Capturing features of hourly-resolution energy models through statistical annual indicators

Long term-energy planning has gradually moved towards finer temporal and spatial resolutions of the energy system to design the decarbonization of the society. However, integrated assessment models (IAMs), focusing on a broader concept of sustainability transition, are typically yearly-resolution models which complicates capturing the specific supply-demand dynamics, relevant in the transition towards renewable energy sources (RES). Different methods for introducing sub-annual information are being used in IAMs, but the hourly representation of variable RES remains challenging.This article presents a method to translate the main dynamics of an hourly-resolution energy model into a yearly-resolution model. Here we test our method with the current European Union region (EU-27) by config-uring and applying the hourly-resolution EnergyPLAN. Multiple linear regression analysis is applied to 174960 simulations (set by varying 39 inputs by clusters and reaching 100% renewable systems), relating the adjusted capacity factors of the technologies as well as the variation of electricity demand and natural gas consumption as a function of the options installed to manage the variable RES. The obtained results allow validation of the developed approach, which shows to be flexible and easily generalizable enough to be applied to any couple of hourly and annual-resolution models and/or country.

Automated summary

Long-term energy planning is shifting towards finer temporal and spatial resolutions to achieve decarbonization. However, current integrated assessment models lack the ability to capture the specific dynamics of supply and demand in the transition to renewable energy sources. This article presents a method to translate an hourly-resolution energy model into a yearly-resolution model and validates it using the European Union region.