Mixing nuclear and conventional fossil fuel units within the baseload of PP using the CPLEX Optimizer - Al-Qahtani, Abdullah M.; Al-Shaalan, Abdullah M.; Al-Masry, Waheed A.; Hussein Farh, Hassan M. (Frontiers in Energy Research, 2024)
The future electric loads in the Kingdom of Saudi Arabia (KSA) are increasing significantly, particularly in the Eastern Provence of the KSA. These high-rise loads are primarily driven by the operational needs of the Saudi Arabian oil company Aramco, including oil refineries, and the infrastructures of the Saudi Basic Industries Corporation (SABIC) factories. This study aims to construct a nuclear power plant in that area to supplement and support the base load currently covered by conventional generation units powered by fossil fuels within the Saudi Electric Company (SEC) operations. The objective function is to minimize the operational costs of the power systems to the greatest extent possible. In this paper, a case study was conducted using the IBM CPLEX Optimizer software to compare the operational costs of KSA's power systems for a 24-hour period. Two scenarios were considered and addressed: the first scenario without the inclusion of a Nuclear Power Plant (NPP), and the second scenario with the inclusion of the NPP. The unit commitment problem was modeled for both scenarios. The obtained results revealed that the second scenario, which involved the penetration of the NPP, offered the optimal economic solution for operating KSA's power systems. By employing the CPLEX Optimizer software and analyzing the unit commitment problem, this study provides valuable insights into the economic advantages of integrating NPP into the power systems of the Kingdom of Saudi Arabia. The NPP shows viability in terms of minimizing the operational costs which equal to 32.10 $/MWh compared to first scenario where operational costs equal to 42.10 $/MWh and resulted in almost 24% reduction of operational costs. In addition, NPP is deemed as an optimal technology to contribute to the zero net goal by 2060 where it can reduce the reliance on fossil fuel power plants and contribute to the reduction of CO2 emissions.