Session ERE2.5

ERE2.5 | Bridging the gap: climate science models and renewable energy research

Bridging the gap: climate science models and renewable energy research

Co-organized by ESSI4

Convener: Giacomo Falchetta | Co-conveners: Anasuya GangopadhyayECSECS, Rajat MasiwalECSECS, Caroline Zimm, Ashwin K Seshadri

Orals

| Thu, 18 Apr, 14:00–15:45 (CEST)

Room 0.16

Posters on site

| Attendance Fri, 19 Apr, 10:45–12:30 (CEST) | Display Fri, 19 Apr, 08:30–12:30

Hall X4

Posters virtual

| Attendance Fri, 19 Apr, 14:00–15:45 (CEST) | Display Fri, 19 Apr, 08:30–18:00

vHall X4

A worldwide transition towards “Net zero” requires electrification of diverse sectors over the coming decades. In addition to replacing existing fossil fuel-fired power plants with low-carbon energy resources, especially wind, solar and hydropower, additional capacity will need to be added. Renewable resources vary at a wide range of time scales, from minute-wise, seasonal, to interannual. Different variabilities and their spatio-temporal distribution can have their specific impacts on renewable energy systems, day-to-day operation, strategic planning and the design of “Net zero” pathways. In a changing climate, the availability patterns of renewable energy resources on various timescales are expected to change. Furthermore, considerable uncertainty underlies prediction of long-term changes in the spatio-temporal patterns of renewable resources. While energy demand often has daily and seasonal patterns that also depends on weather, this is also subject to variability and change. Given that the balance between demand and generation of electricity must always be maintained for grid reliability, there is a critical need for interdisciplinary dialogue between the climate science community and energy modeling research groups to explore renewable resource variability, in present and future scenarios, and resulting challenges for electricity grid management worldwide. It is important to identify critical challenges associated with balancing the demand and renewable generation, as well as identify methods and opportunities to address the challenges in the context of a wide range of uncertainties.

Studies may include (but are not limited to):

• Different ways to address the present seasonality of renewable resources and their expected changes in the future
• Uncertainties associated with future resource availability patterns
• Balancing of demand and supply of energy in present and future using different techniques such as bulk energy storage, maintaining an excess of wind-solar capacity, and demand-side management
• Economics and policy implications of the methods to maintain grid reliability
• Spatio-temporal complementarity between the availability patterns of different renewable energy resources
• Methods to maximize techno-economic synergies between different renewable resources and their hybridisation in the context of variability
• Data needs from climate science based modelling, to advance understanding of renewable energy sources