Green neighbourhoods in low voltage networks: measuring impact of electric vehicles and photovoltaics on load profiles

Authored by Danica Vukadinovic Greetham, Laura Hattam

Date Published: 2017

DOI: 10.1007/s40565-016-0253-0

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

In the near future, various types of low-carbon technologies (LCTs) are expected to be widely employed throughout the United Kingdom. However, the effect that these technologies will have at a household level on the existing low voltage (LV) network is still an area of extensive research. We propose an agent based model that estimates the growth of LCTs within local neighbourhoods, where social influence is imposed. Real-life data from an LV network is used that comprises of many socially diverse neighbourhoods. Both electric vehicle uptake and the combined scenario of electric vehicle and photovoltaic adoption are investigated with this data. A probabilistic approach is outlined, which determines lower and upper bounds for the model response at every neighbourhood. This technique is used to assess the implications of modifying model assumptions and introducing new model features. Moreover, we discuss how the calculation of these bounds can inform future network planning decisions.

Tags

Agent based modelling electric vehicles Technologies Photovoltaics Low voltage networks