Abstract
Efficient energy production and distribution systems are urgently needed to reduce world climate change. Since modern district heating systems are sustainable energy distribution services that exploit renewable sources and avoid energy waste, in-depth knowledge of thermal energy demand, which is mainly affected by weather conditions, is essential to enhance heat production schedules. We hence propose a mixture copula-based approach to investigate the complex relationship between meteorological variables, such as outdoor temperature and solar radiation, and thermal energy demand in the district heating system of the Italian city Bozen-Bolzano. We analyse data collected from 2014 to 2017, and estimate copulas after removing serial dependence in each time series using autoregressive integrated moving average models. Due to complex relationships, a mixture of an unstructured Student-t and a flipped Clayton copula is deemed the best model, as it allows differentiating the magnitude of dependence in each tail and exhibiting both heavy-tailed and asymmetric dependence. We derive the conditional copula-based probability function of thermal energy demand given meteorological variables, and provide useful insight on the production management phase of local energy utilities.
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Acknowledgements
We thank the two anonymous reviewers for comments that greatly improved the development of this work. The first author (corresponding author F. Marta L. Di Lascio) acknowledges the support of the Free University of Bozen-Bolzano, Faculty of Economics and Management, via the project “The use of Copula for the Analysis of Complex and Extreme Energy and Climate data” (CACEEC). The second author (Andrea Menapace) acknowledges Alperia and the Bozen-Bolzano province for providing the analysed data. The third author (Maurizio Righetti) acknowledges the support via the project “Thermo Fluid Dynamics, infrastructures for applied research to business and industry in South Tyrol” (LTFD), ERDF (European Regional Development Fund) 2014-2020 Programme, CUP I52F16000850005.
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Handling Editor: Bryan F. J. Manly.
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Di Lascio, F.M.L., Menapace, A. & Righetti, M. Analysing the relationship between district heating demand and weather conditions through conditional mixture copula. Environ Ecol Stat 28, 53–72 (2021). https://doi.org/10.1007/s10651-020-00475-z
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DOI: https://doi.org/10.1007/s10651-020-00475-z