Joint and conditional dependence modeling of peak district heating demand and outdoor temperature: a copula-based approach
F. Marta L. Di Lascio,
Andrea Menapace () and
Maurizio Righetti ()
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Andrea Menapace: Free University of Bolzano‐Bozen, Faculty of Science and Technology, Italy
Maurizio Righetti: Free University of Bolzano‐Bozen, Faculty of Science and Technology, Italy
No BEMPS53, BEMPS - Bozen Economics & Management Paper Series from Faculty of Economics and Management at the Free University of Bozen
This paper examines the complex dependence between the peak district heating demand and the outdoor temperature. The final aim is to provide the probability law of the heat demand given extreme weather conditions and derive useful implications for the management and the production of thermal energy. We propose a copula-based approach and consider the case of the district of the city of Bozen-Bolzano. The analysed data concerns daily maxima of heat demand observed from January 2014 to November 2017 and the corresponding outdoor temperature. We find that the marginal behavior of the univariate time series of the district heating demand and the temperature is well-described by autoregressive integrated moving average models. Moreover, the selected copula model exhibits a symmetric dependence between the two investigated phenomena that tend to comove closely together during the whole heating season. Taking into account the conditional behaviour of the heat demand given the temperature leads to find that the demand is strongly affected by the temperature and, in case of extreme climatic events, the demand of thermal energy reach a peak with high probability. These findings motivate for improving the production schedule, the system design, and the operational strategies.
Keywords: ARIMA models; Copula function; Conditional probability; District heating system; Outdoor temperature; Peak heat demand (search for similar items in EconPapers)
JEL-codes: C10 C32 P28 (search for similar items in EconPapers)
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