# Economic NMPC for a Reversible Solid Oxide Cell

## TL;DR

This paper introduces an economic control strategy for reversible solid oxide cells to optimize their operation based on electricity prices.

## Contribution

The novelty is an economic nonlinear model predictive control framework tailored for reversible solid oxide cells.

## Key findings

- E-NMPC reduces hydrogen consumption in fuel cell mode while maintaining electricity output.
- E-NMPC provides marginal improvement in hydrogen production during electrolysis mode.
- Battery integration enhances the system's flexibility in meeting energy targets.

## Abstract

Reversible solid oxide fuel cells (rSOCs) offer the flexibility
to operate in tandem with the electric grid by switching between fuel
cell and electrolysis modes based on real-time electricity prices.
However, their complex, tightly coupled dynamic behavior poses significant
challenges in determining optimal operating strategies. In this work,
we present an economic nonlinear model predictive control (E-NMPC)
framework to optimize the operation of rSOCs. The proposed E-NMPC
is applied to a detailed rSOC flowsheet model that includes a utility
scale rSOC module as well as balance-of-plant equipment necessary
for thermal management. Our results demonstrate that in fuel cell
mode, the E-NMPC strategy reduces hydrogen consumption compared to
conventional set-point tracking NMPC, while maintaining the same level
of electricity output. Also, in electrolysis mode, the E-NMPC yields
a marginal improvement in hydrogen production. In addition, we explore
the integration of a battery with the rSOC system to enhance flexibility
in meeting electricity production and consumption targets.