Optimum predictive modelling for a sustainable power supply mix: A case of the Nigerian power system

Abstract

The ever-increasing demand for electricity, as well as its impact on the environment, necessitates expanding the power generation mix of Nigeria by utilizing sustainable energy sources. Power generation planning that is sustainable and efficient must meet various objectives, many of which conflict with one another. Using multi-objective optimization, a model for Nigeria's power supply architecture was developed to integrate indigenous energy sources for a sustainable power generation mix. The model has three conflicting objectives: reducing power generating costs, reducing CO2 emissions, and increasing jobs. Hybrid Structural Interaction Matrix was utilized to compute the weights of the three objectives for the multi-objective model to be modified into a single-objective model. According to the simulations, Nigeria could address its power supply deficit by generating up to 2,100 TWh of power by 2050. Over the projected period, large hydropower plants and solar PV will be the leading option for Nigeria's power generation mix. Furthermore, power generation from solar thermal, incinerator, nuclear, gas plant, combined plant, and diesel engine will all be part of the power supply mix by 2050. In terms of jobs expected to be created, about 2.05 million jobs will be added by 2050 from the construction and operation of power generation plants. CO2 emissions will attain 266 MtCO2 by 2050. The cost of power generation will decline from a maximum of 36 billion US$ in 2030 to 27.1 billion US$ in 2050. Findings conclude that Nigeria can meet its power supply obligations by harnessing indigenous energy sources into an optimal power supply mix.

Keywords

• Multi-objective optimization
• Power
• Sustainability
• Economic
• Emissions
• Job creation