The global energy sector faces the grand challenge of meeting the increasing demand while profoundly reducing greenhouse gas emissions . Today’s energy sector is responsible for approximately 80% of the world’s total GHG emissions, and the electricity sector is the largest single emitting sector with 33% share. Industrial processes constitute 22% of emissions, while the transportation sector is responsible for 16%. Moving forward, the evolution of energy systems is characterized by greater convergence of power, transportation, and industrial sectors and inter-sectoral integration. Investigating powerful complexities arising from this paradigm shift using the existing techniques and instruments is difficult to all stakeholders. Understanding the implications of these dynamics requires novel tools and techniques that provide deep systems-level insights. To address this pressing need, we have developed a modelling framework that is designed to explore the impacts of all relevant technological, operational, temporal, and geospatial characteristics of the evolving energy system .
This paper presents key insights from our modelling work. The analysis focuses on two major energy vectors for deep decarbonization: electric power system and hydrogen. First, the status quo of global coal power plants is presented to demonstrate the need for carbon capture, utilization, and storage for reducing emission intensity of electricity generation. The discussion on power system then explores the impact of meaningful variable renewable energy sources in power generation mix on the performance of existing fossil fuel fired power plants. Key observations from the state of California, USA is presented as a case study. Third, options to address the challenges of balancing the power system with intermittent sources is discussed. Versatility of hydrogen can play an important role in electric power system as well as in other hard to decarbonize sectors. Importance of optionality in addressing the global energy challenge and need for wholistic approach are highlighted in conclusion.