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Evaluating self-consumption for domestic solar PV- simulation using highly resolved generation and demand data for varying occupant archetypes (Leicester, Goodier and Rowley, 2015).pdf (1.6 MB)

Evaluating self-consumption for domestic solar PV: simulation using highly resolved generation and demand data for varying occupant archetypes

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conference contribution
posted on 2016-04-27, 16:07 authored by Philip LeicesterPhilip Leicester, Chris GoodierChris Goodier, Paul Rowley
A detailed study of the on-site consumption of domestic solar PV generated electricity has been undertaken in order to gain an insight in to the relationships between annual consumption, generation and grid injection and to explore the effect of factors such as orientation and occupant behaviour on self-consumption (SC). Both empirical and simulated generation and export time series data for a large number of PV systems were analysed, and the degree to which SC is predicted by absolute generation and consumption and its variability have been quantified. SC is seen to be generally less than 50%, and the results illustrate the value of probabilistic models for predicting the socioeconomic impacts of domestic PV. As such, the results are significant for evaluating both socioeconomic impacts and distribution network loadflow implications.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Photovoltaic Science, Applications and Technology (PVSAT-11)

Pages

89 - 92 (4)

Citation

LEICESTER, P., GOODIER, C. and ROWLEY, P., 2015. Evaluating self-consumption for domestic solar PV: simulation using highly resolved generation and demand data for varying occupant archetypes. IN: Proceedings of 2015 11th Photovoltaic Science, Applications and Technology conference (PVSAT-11), Leeds, Great Britain, 15-17 April 2015, pp.89-92.

Publisher

© Solar Energy Society

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

ISBN

0904963810

Publisher version

Language

  • en

Location

University of Leeds

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