * In order to capture the key features of electricity demand load pattern, each year has been divided into four seasons and two day parts. (Season 1: March-May, Season 2: June-August, Season 3: September-November, Season 4: December-February; Day part 1: 09:00-18:00, Day part 2: 19:00-08:00). * In the OSeMOSYS model, a country-specific hourly load profile was used to reflect the power demand profile. * Only the capacity of the committed future projects (power plants, electricity trade links), which their contract has been signed or the construction has started are forced to be installed into the model. The rest of the future power plants and trade links are provided as an option for the model to invest in. * The grid-connected power generation technologies are distinguished in \"old\" (existing capacity until 2014) and \"new\" (capacity investments 2015-2065). The study researchers were able to collect data about the county's power generation technologies by capacity and generation since 2015 from the country's national load dispatching centre. As a result, the Electricity demand projection is started at 2015. * Techno-economic assumptions for the power generation technologies are derived from international organizations such as IEA andWorld Energy Outlook 2016 [29]. * In the analysis, carbon dioxide emission factors per fuel were employed. * Country specific fossil fuels reserves and renewable energy potential. * Country specific capacity factors for renewable energy technologies (solar, wind) in the OSeMOSYS model are derived from www.renewables.ninja (accessed on 6 November 2021), which is relevant to estimate amount of energy that could be generated by wind or solar farms at any location [30]. The parameter Capacity Factor is used to specify the generation curve of the wind and solar technologies. * Generic capacity factors are assumed for hydropower plants. The hydropower plants are divided into the following categories: small (<20 MW), medium (20-100 MW), large (>100 MW). The capacity factor 50% is assumed. * Electricity trades are considered in the analysis. It has been assumed that a lower amount of electricity based on historical values and the respective installed capacity of the electricity interconnector will be exported to the other countries (Djibouti, Sudan, Kenya, and Tanzania). * The power generation technologies (centralized, decentralized) used in the models are mentioned in Table 1. In this article, the centralized power generation technologies are only discussed.