Developing a strategic roadmap toward hydrogen energy economy for energy mix integration in Saudi Arabia

Abstract

Luk, Patrick Chi-Kwong - Associate SupervisorHydrogen has come to the forefront as a hopeful solution in the transition toward cleaner, more sustainable sources of energy that will meet global decarbonization goals. However, while it is a great potential, a few challenges are found within the hydrogen sector, including fluctuating renewable energy costs, policy uncertainties, and complex issues related to storage, transportation, and market integration. These make efficient production and distribution of hydrogen hard, hence acting as a barrier to large-scale adoption. This research addresses these challenges through developing a strategic DSS intended to optimize the production and distribution of hydrogen. The presented DSS integrates multi-criteria decision-making and decision tree methodologies to obtain a flexible tool based on data that will balance economic feasibility, technological adaptability, environmental sustainability, and compliance with regulations. By putting all these elements together, the DSS provides an integrated approach to making decisions for addressing issues with hydrogen energy systems. This work is motivated by the fact that literature lacks integrated frameworks that might guide decision analyses in hydrogen production. Most works have focused on isolated issues related to the analysis of technology costs or even policy impacts, excluding the important needs for a strategic approach that captures all these significant factors in one fell swoop. This study fills this gap by presenting one unified system able to support relevant, strategic decisions by any stakeholder. A case study undertaken in Saudi Arabia validates the DSS against practical, real-world scenarios for completeness in aligning with the Vision 2030 energy transition pathways of the country. It should not only promote efficiency and costeffectiveness of hydrogen production but also meet green practices by remaining in step with environmental targets and market demand. Besides, the integration of machine learning techniques enhances the predictive capabilities of DSS and hence increases its adaptability toward dynamically changing energy markets. These research findings pinpoint the DSS as a very important tool for furthering hydrogen production and distribution while offering valuable insights for policymakers, industry leaders, and investors in the same instance. Given that this study provides a structured approach to decision-making, it will contribute valuably to the global effort of developing a sustainable hydrogen economy and support broader goals for energy security and environmental stewardship.PhD in Energy and Powe