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A platform for research: civil engineering, architecture and urbanism
Data-Driven Short-Term Forecasting of Residential Building Energy Demand: A Case Study
https://orcid.org/http://orcid.org/0000-0003-1304-8591
https://orcid.org/http://orcid.org/0000-0002-8240-4425
The energy consumption from buildings in Poland, as well as the corresponding CO2 emissions, are high. A significant potential for energy-efficiency improvement for buildings can be achieved either by long- or short-term strategies. Long-term actions, in particular building refurbishments, are effective approaches to obtain significant energy savings; yet a huge financial contribution is required. On the other hand, short-term methods can be considered as less expensive strategies for energy efficiency and sustainability improvement of buildings. Energy demand control and optimization, and constant energy consumption monitoring stood among other easy-to-apply strategies.
The data-driven short-term forecasting of energy demand for heating and cooling for a case-study residential single-family house in Poland is presented. The analyzed building was examined on-site to evaluate its performance and characteristics. The performed measurements were used as input data for building energy modeling (BEM) by means of the Energy Plus software. The white-box (WB) method was applied to generate a time-series database, further used for predictions of future energy consumption. This paper presents an approach for short-term forecasts based on the autoregressive (AR) model. The predicted time-series of operation loads for the examined single-family house assumes that the quality of the indoor climate is not compromised. Additionally, this study skipped the unpredictable human-related factors: residents’ behavior is assumed as a pattern. Various climate data for the selected localizations of Poland are examined as the critical factor affecting building energy consumption. The examination of the forecasting errors is carried out, compared with the outputs from the WB model. This work aims to evaluate the accuracy of predictions regarding the energy response of the building for different climate conditions.
Data-Driven Short-Term Forecasting of Residential Building Energy Demand: A Case Study
https://orcid.org/http://orcid.org/0000-0003-1304-8591
https://orcid.org/http://orcid.org/0000-0002-8240-4425
The energy consumption from buildings in Poland, as well as the corresponding CO2 emissions, are high. A significant potential for energy-efficiency improvement for buildings can be achieved either by long- or short-term strategies. Long-term actions, in particular building refurbishments, are effective approaches to obtain significant energy savings; yet a huge financial contribution is required. On the other hand, short-term methods can be considered as less expensive strategies for energy efficiency and sustainability improvement of buildings. Energy demand control and optimization, and constant energy consumption monitoring stood among other easy-to-apply strategies.
The data-driven short-term forecasting of energy demand for heating and cooling for a case-study residential single-family house in Poland is presented. The analyzed building was examined on-site to evaluate its performance and characteristics. The performed measurements were used as input data for building energy modeling (BEM) by means of the Energy Plus software. The white-box (WB) method was applied to generate a time-series database, further used for predictions of future energy consumption. This paper presents an approach for short-term forecasts based on the autoregressive (AR) model. The predicted time-series of operation loads for the examined single-family house assumes that the quality of the indoor climate is not compromised. Additionally, this study skipped the unpredictable human-related factors: residents’ behavior is assumed as a pattern. Various climate data for the selected localizations of Poland are examined as the critical factor affecting building energy consumption. The examination of the forecasting errors is carried out, compared with the outputs from the WB model. This work aims to evaluate the accuracy of predictions regarding the energy response of the building for different climate conditions.
Data-Driven Short-Term Forecasting of Residential Building Energy Demand: A Case Study
https://orcid.org/http://orcid.org/0000-0003-1304-8591
https://orcid.org/http://orcid.org/0000-0002-8240-4425
The energy consumption from buildings in Poland, as well as the corresponding CO2 emissions, are high. A significant potential for energy-efficiency improvement for buildings can be achieved either by long- or short-term strategies. Long-term actions, in particular building refurbishments, are effective approaches to obtain significant energy savings; yet a huge financial contribution is required. On the other hand, short-term methods can be considered as less expensive strategies for energy efficiency and sustainability improvement of buildings. Energy demand control and optimization, and constant energy consumption monitoring stood among other easy-to-apply strategies.
The data-driven short-term forecasting of energy demand for heating and cooling for a case-study residential single-family house in Poland is presented. The analyzed building was examined on-site to evaluate its performance and characteristics. The performed measurements were used as input data for building energy modeling (BEM) by means of the Energy Plus software. The white-box (WB) method was applied to generate a time-series database, further used for predictions of future energy consumption. This paper presents an approach for short-term forecasts based on the autoregressive (AR) model. The predicted time-series of operation loads for the examined single-family house assumes that the quality of the indoor climate is not compromised. Additionally, this study skipped the unpredictable human-related factors: residents’ behavior is assumed as a pattern. Various climate data for the selected localizations of Poland are examined as the critical factor affecting building energy consumption. The examination of the forecasting errors is carried out, compared with the outputs from the WB model. This work aims to evaluate the accuracy of predictions regarding the energy response of the building for different climate conditions.
Data-Driven Short-Term Forecasting of Residential Building Energy Demand: A Case Study
Lecture Notes in Civil Engineering
Berardi, Umberto (editor) / Zygmunt, Marcin (author) / Gawin, Dariusz (author)
International Association of Building Physics ; 2024 ; Toronto, ON, Canada
2024-12-19
7 pages
Article/Chapter (Book)
Electronic Resource
English
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