A prototype tool for automatically generating energy-saving advice based on smart meter data
- 60 Downloads
As many countries and regions have started large-scale deployment of smart meters, there is a growing amount of data on electricity use available for energy efficiency services. We have developed a novel tool that, based on smart meter data, automatically generates customised energy-saving advice to commercial and industrial customers. This type of audit tool could enormously expand the target of energy audits to almost all small- and medium-sized enterprises (SMEs) with smart metering at a low cost per customer. In this paper, we explain the structure of and approaches that we used in our prototype tool, such as fault detection, energy disaggregation, social comparison and benchmarking and selective visualisation. We also show test case results for the tool by using smart meter data from 34 public buildings in Japan. While the prototype tool presented in this paper has some limitations, the approach and the basic structure of the tool are valuable and provide the basis for more sophisticated tools.
KeywordsSmart meter Energy audit Energy-saving advice Automated tool Small- and medium-sized enterprises
The authors would like to thank the city government for permission to use the electricity demand data of their buildings. This paper is based on a Japanese report by the authors (Komatsu et al. 2016) with substantial modifications.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Agency for Natural Resources and Energy of Japan [ANRE] (2011). Estimation of the demand structure in the summer peak day in the TEPCO region. Tokyo: Agency for Natural Resources and Energy of Japan. http://www.meti.go.jp/setsuden/20110513taisaku/16.pdf. Accessed 30 March 2017. (in Japanese).
- Agency for Natural Resources and Energy of Japan [ANRE] (2014). Current status of and support policies for energy efficiency in Japan. Tokyo: Agency for Natural Resources and Energy of Japan. http://www.meti.go.jp/committee/sougouenergy/shoene_shinene/sho_ene/pdf/005_02_00.pdf. Accessed 20 October 2017. (in Japanese).
- Agency for Natural Resources and Energy of Japan [ANRE] (2015). Current status of development of the switching system and installation of smart meters in utility companies. Tokyo: Agency for Natural Resources and Energy of Japan. http://www.meti.go.jp/committee/sougouenergy/denryoku_gas/kihonseisaku/pdf/001_07_01.pdf. Accessed 20 October 2017. (in Japanese).
- Agency for Natural Resources and Energy of Japan [ANRE] (2017). Energy balance table for FY2015. Tokyo: Agency for Natural Resources and Energy of Japan. http://www.enecho.meti.go.jp/statistics/total_energy/results.html. Accessed 20 October 2017. (in Japanese).
- Cooper, A. (2016). Electric company smart meter deployments: foundation for a smart grid. Washington DC: Institute for Electric Innovation, The Edison Foundation.Google Scholar
- Darby, S. (2006). The effectiveness of feedback on energy consumption. A review for DEFRA of the literature on metering, billing, and direct displays. Environmental Change Institute, University of Oxford. http://www.eci.ox.ac.uk/research/energy/downloads/smart-metering-report.pdf. Accessed 30 March 2017.
- Electric Power Research Institute [EPRI]. (2009). Residential electricity use feedback: a research synthesis and economic framework. California: Electric Power Research Institute.Google Scholar
- Energy Conservation Center Japan [ECCJ]. (2008). Tuning manual for energy efficiency. Tokyo: Energy Conservation Center Japan.Google Scholar
- Energy Conservation Center Japan [ECCJ]. (2009). Energy conservation in office buildings. Tokyo: Energy Conservation Center Japan.Google Scholar
- Federation of Electric Power Companies of Japan [FEPC] (2013). Status of the electric power industry. Federation of Electric Power Companies of Japan. (in Japanese).Google Scholar
- Gruber, E., Fleiter, T., Mai, M., & Frahm, B. (2011). Efficiency of an energy audit programme for SMEs in Germany: results of an evaluation study. Proceedings of ECEEE 2011 Summer Study, 663–673.Google Scholar
- Hyvärinen, J. et al. (Eds.) (1999). Real time simulation of HVAC systems for building optimisation, fault detection and diagnostics, Technical synthesis report, Energy Conservation in Buildings and Community Systems Programme (IEA ECBCS) Annex 25, International Energy Agency.Google Scholar
- Industrial Assessment Center [IAC] (2017). IAC Database. https://iac.university/#database. Accessed 20 October 2017.
