Incorporating residual temperature and specific humidity in predicting weather-dependent warm-season electricity consumption

Huade Guan, Simon Beecham, Hanqiu Xu, Greg Ingleton

    Research output: Contribution to journalArticle

    9 Citations (Scopus)

    Abstract

    Climate warming and increasing variability challenges the electricity supply in warm seasons. A good quantitative representation of the relationship between warm-season electricity consumption and weather condition provides necessary information for long-term electricity planning and short-term electricity management. In this study, an extended version of cooling degree days (ECDD) is proposed for better characterisation of this relationship. The ECDD includes temperature, residual temperature and specific humidity effects. The residual temperature is introduced for the first time to reflect the building thermal inertia effect on electricity consumption. The study is based on the electricity consumption data of four multiple-street city blocks and three office buildings. It is found that the residual temperature effect is about 20% of the current-day temperature effect at the block scale, and increases with a large variation at the building scale. Investigation of this residual temperature effect provides insight to the influence of building designs and structures on electricity consumption. The specific humidity effect appears to be more important at the building scale than at the block scale. A building with high energy performance does not necessarily have low specific humidity dependence. The new ECDD better reflects the weather dependence of electricity consumption than the conventional CDD method.

    Original languageEnglish
    Article number024021
    Pages (from-to)Art: 024021
    Number of pages10
    JournalEnvironmental Research Letters
    Volume12
    Issue number2
    DOIs
    Publication statusPublished - 2017

    Fingerprint Dive into the research topics of 'Incorporating residual temperature and specific humidity in predicting weather-dependent warm-season electricity consumption'. Together they form a unique fingerprint.

  • Cite this