TITLE:
Multi-Objective Optimization Model for Generation Expansion Planning in Industrial Power Systems: A Case Study of Kolwezi, DRC
AUTHORS:
Delphin Ndjaokako Olembo, Henri-Joshua Mukoko
KEYWORDS:
Generation Expansion Planning, Multi-Objective Optimization, MILP, Renewable Energy, Battery Storage, Demand Response, Industrial Power System, Kolwezi, DRC
JOURNAL NAME:
Energy and Power Engineering,
Vol.18 No.11,
November
5,
2026
ABSTRACT: The energy transition and rapid growth in electricity demand in African mining regions, such as Kolwezi (Democratic Republic of the Congo), require a redesign of industrial power systems currently dependent on costly and polluting diesel generators. This work proposes a multi-objective optimization model based on mixed-integer linear programming (MILP) for generation expansion planning, integrating photovoltaic plants, battery energy storage systems (BESS), and demand response (DR) programs. Three objectives are simultaneously minimized: total annualized cost, CO2 emissions, and energy not supplied. The ε-constraint method is used to generate the Pareto front, and the best compromise solution is identified using the TOPSIS method. Applied to the Kolwezi industrial power system, the model shows that integrated planning can reduce total operating costs by more than 20%, CO2 emissions by approximately 49%, and energy not supplied by more than 80% compared to the reference scenario, while increasing the share of renewables to over 55% of the energy mix. Sensitivity analysis shows that both the battery investment cost and the diesel price are the most influential parameters: a 50% reduction in battery costs increases the optimal BESS capacity by 6% and improves system profitability, while a 30% increase in battery costs would further improve system profitability. This model constitutes a robust decision-support tool to support the energy transition of African mining basins.