Advanced SearchSearch Tips
A Validation Study of Remote Energy Diagnosis Algorithm Performance through Actual Building Energy Data Analysis
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Validation Study of Remote Energy Diagnosis Algorithm Performance through Actual Building Energy Data Analysis
Jeong, Seong-Hyeok; Kim, Hwa-Young; Lee, Ha-Ny; Leigh, Seung-Bok;
Energy reduction and efficiency in existing buildings are an essential part of energy saving in building sector. Measurement of energy consumption by end-use and analysing data to find opportunities in improvement of energy performance are the key steps and the most important part of energy saving activities for buildings. This paper introduces and studies a recently-developed remote energy diagnosis program which has a new approach in building energy audit and analysis processes. The program consists of two algorithms - disaggregation and prediction. The first one is an algorithm for disaggregation of electricity consumption by end-use which divides the actual whole electricity consumption data of a building into three different end-use loads - heating & cooling load, lighting & other power supply load, and base load. Building characteristic factors in both heating and cooling periods are calculated for each building in this algorithm. The second algorithm provides the prediction of weather-corrected electricity consumption of a whole building. The output of the first algorithm and present outdoor temperature are combined for the prediction of present normal electricity consumption. This program does not require any difficult-to-get information or any hardwares for measurement. The analysis procedure is a lot quicker than the traditional on-site diagnosis approach. The validation of this remote energy diagnosis program is made based on comparison with actual building electricity consumption data. The result shows that the mean bias error(MBE) is -0.12% and coefficient of variation of the root mean square error(CV) is 5.7%, which are much better results than ASHRAE standards of acceptable calibration tolerances of and 30% respectively.
Remote Energy Diagnosis;Actual Building Energy Data;BEMS;
 Cited by
건물의 실측 에너지 데이터를 통한 건물 에너지 소비 패턴 분류에 관한 연구,우혜지;최기원;김현수;어진선;조수연;백주미;김기석;이승복;

대한건축학회논문집:계획계, 2016. vol.32. 5, pp.143-151 crossref(new window)
ASHRAE Guideline, ASHRAE Guideline 14-2002, Measurement of Energy Demand Savings, SXection

KEEI (2013). Monthly Energy Statistics.

Cho, Y., Lee, S., & Woo, S. (2013). In Small and Medium Business the Government 3.0-based Big Data Utilization Policy. The Journal of IT Convergence Society for SMB, 3(1), 15-22.

Jeong, H., Park, J., Lee, Y., & Song, D. (2012). Proposal of the Energy Retrofit in a Small Sized Office Building and its Application. Korean Journal of Air-Conditioning and Refrigeration Engineering, 24(9), 663-670. crossref(new window)

Kim, D., Lee, Y., & Kim, J. (2008). An Analysis of Import and Revitalization of the Building Energy Management System for Energy-saving about Application case of the BEMS in Japan. Proceeding of Annual Conference of the Architectural Institute of Korea, Planning and Design Section, 28(1), 571-574.

Leigh, S. (2000). A Study for Predicting Building Energy Use with Regression Analysis. Korean Journal of Air-Conditioning and Refrigeration Engineering, 12(12), 1090-1097.

Moon, H. (2013). Recent Research Trends in Building Energy Management System. Korean Journal of Air-Conditioning and Refrigeration Engineering, 42(9), 54-63.

Son, H. (2014). A Study on the Major Constituent Components and the Effect of Efficiency Improvement for the BEMS. The Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, 28(1), 105-113. crossref(new window)

Seo, D., Lee, H., Leigh, S. (1998). A Study for Predicting Energy Use in an Office Building. Proceedings of the SAREK 1998 Summer Annual Conference, 1309-1316.

Seol, I., Kim, S., & Choi, D. (2012). A Study of the Current Status of Domestic Building Energy Management System and the Correct way for Improvement. Proceedings of Annual Summer Conference of the Korean Institute of Information Technology, 58-63.