Developing a Strategic Roadmap Toward Hydrogen energy Economy for energy mix integration In Saudi Arabia

Abstract

The present thesis provides a detailed analysis of the current situation in the landscape of hydrogen energy, underlining an advanced framework of DSS that can work on optimizing all stages of hydrogen production, deployment, and integration into the energy sector. This research, conducted within the larger context of transitioning global energy resources towards sustainability, investigates how DSS might empower leaders to master the complexities associated with transitioning toward a hydrogen-based economy balanced among economic, environmental, and logistical concerns. In this DSS framework, designed on MATLAB Web App Designer, nine strategic scenarios are analysed using MCDM and decision tree approaches, considering the dynamics of demand and supply, production costs, policies, and ecological benefits. A DSS framework is an integrated system wherein data, modelling, analysis, and decision-making are systematically structured. Therefore, the present DSS framework acts as an important tool to arrive at informed, scalable, and flexible hydrogen production strategies. This study highlights the DSS's potential to undertake activities, such as market analysis, regulatory compliance, and technological integration, which are essential for any strategic planning and operational decision-making in the hydrogen sector. A stakeholder survey validated the functionality of the DSS in promoting green hydrogen adoption. The real-time analysis and scenario planning functionality of the system received high ratings among industry and policy stakeholders. Moreover, survey analysis underlined that DSS can be adapted to different regulatory and operational contexts. Such a characteristic is indicative of wide applicability in the hydrogen economy. Large correlations between important dimensions imply the contribution of the DSS framework to a strong and predictive decision-making process. Dimension 2 acts as a key factor in the performance of systems regarding market trend analysis and trade decisions. i Results strongly point toward the contribution of DSS in developing hydrogen energy in tune with global sustainability targets and extend a peek into some future directions based on the functionality of the DSS itself. Recommendations include embedding machine learning with advanced predictive analytics to improve market trend forecasting and regulatory response, while expansion of DSS customization to accommodate the diverse production methods for hydrogen is also welcome. This DSS will stimulate more accurate, data-driven decision-making by making strategic insights available that will be required to optimize hydrogen production and its integration into a global energy world to further sustainable development goals