Synthesis of bio-hydrogen supply network via graph-theoretic approach coupled with Monte Carlo simulation model

Abstract

Abstract The shift from fossil fuels-derived hydrogen (grey or brown hydrogen) to renewable energy-derived hydrogen (green hydrogen) production is essential to achieve Sustainable Development Goal 7 (SDG7) which aims to ensure the accessibility to affordable, reliable, sustainable, and modern energy. One of the renewable energy sources that have been extensively studied is the biomass-derived energy source. The abundance of palm oil mill effluent (POME) produced annually in Malaysia, poses a unique potential of them being utilized as an alternative renewable feedstock for biohydrogen production. Therefore, this project aims to synthesize an optimal bio-hydrogen supply network via the integration of graph-theoretic approach and Monte Carlo simulation model where palm oil mills serve as hydrogen sources, while the ammonia plants serve as hydrogen sinks. Monte Carlo simulation was performed for the top three ranked bio-hydrogen supply networks extracted from the P-graph model. The uncertainties incorporated in the Monte Carlo simulation model are natural gas price and hydrogen price. Using Sarawak as the case study, it was found that the first ranked solution extracted from the P-graph model had the higher mean NPV value of USD 1,202.12 million.