CO2 emissions related to electricity, an architecture implemented in Python

Abstract

In recent years, the environmental impact of energy consumption has gained attention. In this thesis, we create an android application that shows CO2 emission intensity value of the Germany electricity grid using ENTSOE Transparency Platform API. The application shows the latest available CO2 information, total electricity production, and electricity produced by each resource type for every fifteen-minutes time intervals. In addition to this, we provided the last 24hours generation mix and CO2 emission information. Moreover, we formulate the optimization problem for scheduling of hybrid household appliances using mixed integer linear programming technique. The objective of our approach is to minimize the CO2 emission from household while considering the user preference. We scheduled the appliance based on both load shift in time and combination of multiple energy carriers. We consider electricity, hot water, and natural gas energy carriers. We use a gas boiler to produce hot water that can be stored in a hot water storage tank. Electricity and natural gas are supplied by distribution grids.