Some have argued that the wide use of Artificial Intelligence (AI) will require substantial amounts of energy and that this will overwhelm any environmental gains from improved energy use efficiency and emission reduction. However, there are other views. LSE's Grantham Institute and Systemiq produced a study last year claiming that AI applications in just three sectors (power, food, and mobility) could reduce global greenhouse gas emissions by 3.2 to 5.4 billion metric tons annually by 2035. That would more than offset all projected data centre emissions from AI across the entire global economy in the same period, and move us 36% closer to an ambitious 2035 emissions reduction trajectory versus business as usual. A recent overview of the issues said that ‘This would be a huge win, and powered by only three sectors’. But it also reported that a more recent paper from MIT is much more cautious: ‘AI is likely to worsen climate change even if it stimulates large emi...
Integrated renewables- the cheapest option IRENA has develop a new energy costing system and found that renewables plus storage could supply firm power at low system costs- see my earlier post . Another new metric for assessing the total levelized cost of energy (LCOE) has also emerged with equally striking results. It puts the costs of a mix of offshore wind & solar at about €46/MWh in a future climate-neutral energy system for Denmark- less than half the equivalent cost of nuclear under the same conditions. Thats the conclusion of a new multi-authored peer reviewed study with inputs from Denmark, Finland, Chile, Croatia and the UK. It introduces a new system-based LCOE metric - referred to as SLCOE. It says that ‘while the LCOE is only a function of the respective technology, the SLCOE is a function of both the technology and the energy system context in which it operates’. It shows that ‘the SLCOE of wind power and solar photovoltaics can be much lo...