This study examines the optimization and expansion of electricity supply in the Democratic Republic of Congo (DRC) using the OSeMOSYS energy modeling framework, a cost-optimization tool tailored to meet growing energy demand. The primary goal is to model energy supply scenarios capable of addressing the rising electricity demand in the residential sector, driven by population growth, income increases, and improved electricity access rates. Three energy-mix scenarios are analyzed: the baseline or business-as-usual scenario (BASE), the governmental ambition scenario (GVT), and the renewable energy integration scenario (RNW). The BASE scenario allows unrestricted investments in any available technology. The GVT scenario incorporates BASE while emphasizing the rehabilitation of existing infrastructure. The RNW scenario excludes fossil fuel investments, prioritizing hydropower and solar energy. Results indicate that GVT is the least costly scenario, followed by BASE. RNW, while more expensive, is the least polluting. However, the GVT scenario excludes rehabilitation costs, and both BASE and GVT rely on diesel and natural gas plants to meet the government's ambitious targets of 62% electricity access and 30% clean cooking access. RNW is the most suitable for DRC’s context, leveraging off-grid hydropower and solar solutions for remote rural areas with limited road access, despite its higher upfront costs.