Optimal Operations of Nuclear-Based Integrated Energy Systems with Mixed-Integer Programming

A nuclear-based integrated energy system (IES), consisting of multiple carbon-free energy generation and conversion technologies to meet heterogeneous end-use demands, offers a promising approach to decarbonize the U.S. economy. Operating such an IES is challenging due to its complexity and the diverse end-use demands, such as heating and electricity. This paper aims to address the optimal operation of an IES composed of a small modular reactor, a steam manifold, a balance of plant, a high-temperature steam electrolysis system, a district heating (DH) network, and electrical grids. We formulate the system's operation as a mixed-integer linear programming problem to maximize net revenues from sales of electricity and hydrogen. To evaluate the efficacy of the proposed model, we conduct a 24-hour simulation considering day-ahead electricity prices from the California Independent System Operator (CAISO) and a varying DH demand profile with hourly resolution. The simulation results show that our model effectively optimizes the operation by selling electricity during on-peak periods and purchasing electricity for hydrogen production during off-peak periods, while satisfying operating constraints within the IES.