The impact of GHG emission reduction projects connected to the grid

How much will GHG emissions of the complete system be reduced by implementing the project?

How do you calculate the final GHG emission reductions resulting from an energy efficiency or renewable energy project? One of the complexities of this task is that the applications are in most cases connected to the grid. As a result, not only the local effects need to be calculated, but also the effect on the entire grid including all of its power plants.

A joint project of the World Resources Institute (WRI) and the World Business Council for Sustainable Development (WBCSD) has drawn up some excellent guidelines for executing this challenging task. The Guidelines, while designed to be used by governments and business leaders, are also interesting reading for anyone eager to gain more insight into the electricity grid as a system with all its intricate interactions and decision factors.

What’s the baseline scenario?

The GHG emission reductions by the activity should be calculated relative to a baseline. One of the complexities is to determine these baseline emissions.

They can be defined as the GHG emissions from the sources of electricity that are avoided by the project. These can be of two kinds:

1. Avoided emissions of the operation of existing power plants on the grid, called the Operational Margin (OM)
2. Avoided emissions of the construction and operation of new power plants on the grid, called the Built Margin (BM)

Each project has baseline emissions consisting of a weighted sum of Built Margin and Operational Margin emissions.

The Built Margin emissions can be estimated from the GHG emission rates of recent capacity additions, or in some cases, from planned capacity and capacity currently under construction.

Estimating the Operational Margin emissions requires identifying which power plants are operating within the margin (last to be switched on-line, first to be switched off-line) during times when the project activity is operating. This can be a complex and data intensive task.

Does it meet demand for new capacity?

Another difficult task is to determine to which degree the project has an effect on the Built Margin and to which degree on the Operational Margin. Or in other words: to what extent does the project’s activity meet the demand for new capacity, and therefore avoid the building of other new capacity units.

There are three questions to consider in this regard:

1. Does demand for new capacity exist? This will almost always be the case.
2. Is the project activity considered as a source of new capacity? Some projects may be implemented which have nothing to do with the need for new capacity, for instance, energy efficiency projects.
3. What is the project’s activity capacity value? The capacity value is the amount of capacity a power plant can be statistically relied upon to provide during times of greatest demand. A single wind turbine will have a capacity value close to zero. By bundling several wind turbines, this can raise to, for instance, 10 per cent (‘the wind will always be blowing somewhere’). The capacity value of a coal-fired plant on the other hand will approach 100 per cent (not 100 per cent, since the plant will experience outages at some point).

What are the grid boundaries?

A last complexity for making the baseline calculation is how to define the grid boundaries. The Guidelines suggest defining them by the grid that is under control of a single grid operator. This is a simplification though, since the project activity may also affect generation on neighbouring grids.

But when all the estimates are completed and the intended change in GHG emissions caused by the project activity is calculated, the work is still not done. There can also be 'secondary effects' from unintended changes. Examples include the GHG emissions caused by the production, refining, and transportation of biomass, or the methane emissions caused by organic decomposition in hydro reservoirs.

In short, calculating the real GHG emission reductions caused by grid coupled systems is much more complex than you would expect. The paper did a good job in throwing light on this complex matter and in creating realistic and practical guidelines.