The Impact of Data Granularity of Indoor Temperature Measurements on the Calculation of Degree Days

2021 ◽  
Vol 25 (1) ◽  
pp. 1305-1316
Author(s):  
Xue Mei ◽  
Carlos Jimenez-Bescos

Abstract Degree-days are to normalise energy consumption data and furthermore can generate forecasting predictions for energy demand being used to compare between different properties across different location and years. The base temperature is the main factor to consider the accuracy of degree days. The aim of this study was to evaluate the impact of data granularity to understand its effect on a correlation between energy consumption and Degree Days. Degree Days were calculated using the standard 18.3 °C base temperature as taking in the United States of America and compare the Degree Days calculations against the calculation based on hourly, daily and monthly data for base temperature. The methodology followed is based on the analysis of 23 houses located in Texas, Austin. The properties under study are from different construction periods and with a variety of total floor areas. This study had demonstrated the effect of the granularity of the data collected to generate Degree Days and its impact on the correlation between energy consumption and degree-days for different base temperatures. While the higher correlations are achieved using a monthly granularity, this approach is not recommended due to the small number of data points and a much more preferred approach that should be taken is a daily approach, which would generate a much more reliable correlation. In this study, higher correlation values were achieved when using the standard 18.3 °C base temperature for the Degree Days calculations, 70 % correlation in daily approach versus 56.67 % using indoor temperature, showing better results across the board against the use of indoor temperature at all granularity levels.

2020 ◽  
Vol 24 (2) ◽  
pp. 364-372
Author(s):  
Xabat Oregi ◽  
Carlos Jimenez-Bescos

AbstractDegree-days are used as a forecasting tool to predict energy demand and for normalizing energy consumption to be able to compare between different properties across different years. The base temperature is the main aspect to accurately calculate degree-days. The aim of this study was to evaluate the effect of different base temperatures and their impact on the correlation between energy consumption and degree-days. The base temperature was selected as the standard 15 °C for the region, the balance temperature calculated with dynamic building simulations and the thermostat temperature setting as collected by questionnaires. The methodology followed is based on the analysis of 20 properties located in the cities of Bilbao, San Sebastian and Vitoria in northern Spain. The properties are a combination of flats and houses, from different construction periods, tenancies, occupancy and sizes. This study had highlighted the effect and impact of selecting different base temperatures for the calculation of degree-days and the correlation between energy consumption and degree-days. While the use of the balance temperature as base temperature could generate very good correlation, they were not so dissimilar from using the standard 15 °C base temperature to justify the amount of extra work required to generate the balance temperature. The use of the thermostat setting as an indication of the base temperature was not as reliable as the other base temperature methods in generating a good correlation to explain the energy consumption on the 20 properties investigated in this study.


Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3775 ◽  
Author(s):  
Khaled Bawaneh ◽  
Farnaz Ghazi Nezami ◽  
Md. Rasheduzzaman ◽  
Brad Deken

Healthcare facilities in the United States account for 4.8% of the total area in the commercial sector and are responsible for 10.3% of total energy consumption in this sector. The number of healthcare facilities increased by 22% since 2003, leading to a 21% rise in energy consumption and an 8% reduction in energy intensity per unit of area (544.8 kWh/m2). This study provides an analytical overview of the end-use energy consumption data in healthcare systems for hospitals in the United States. The energy intensity of the U.S. hospitals ranges from 640.7 kWh/m2 in Zone 5 (very hot) to 781.1 kWh/m2 in Zone 1 (very cold), with an average of 738.5 kWh/m2. This is approximately 2.6 times higher than that of other commercial buildings. High energy intensity in the healthcare facilities, particularly in hospitals, along with energy costs and associated environmental concerns make energy analysis crucial for this type of facility. The proposed analysis shows that U.S. healthcare facilities have higher energy intensity than those of most other countries, especially the European ones. This necessitates the adoption of more energy-efficient approaches to the infrastructure and the management of healthcare facilities in the United States.


Author(s):  
Lindsey Kahn ◽  
Hamidreza Najafi

Abstract Lockdown measures and mobility restrictions to combat the spread of COVID-19 have impacted energy consumption patterns. The overall decline of energy use during lockdown restrictions can best be identified through the analysis of energy consumption by source and end-use sectors. Using monthly energy consumption data, the total 9-months use between January and September for the years 2015–2020 is calculated for each end-use sector (transportation, industrial, residential, and commercial). The cumulative consumption within these 9 months of the petroleum, natural gas, biomass, and electricity energy by the various end-use sectors are compared. The analysis shows that the transportation sector experienced the greatest decline (14.38%). To further analyze the impact of COVID-19 on each state within the USA, the consumption of electricity by each state and each end-use sector in the times before and during the pandemic is used to identify the impact of specific lockdown procedures on energy use. The distinction of state-by-state analysis in this study provides a unique metric for consumption forecasting. The average total consumption for each state was found for the years 2015–2019. The total average annual growth rate (AAGR) for 2020 was used to find a correlation coefficient between COVID-19 case and death rate, population density, and lockdown duration. A correlation coefficient was also calculated between the 2020 AAGR for all sectors and AAGR for each individual end-user. The results show that Indiana had the highest percent reduction in consumption of 10.07% while North Dakota had the highest consumption increase of 7.61%. This is likely due to the amount of industrial consumption relative to other sectors in the state.


