The power sector’s transition toward an increasingly low-carbon system is well under way. The transport sector is starting to turn a corner with the rise of electrified transport, but progress in reducing the carbon footprint in the industry and buildings sector is still lagging.
The report provides a detailed update on the Economic Transition Scenario, or ETS our baseline assessment of how the energy sector may evolve from today as a result of cost-based technology changes. We present out Economic Transition Scenario, explore the impact of the current global energy crisis and the war in Ukraine on key modeling parameters, and then provide an overview of the global key drivers that shape this economics-led pathway and sectoral results.
The ETS is our baseline assessment of how the energy sector might evolve from today as a result of cost-based technology changes. It includes detailed modeling on the power sector, transport, industry and buildings. The ETS combines near-term market activity, the uptake of new consumer-facing energy products, least-cost system modeling and economics-led analysis to describe the deployment and diffusion of commercially available technologies. Technology transition only occurs in this scenario where it outcompetes existing technologies or lowers system cost. Global population and economic growth continue in line with historic trends and demographic shifts, taking into account changing demand.
Our scenarios incorporate legislated and firm near-term policy, but do not assume either country-level, or corporate, energy and climate objectives are met. In this way the ETS describes how the energy sector might evolve in the absence of further major climate policy intervention.
BNEF uses a sector-led, bottom-up modeling approach with country-level granularity for all major sub-sectors of the energy economy. The power sector outlook is produced with BNEF’s NEFM-2 power model, which simulates the power sector at the end-use level in 49 markets and regions. The model takes into account 25 electricity generation classes, deployment of energy storage, demand flexibility, on-grid hydrogen electrolyzers and grid constraints. It then uses an hourly supply-demand model to 2050 to build an optimized least-cost system capable of meeting peak demand.
