Genetic algorithm based optimization of smart utilization for a small power grid

Abstract

The objective of this study is to develop a comprehensive tool to support the development of operating strategies needed to minimize the total generation cost of a small nuclear reactor (SMART-100) in the region. To achieve this, uniform generation costs according to carbon tax, interest rates, and generation efficiency were defined for each type of power generation. Seasonal renewable energy generation and electricity demand for different regions were predicted using LSTM (Long Short-Term Memory) models. It was assumed that a small nuclear reactor was installed in the region, and the electricity production over time was determined based on a genetic algorithm. The objective function of the genetic algorithm is to minimize the generation cost. It was found that installing a small nuclear reactor results in more economical outcomes compared to not installing one. However, since the generation cost increases significantly as the generation efficiency of the small nuclear reactor decreases, it is generally more viable to perform base load operation. Depending on the case, it may be necessary to use energy storage systems or reduce the real-time electricity production of energy sources that can control the generation capacity to handle the rapid increase in renewable energy production during off-peak hours. Maintaining a high generation efficiency of the small nuclear reactor while performing load-following operation is important. Additionally, based on literature reviews and our own research, it was concluded that actively using energy storage systems is not economically viable at the moment, so load-following operation of energy sources that can control generation capacity is a more feasible option. However, due to excess reactivity caused by the consumption of fuel and the distorted axial power distribution in the reactor, there are significant constraints on load-following operation of small nuclear reactors. Therefore, further analysis is needed for load-following operation of small nuclear reactors. For this purpose, mathematical models of the primary system, steam generator, and secondary system of SMART-100 were developed using Python and MATLAB. The core reactivity and axial power distribution required for load-following operation were controlled using two banks of control rods located in the upper and lower parts, and a multi-purpose sliding mode control technique was applied. As a result, it was concluded that when there are small nuclear reactors with different fuel consumption rates in the power grid, load-following operation can be performed without issues in excess reactivity and axial power distribution only when the nuclear fuel consumption rate exceeds 99.5%.