A Perspective on Methods for Analysis of Measured Energy Data from Commercial Buildings

1998 ◽  
Vol 120 (3) ◽  
pp. 150-155 ◽  
Author(s):  
D. E. Claridge

This paper provides a historical perspective on the methods used to analyze measured energy use in commercial buildings. It summarizes the capabilities and uncertainties of the regression methods used in most M&V applications today and the calibrated simulation approaches used for M&V, commissioning, and end-use disaggregation. The need for graphical indices is introduced and applications of artificial neural networks, Fourier series and spectral analysis methods for M&V and data acquisition are described.

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.


Author(s):  
Philip Agee ◽  
Leila Nikdel ◽  
Sydney Roberts

This paper provides an open dataset of measured energy use, solar energy production, and building air leakage data from a 328 m2 (3,531 ft2) all-electric, zero energy commercial building in Virginia, USA. Over two years of energy use data were collected at 1-hour intervals using circuit-level energy monitors. Over six years of solar energy production data were measured at 1-hour intervals by 56 microinverters. The building air leakage data was measured post-construction per ASTM-E779 Standard Test Method for Determining Air Leakage Rate by Fan Pressurization and the United States Army Corps (USACE) Building Enclosure Testing procedure; both pressurization and depressurization results are provided. The architectural and engineering (AE) documents are provided to aid researchers and practitioners in reliable modelling of building performance. The paper describes the data collection methods, cleaning, and convergence with weather data. This dataset can be employed to predict, benchmark, and calibrate operational outcomes in zero energy commercial buildings.


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