- Jagpal, R. (Ed.) (2006). Technical synthesis report Annex 34: computer aided evaluation of HVAC system performance, Energy Conservation in Buildings and Community Systems Programme (IEA ECBCS), International Energy Agency.Google Scholar
- Kimura, O., & Noda, F., (2010). Effectiveness of regulations on firms by Japanese Energy Conservation Law. Report No.Y09010. Tokyo: Central Research Institute of Electric Power Industry. (in Japanese).Google Scholar
- Komatsu, H., Kimura, O., Nishio, K., & Mukai, T. (2016). An automated energy report generation tool based on smart meter data: a conceptual design aiming at information services for commercial customers. Report No. Y15004. Tokyo: Central Research Institute of Electric Power Industry. (in Japanese).Google Scholar
- Masukawa, Y., Kimura, Y., & Matsuoka, S. (2012). R&D of fault detection techniques on energy consumption in building services part 18: practical development of energy fault detection system. Technical papers of annual meeting, The society of heating, air-conditioning and sanitary engineers of Japan, 2012, 485–488. (in Japanese).Google Scholar
- Masukawa, Y., Togari, S., Miura, K., & Matsuoka, S. (2007). R&D of fault detection techniques on energy consumption in building services part 1: objective of the R&D and definition of energy fault, Technical papers of annual meeting, The society of heating, air-conditioning and sanitary engineers of Japan, 2007, 1039–1042. (in Japanese).Google Scholar
- Meier, A., Bedir, K., Hirayama, S., & Nakagami, H. (2015). Japan’s 6 GW lunch break. Proceedings of ECEEE Summer Study, 2015, 2003–2007.Google Scholar
- Mogilner, L. (2014). Business energy reports pilot results, presented at Behaviour, Energy, and Climate Change Conference (BECC) 2014, 7–10 December 2014, Washington D.C.Google Scholar
- Mukai, T., Nishio, K., Komatsu, H., & Kimura, O. (2016). Classifying air conditioning electricity consumption of commercial buildings using automated daily pattern filtering, summaries of technical papers of Annual Meeting, Architectural Institute of Japan. Environmental Engineering I, 2016, 797–798.Google Scholar
- Roth, K., Llana, P., Westphalen, D., & Brodrick, J. (2005). Automated whole building diagnostics. ASHRAE Journal, 47(5), 82–84.Google Scholar
- Schleich, J., & Fleiter, T. (2017). Effectiveness of energy audits in small business organizations. Resource and Energy Economics. https://doi.org/10.1016/j.reseneeco.2017.08.002.
- Shah, S. (2014). Rapid building assessment project, final report, ESTCP Project EW-201261, Environmental Security Technology Certification Program, Department of Defence. https://www.serdp-estcp.org/Program-Areas/Energy-and-Water/Energy/Conservation-and-Efficiency/EW-201261. Accessed 30 March 2017.
- Smith, B. A. (2014). Business energy reports: first year’s evaluation results, presented at Behaviour, Energy, and Climate Change Conference (BECC) 2014, 7–10 December 2014, Washington D.C.Google Scholar
- Sorrell, S., Schleich, J., & Scott, S. (eds.) (2000). The economics of energy efficiency: barriers to cost-effective investment. Edward Elgar.Google Scholar
- Stewart, J. (2015). Energy savings from business energy feedback, presented at Behaviour, Energy, and Climate Change Conference (BECC) 2015, 18–21 October 2015, Sacramento.Google Scholar
- Thaler, R. H., & Sunstein, C. R. (2008). Nudge: improving decisions about health, wealth and happiness. Penguin Books.Google Scholar
- Thollander, P., Paramonova, S., Cornelis, E., Kimura, O., Trianni, A., Karlsson, M., Cagno, E., Morales, I., & Jimenez Navarro, J. P. (2015a). International study on energy end-use data among industrial SMEs (small and medium-sized enterprises) and energy end-use efficiency improvement opportunities. Journal of Cleaner Production, 104, 282–296.CrossRefGoogle Scholar
- US Energy Information Administration [USEIA]. (2016). Electric power annual 2015. Washington DC: US Department of Energy.Google Scholar
- USmartConsumer Project (2016). European Smart Metering Landscape Report 2016, USmartConsumer Project. http://www.escansa.es/usmartconsumer/documentos/USmartConsumer_European_Landscape_Report_2016_web.pdf. Accessed 20 Octber 2017.
- Yoshida, S., Ogawa, H., & Sadohara, S. (2015). Study on the future city in the global environment age, Part7: Survey on the end-use energy consumption unit of the buildings. Summaries of technical papers of Annual Meeting, Architectural Institute of Japan, 2015, Environmental Engineering I, 661–662. (in Japanese).Google Scholar