Extended Load Flexibility of Industrial P2H Plants: A Process Constraint-Aware Scheduling Approach

TL;DR

This paper introduces a process constraint-aware scheduling method for industrial P2H plants that exploits detailed electrolyzer dynamics to significantly enhance operational flexibility and profitability.

Contribution

It presents a novel MILP-based scheduling framework that fully considers electrolyzer process constraints, temperature effects, and efficiency variations, extending load flexibility beyond constant assumptions.

Findings

Achieves a 1.627% profit increase in case studies

Demonstrates improved operational flexibility over existing methods

Validates constraints through experiment-based case analysis

Abstract

The operational flexibility of industrial power-to-hydrogen (P2H) plants enables admittance of volatile renewable power and provides auxiliary regulatory services for the power grid. Aiming to extend the flexibility of the P2H plant further, this work presents a scheduling method by considering detailed process constraints of the alkaline electrolyzers. Unlike existing works that assume constant load range, the presented scheduling framework fully exploits the dynamic processes of the electrolyzer, including temperature and hydrogen-to-oxygen (HTO) crossover, to improve operational flexibility. Varying energy conversion efficiency under different load levels and temperature is also considered. The scheduling model is solved by proper mathematical transformation as a mixed-integer linear programming (MILP), which determines the on-off-standby states and power levels of different electrolyzers in the P2H plant for daily operation. With experiment-verified constraints, a case study show that compared to the existing scheduling approach, the improved flexibility leads to a 1.627% profit increase when the P2H plant is directly coupled to the photovoltaic power.