A Transactive Energy Framework for Hydrogen Production with Economically Viable Nuclear Power

This paper demonstrates the use of transactive energy (TE) to maximize the profitability and flexibility of a nuclear power plant. Reductions in the price of natural gas, and the concurrent influx of variable and distributed energy resources in the electricity market of the U.S. have impacted the economic viability of traditional nuclear power generation, which is currently untenable for adapting to dynamic pricing trends. This can be resolved by using TE concepts to control and coordinate an integrated nuclear energy system. This system can recuperate by using the excess nuclear thermal energy at times when the electricity prices are low to produce hydrogen and participate in the hydrogen market. A nuclear-renewable integrated energy system is demonstrated here with renewable sources, electrolyzers, a power conversion system, and storage systems along with the nuclear power plant. Deep reinforcement learning (DRL) methodology has been used to control, coordinate, and optimize the system based on TE concepts. The proposed framework demonstrates how future nuclear generation can flexibly participate in electric power markets.