Multi-objective optimal day-ahead scheduling of desalination-hydrogen system powered by hybrid renewable energy sources

An energy system with desalination and hydrogen production and storage is a promising option for remote areas with shorelines, e.g., Middle East, to jointly manage electricity, desalinated water and hydrogen resources. Thus, a hybrid renewable energy system considering seawater reverse osmosis desalination, proton exchange membrane electrolyzer stacks, and also proton exchange membrane fuel cell, is proposed. This work focuses on the optimal operation problem of the system. It is established in a multi-objective optimization manner, with consideration of minimizing system total cost, power transmission and renewable energy curtailment. The problem is solved with Non-dominated Sorting Genetic Algorithm-III, a meta-heuristic method dedicated to multi-objective optimization. Results show through the solving of the optimization problem the optimal energy management strategy can be obtained, and in the studied scenario, the system can avoid 38-42% of carbon dioxide emission compared to conventional electricity generation and gray hydrogen production measures. The operational benefit of fuel cell is also verified. Compared to existing works, this work maintains the flexibility and cleanness of green hydrogen production components, consider more aspect in operation and can be solved with limited computational resources and obtain a satisfying result.

Automated summary

This study proposes a hybrid renewable energy system with seawater reverse osmosis desalination, proton exchange membrane electrolyzer stacks, and proton exchange membrane fuel cells for optimal operation. The system aims to minimize total cost, power transmission, and renewable energy curtailment through multi-objective optimization. Results show that the system can reduce carbon dioxide emissions by 38-42% compared to conventional electricity generation and gray hydrogen production measures.