Scenario-Based Optimization towards Sustainable Power Generation in Sudan

Sudan faces an electricity supply shortage despite its abundant natural resources. This paper aims to manage these resources for sustainable power generation to meet Sudan's electricity demand. The sustainability assessment integrates quantitative analysis of power generation's impacts on water, land, and greenhouse gas (GHG) emissions, in addition to the levelized cost of electricity (LCOE). Cost-effective, resource- and GHG emission-effective, and GHG-stringent scenarios are executed in this study to investigate the impact of different constraints on the sustainability of power generation in Sudan. The average LCOEAV for these three scenarios is 43.64-100.00 USD/MWh, with the lowest in the cost-effective scenario and the highest in the resource- and GHG emission-effective scenario. The LCOEAV for the stringent scenario is 32% higher than the cost-effective scenario. The two governmental and lowest-cost plans, which serve as the business-as-usual cases in this study, are optimized and comparatively evaluated. The sensitivity analysis is conducted by reducing each clean energy pathway to a minimum LCOE of 42.89 USD/MWh. Solar-photovoltaic (PV), wind, and hydroelectricity pathways are the most sensitive to the LCOE and can significantly contribute to Sudan's total power generation if their costs are minimal. A rational scenario for power generation in Sudan is developed to improve sustainability performance and avoid the unreliability of the studied scenarios and cases. The rational average generation mix comprises 44% clean energy, 46% fossil fuels, and 10% imported electricity pathways.

Automated summary

This study aims to achieve sustainable power generation in Sudan by effectively managing resources to meet the electricity demand. It analyzes the impact of different constraints on the sustainability of power generation through quantitative analysis of water, land, greenhouse gas emissions, and the levelized cost of electricity. The sensitivity analysis reveals that solar-photovoltaic, wind, and hydroelectricity pathways are most sensitive to the cost of electricity and can significantly contribute to Sudan's total power generation if their costs are minimized. A rational power generation scenario is developed to improve sustainability performance and reliability.