Why 100% renewable energy is not enough

Carbon accounting is challenging. Determining the impact on the environment from generating energy at a given power plant is the first hurdle. Electricity from one source cannot be distinguished from another, which makes the impact of consumption even more difficult to estimate. finally, investment decisions made today will have impacts for decades to come.

As more precise data become routinely available, they should be used to measure the carbon footprint of electricity consumption and production. Carbon-accounting metrics aim to associate a certain environmental quality with the power flowing through the grid. It should become standard for such metrics to consider information on a local level and at a sub-daily timescale.

In other locations, nighttime hours will be the cleanest, or there will be no difference between night and day. Location-specific assessments are needed. Wherever variable wind and solar generation are high, hourly carbon accounting will be required to make those assessments and guide investments.

As the fraction of renewable energy in the power grid increases, institutional targets to procure ‘‘100% renewable energy’’ should use hourly accounting to accurately measure the carbon emissions reductions achieved and can result in either less or more than 100% emissions reductions. In solar-dominated grids such as in California, hourly accounting reveals that adding new wind capacity has much greater carbon benefit than adding new solar generation. Location-specific assessments will be needed to make similar assessments for other regions, where other generation sources may hold greater environmental value. Research to inform such assessments and design transparent, precise, and meaningful carbon accounting will be of great help.

Looking to the future, achieving concomitant emissions reductions with renewable generation will also require shifting loads to take advantage of low carbon generation sources by utilizing energy storage and scheduling those loads that are flexible to better follow the availability patterns of renewables.