2015 ◽  
Vol 16 (SE) ◽  
pp. 97-103
Author(s):  
Allah Bakhsh Kavoosi ◽  
Shahin Heidari ◽  
Hamed Mazaherian

Growth and development of technology caused enormous transformation and change in the world after Industrial Revolution. The contemporary human has prepared the platform for their realization in many activities that the humans were unable to do it in the past time and struck the dream of their realization in their mind so that today doing many of those activities have been apparently practical by human. This accelerating growth accompanied with consuming a lot of energy where with respect to restriction of the given existing resources, it created energy crises. On the other hand, along with growth in industry and requirement for manpower and immigration from village to city and basic architectural changes in houses, which have emerged due to change in social structure it has led to change in lifestyle and type and quantity of consuming energy in contemporary architecture. Inter alia, with increase in human’s capability, cooling and heating and acoustic and lighting technologies were also changed in architecture and using mechanical system was replaced by traditional systems. Application of modern systems, which resulted from growth of industry and development of technology and it unfortunately, caused further manipulation in nature and destruction of it by human in addition to improving capability and potential of human’s creativity. With respect to growth of population and further need for housing and tendency to the dependent heating and cooling systems to them in this article we may notice that the housing is assumed as the greatest consumer of energy to create balance among the exterior and interior spaces in line with creating welfare conditions for heating and cooling and lighting. The tables of energy demand prediction in Iran show that these costs and energy consumption will be dubbed with energy control smart management in architecture.


Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7590
Author(s):  
Adam Kula ◽  
Albert Smalcerz ◽  
Maciej Sajkowski ◽  
Zygmunt Kamiński

There are many papers concerning the consumption of energy in different buildings. Most describe residential buildings, with only a few about office- or public service buildings. Few articles showcase the use of energy consumption in specific rooms of a building, directed in different geographical directions. On the other hand, many publications present methods, such as machine learning or AI, for building energy management and prediction of its consumption. These methods have limitations and represent a certain level of uncertainty. In order to compare energy consumption of different rooms, the measurements of particular building-room parameters were collected and analyzed. The obtained results showcase the effect of room location, regarding geographical directions, for the consumption of energy for heating. For south-exposed rooms, due to sun radiation, it is possible to switch heating off completely, and even overheating of 3 °C above the 22 °C temperature set point occurs. The impact of the sun radiation for rooms with a window directed east or west reached about 1 °C and lasts for a few hours before noon for the east, and until late afternoon for the west.


2021 ◽  
pp. 111657
Author(s):  
Marina Laskari ◽  
Rosa-Francesca de Masi ◽  
Stavroula Karatasou ◽  
Mat Santamouris ◽  
Margarita-Niki Assimakopoulos

Author(s):  
Lindsey Kahn ◽  
Hamidreza Najafi

Abstract Lockdown measures and mobility restrictions implemented to combat the spread of the novel COVID-19 virus have impacted energy consumption patterns, particularly in the United States. A review of available data and literature on the impact of the pandemic on energy consumption is performed to understand the current knowledge on this topic. The overall decline of energy use during lockdown restrictions can best be identified through the analysis of energy consumption by source and end-user breakdown. Using monthly energy consumption data, the total 9-months use between January and September for the years 2015–2020 are calculated for each end-use. The cumulative consumption within these 9 months of the petroleum, natural gas, biomass, and electricity energy by the various end-use sectors are compared to identify a shift in use throughout time with the calculation of the percent change from 2019 to 2020. The analysis shows that the transportation sector experienced the most dramatic decline, having a subsequent impact on the primary energy it uses. A steep decline in the use of petroleum and natural gas by the transportation sector has had an inevitable impact on the emission of carbon dioxide and other air pollutants during the pandemic. Additionally, the most current data for the consumption of electricity by each state and each end-user in the times before and during the pandemic highlights the impact of specific lockdown procedures on energy use. The average total consumption for each state was found for the years 2015–2019. This result is used calculation of yearly growth rate and average annual growth rate in 2020 for each state and end-user. The total average annual growth rate for 2020 was used to find a correlation coefficient between COVID-19 case and death rates as well as population density and lockdown duration. To further examine the relationship a correlation coefficient was calculated between the 2020 average annual growth rate for all sectors and average annual growth rate for each individual end-user.


2020 ◽  
pp. 0958305X2094403
Author(s):  
Emrah Ismail Cevik ◽  
Durmuş Çağrı Yıldırım ◽  
Sel Dibooglu

We examine the relationship between renewable and non-renewable energy consumption and economic growth in the United States. While the regime-dependent Granger causality test results for the non-renewable energy consumption and economic growth suggest bi-directional causality in both regimes, we cannot validate any causality between renewable energy consumption and economic growth. The US meets its energy demand from non-renewable sources; as such, renewable energy consumption does not seem to affect economic growth. Given the efficiency and productivity of renewable energy investments, we conclude that it is worthwhile to consider renewable energy inputs to replace fossil fuels given potential benefits in terms of global warming and climate change concerns. In this regard, increasing the R&D investments in the renewable energy sectors, increases in productivity and profitability of renewable energy investments are likely to accrue benefits in the long run.


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