A Framework for Assessing the Direct Energy Use of Blockchain Technology Systems
This project will lay a foundation for more analytically-sound and transparent estimates of blockchain energy use moving forward.
The potential energy implications of blockchain technologies have received much attention recently, both in the popular media and among energy and technology sector analysts. The prevailing narratives span a wide spectrum of predictions, ranging from alarmistic (e.g., the carbon emissions of Bitcoin growing wildly) to optimistic (e.g., acceleration of distributed renewables via peer-to-peer energy trading). As a result, there is much confusion surrounding blockchain’s implications for energy use and its potential roles in energy transitions. The reality is that blockchain technologies are still in their infancy, with too few data and too little empirical evidence to robustly understand their implications on energy use, whether good and bad. This project will lay a foundation for more analytically-sound and transparent estimates of blockchain energy use moving forward.
How can we build more uniform and credible estimates of the energy consumption of blockchain technologies?
In particular, how do various factors involved in the blockchain transaction process contribute to a model of the technology’s energy consumption?
The project will consist of four key tasks: (1) a review of major blockchain applications (including, but not limited to cryptocurrencies) and the equipment types comprising the associated blockchain technology systems; (2) establishment of a best-practice analysis framework for estimating the direct energy use of blockchain technology system components; (3) development of a future research agenda for applying the proposed analytical framework; and (4) direct energy use measurements of a cryptocurrency mining computer to begin filling empirical data gaps on the energy intensity of algorithm solving.
The project will provide blockchain energy researchers with a much-needed, best practice-based analytical structure, thereby enabling greater data sharing and inter-study comparability, leading to more transparent and replicable results to better inform future policy and blockchain technology adoption decisions.