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Journal article

Synthesising Residential Electricity Load Profiles at the City Level Using a Weighted Proportion (Wepro) Model

From

Energy Systems Analysis, Sustainability, Department of Technology, Management and Economics, Technical University of Denmark1

Department of Technology, Management and Economics, Technical University of Denmark2

De La Salle Catholic University3

Sam Ratulangi University4

Sustainability, Department of Technology, Management and Economics, Technical University of Denmark5

CITIES - Centre for IT-Intelligent Energy Systems, Centers, Technical University of Denmark6

It is important to understand residential energy use as it is a large energy consumption sector and the potential for change is of great importance for global energy sustainability. A large energy-saving potential and emission reduction potential can be achieved, among others, by understanding energy consumption patterns in more detail.

However, existing studies show that it requires many input parameters or disaggregated individual end-uses input data to generate the load profiles. Therefore, we have developed a simplified approach, called weighted proportion (Wepro) model, to synthesise the residential electricity load profile by proportionally matching the city's main characteristics: Age group, labour force and gender structure with the representative households profiles provided in the load profile generator.

The findings indicate that the synthetic load profiles can represent the local electricity consumption characteristics in the case city of Amsterdam based on time variation analyses. The approach is in particular advantageous to tackle the drawbacks of the existing studies and the standard load model used by the utilities.

Furthermore, the model is found to be more efficient in the computational process of the residential sector's load profiles, given the number of households in the city that is represented in the local profile.

Language: English
Publisher: MDPI AG
Year: 2020
Pages: 3543
ISSN: 19961073
Types: Journal article
DOI: 10.3390/en13143543
ORCIDs: Kewo, Angreine , Nielsen, Per Sieverts and 0000-0002-4891-4560

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