(471f) Co-Optimized Power and H2 Infrastructure Planning for Multi-Sector Decarbonization | AIChE

(471f) Co-Optimized Power and H2 Infrastructure Planning for Multi-Sector Decarbonization


Mallapragada, D. - Presenter, MIT Energy Initiative
Heuberger, C. F., Imperial College London
Bose, A., Massachusetts Institute of Technology
He, G., Massachusetts Institute of Technology
The past decade has seen significant progress in CO2 emission reduction in the power sector, while progress in other sectors has remained sluggish. With cost reductions in fuel cell and electrolysis technologies and power sector decarbonization, Hydrogen (H2) is becoming an increasingly appealing option for reducing emissions from other end-use sectors, like heavy-duty transport, heating and industry, where electrification may be challenging. Meeting spatially and temporally varying H2 demand requires significant infrastructure investments in H2 generation,storage and transport. To date, most studies on hydrogen infrastructure planning have focused on H2 use in transportation and on evaluating the trade-offs within the H2 supply chain, without consideration to the dynamics of its interactions with the electricity sector. The latter could include: a) H2-based energy storage to manage wind, solar, and demand variability at multiple time-scales, b) flexible electrolytic H2 production coordinated with electricity adequacy and c) transporting H2 or derived carriers instead of electricity to balance spatial variations in energy supply and demand. Understanding the implications of these interactions on the overall cost competitiveness of H2 use requires developing scalable decision-support frameworks with adequate representation of temporal and spatial variability in cross-sectoral interactions.

We have developed a framework for power and H2 infrastructure planning that determines the least-cost mix of electricity and H2 generation, storage, and transmission infrastructures to meet power and H2 demands subject to a variety of operational and policy constraints. Notably, the model includes hourly representation of power and H2 system operation, that is made computationally tractable using judicious approximations and offline time-domain reduction strategies. The developed optimization model can represent a wide range of power and H2 technology options, including renewables, carbon capture and storage (CCS) applied to power and H2 generation, and truck (gaseous and liquid) and pipelines for H2 transportation.

We apply the model to study future electricity and H2 infrastructure needs for the U.S. Northeast region under various carbon policy and H2 demand scenarios. The study reveals several interesting insights. First, CCS is deployed for H2 production via steam methane reforming at lower CO2 prices (< $100/tonne-CO2) than for power generation (~ $200/tonne-CO2). Second, for scenarios with relatively small H2 demand, the operational synergies between the power and H2 sectors, especially at times when electricity prices are low or high, reduces the cost of power sector decarbonization compared to the case without H2 demand. These findings indicate the importance for joint planning of electricity and hydrogen infrastructure for cost-effective energy system decarbonization.