Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV
Journal article, 2021

Due to data restrictions and power system complexity issues, it is difficult to estimate grid capacity for solar PV on regional or national scales. We here present a novel method for estimating low-voltage grid capacity for residential solar PV using publicly available data. High-resolution GIS data on demographics and dwelling dynamics is used to generate theoretical low-voltage grids. Simplified power system calculations are performed on the generated low-voltage grids to estimate residential solar PV capacity with a high temporal resolution. The method utilizes previous developments in reference network modelling and solar PV hosting capacity assessments. The method is demonstrated using datasets from Sweden, UK and Germany. Even though the method is designed to estimate residential solar PV grid capacity, the first block of the method can be utilized to estimate grid capacity or impacts from other residential end-use technologies, such as electric heating or electric vehicle charging. This method presents: • A method for estimating peak demand based on population density and dwelling type. • Generation of low-voltage grids based on peak demand. • Sizing of transformers and cables based on national low-voltage regulations and standards.

Residential solar PV

End-use technologies

Open LV-Grid Generator

Hosting capacity

Low-voltage grid

Gis

Author

Elias Hartvigsson

Chalmers, Space, Earth and Environment, Energy Technology, Energy Technology 2

Mikael Odenberger

Chalmers, Space, Earth and Environment, Energy Technology

Peiyuan Chen

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

Emil Nyholm

Chalmers, Space, Earth and Environment, Energy Technology

MethodsX

2215-0161 (eISSN)

Vol. 8 101431

Subject Categories

Energy Systems

Probability Theory and Statistics

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1016/j.mex.2021.101431

PubMed

34434853

More information

Latest update

7/8/2021 2