Decarbonized energy system planning with high-resolution spatial representation of renewables lowers cost

Liying Qiu, Rahman Khorramfar, Saurabh Amin, Michael F. Howland

Decarbonized energy systems will heavily rely on wind, solar, and storage to satisfy time-varying energy demand, yet optimal siting of variable renewable energy (vRE) remains challenging for designing resource-adequate, low-cost power systems. This study performs km-resolution, spatially explicit energy system optimizations to understand how to harness vRE resource complementarity through high-resolution representation of vRE to reduce supply-demand mismatch in the system, especially on the sub-daily scale. The optimized siting is significantly impacted by the resolution used to generate meteorological inputs. Using downscaled meteorological data at km-scale yields lower cost compared with typical meteorological data at resolutions over 30 km, underscoring the value of high-resolution weather and climate data in planning energy systems. In tandem with km-scale meteorological input, spatially explicit energy modeling at 4–6 km for wind and 14–50 km for solar is required to achieve less than 0.5% error in cost estimation across New England (ISONE), Texas (ERCOT), and California (CAISO).

Qiu, Liying, Rahman Khorramfar, Saurabh Amin, and Michael F. Howland. “Decarbonized Energy System Planning with High-Resolution Spatial Representation of Renewables Lowers Cost.” Cell Reports Sustainability, December 6, 2024. https://doi.org/10.1016/j.crsus.2024.100263

Electric-gas infrastructure planning for deep decarbonization of energy systems

Rahman Khorramfar, Dharik Mallapragada, Saurabh Amin

The transition to a deeply decarbonized energy system requires coordinated planning of infrastructure investments and operations serving multiple end-uses while considering technology and policy-enabled interactions across sectors. Electricity and natural gas (NG), which are vital vectors of today’s energy system, are likely to be coupled in different ways in the future, resulting from increasing electrification, adoption of variable renewable energy (VRE) generation in the power sector and policy factors such as cross-sectoral emissions trading. This paper develops a least-cost investment and operations model for joint planning of electricity and NG infrastructures that considers a wide range of available and emerging technology options across the two vectors, including carbon capture and storage (CCS) equipped power generation, low-carbon drop-in fuels (LCDF) as well as long-duration energy storage (LDES). The model incorporates the main operational constraints of both systems and allows each system to operate under different temporal resolutions consistent with their typical scheduling timescales. We apply our modeling framework to evaluate power-NG system outcomes for the U.S. New England region under different technology, decarbonization goals, and demand scenarios. Under a global emissions constraint, ranging between 80%–95% emissions reduction compared to 1990 levels, the least-cost solution relies significantly on using the available emissions budget to serve non-power NG demand, with power sector using only 14%–23% of the emissions budget. Increasing electrification of heating in the buildings sector results in greater reliance on wind and NG-fired plants with CCS and results in similar or slightly lower total system costs as compared to the business-as-usual demand scenario with lower electrification of end-uses. Interestingly, although electrification reduces non-power NG demand, it leads to up to 24% increase in overall NG consumption (both power and non-power) compared to the business-as-usual scenarios, resulting from the increased role for CCS in the power sector. The availability of low-cost LDES systems reduces the extent of coupling of electricity and NG systems by significantly reducing fuel (both NG and LCDF) consumption in the power system compared to scenarios without LDES, while also reducing total systems costs by up to 4.6% for the evaluated set of scenarios.

Khorramfar, Rahman & Mallapragada, Dharik & Amin, Saurabh, 2024. "Electric-gas infrastructure planning for deep decarbonization of energy systems," Applied Energy, Elsevier, vol. 354(PA). https://doi.org/10.1016/j.apenergy.2023.122176.