Colloquia

Summary

Electrical power in the grid is generated by an increasingly dynamic composition of sources. This is a result of intermittent renewable energy sources and dynamic power consumption. Different generation types show large variations in life-cycle environmental impact. Therefore, the environmental impact of electricity use is time dependent. 

This thesis presents a methodology that determines the dynamic greenhouse gas emission intensity of an electricity grid. Additionally a model tracking the GHG emission intensity of the Dutch grid, the Open Dynamic Electricity Composition Tracker (ODECT), is presented and validated with real measured data. ODECT results show a steady decline as well as growing volatility of the GHG emission intensity.

In conclusion, current methods of carbon accounting fail to show the large potential for GHG emission reduction through shifting power consumption in time. Insight in the dynamic aspects of the electricity mix allow for lowering the carbon footprint of power consumption though the use of demand side management. Time granular carbon accounting provides a fair method of allocating emissions to consumers. Furthermore, the transition towards a low-carbon electricity supply will be accelerated by standard open methodology as opposed to the multiple incomplete models that are accessible today.