The application of predictive stochastic model based on Monte Carlo method in building energy saving renovation

• Autorzy: Xiao Juxian

Identyfikatory

DOI

10.24425/ace.2024.151878

• Języki publikacji: EN

Abstrakty

EN

This research has established an energy consumption prediction model based on the Monte Carlo method to resolve the energy-saving transformation problem. First, simplify the building to construct the proposed model. Second, through the principle of building energy balance and Monte Carlo method, the cooling and heat demand model of regional buildings and the energy consumption prediction model of regional buildings are built. Finally, the energy consumption simulation and energy consumption prediction of the regional building complex after energy-saving renovation are carried out. The experiment shows that the building energy consumption in July and August was relatively high, reaching 2.36E+14 and 2.4E+14, respectively. The energy consumption in April and November was relatively low, reaching 1.2E+14 and 1.4E+14, respectively. The highest prediction error was in November, reaching 12%. The lowest prediction error was in January and February, only about 2%. The error of monthly energy consumption predicted by Monte Carlo method is less than 12%, the Root-mean-square deviation is 5%, and the error between predicted and actual annual total energy consumption is only about 2%. By comparing the predicted energy consumption after energy-saving renovation with before, the energy-saving rate reached about 20%. The research results indicate that the proposed Monte Carlo based predictive stochastic model exhibits good predictive performance in building energy-saving renovation, providing theoretical guidance and reference for feasibility studies, planning, prediction, decision-making, and optimization of building energy-saving renovation.

Słowa kluczowe

EN

energy renovation; Monte Carlo method; energy demand; regional building; data mining

PL

renowacja energetyczna; metoda Monte Carlo; zapotrzebowanie na energię; budynek regionalny; eksploracja danych

• Wydawca: Komitet Inżynierii Lądowej i Wodnej PAN ; Politechnika Warszawska, Wydział Inżynierii Lądowej
• Czasopismo: Archives of Civil Engineering
• Rocznik: 2024
• Tom: Vol. 70, nr 4
• Strony: 43--56
• Opis fizyczny: Bibliogr. 21 poz., il.

Twórcy

autor

Xiao Juxian

• Department of Architectural Engineering, Shijiazhuang University of Applied Technology, Shijiazhuang, China

• https://orcid.org/0009-0007-6568-2785

Bibliografia

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