Journal of Environmental Science International (한국환경과학회지)

The Korean Environmental Sciences Society (한국환경과학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Energy Consumption Estimation Model Using Multiple Regression Analysis

다중회귀분석을 활용한 하수처리시설 에너지 소비량 예측모델 개발

  • Shin, Won-Jae (Tae Sung Environment Institute Co., Ltd.) ;
  • Jung, Yong-Jun (Department of Environmental Engineering, Catholic University of Pusan) ;
  • Kim, Ye-Jin (Department of Environmental Engineering, Catholic University of Pusan)
  • 신원재 ((주)태성종합환경연구소) ;
  • 정용준 (부산가톨릭대학교 환경공학과) ;
  • 김예진 (부산가톨릭대학교 환경공학과)
  • Received : 2015.09.08
  • Accepted : 2015.10.08
  • Published : 2015.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

Wastewater treatment plant(WWTP) has been recognized as a high energy consuming plant. Usually many WWTPs has been operated in the excessive operation conditions in order to maintain stable wastewater treatment. The energy required at WWTPs consists of various subparts such as pumping, aeration, and office maintenance. For management of energy comes from process operation, it can be useful to operators to provide some information about energy variations according to the adjustment of operational variables. In this study, multiple regression analysis was used to establish an energy estimation model. The independent variables for estimation energy were selected among operational variables. The $R^2$ value in the regression analysis appeared 0.68, and performance of the electric power prediction model had less than ${\pm}5%$ error.

Keywords

References

  1. Amand. L, and Carlsson, B., 2012, Optimal aeration control in a nitrifying activated sludge process, Water Research, 46, 2101-2110. https://doi.org/10.1016/j.watres.2012.01.023
  2. Cho, E. S., Han, D. H., Ha, J. S., 2012, Energy efficiency evaluation of publicly owned wastewater utilities, Journal of Environmental Policy, 11(4), 85-105. https://doi.org/10.17330/joep.11.4.201212.85
  3. Camdevren, H., Nilsun, D., Arzu, K., Keskyn, S., 2005, Use of principal component scores in multiple linear regression models for prediction of Chlorophyll-a in reservoirs. Ecological Modelling, 181, 581-589. https://doi.org/10.1016/j.ecolmodel.2004.06.043
  4. Ekman. M., Bjorlenius, B., Andersson, M., 2006, Control of the aeration volume in an activated sludge process using supervisory control strategies. Water Research, 40, 1668-1676. https://doi.org/10.1016/j.watres.2006.02.019
  5. Fernandez, F. J., Castro, M. C., Rodrigo, M. A., and Canizares, P., 2011, Reduction of aeration costs by tuning a multi-set point on/off controller: A case study, Control Engineering Practice, 19(10), 1231-1237. https://doi.org/10.1016/j.conengprac.2011.07.003
  6. Ham, H. B., 2007, Data analysis and SAS programming, 328.
  7. Hernandez-Sancho, F., Molinos-Senante, M., and Sala- Garrido, R., 2011, Energy efficiency in Spanish waste -water treatment plants: A non-radial DEA approach. Science of the Total Environment, 409(14), 2693-2699. https://doi.org/10.1016/j.scitotenv.2011.04.018
  8. Kim, M. H., Ji, S. H., Chang, J. H., 2014, A study on energy saving effect from automatic control of air flowrate and estimation of optimal DO concentration in oxic reactor of wastewater treatment plant, Journal of Energy Engineering, 23(2), 49-56. https://doi.org/10.5855/ENERGY.2014.23.2.049
  9. Korean Society of Water and Wastewater, 2006, Research on energy saving strategies at public sewerage system.
  10. Liu, C., Li, S., and Zhang, F., 2011, The oxygen transfer efficiency and economic cost analysis of aeration system in municipal wastewater treatment plant. Energy Procedia. 5., 5, 2437-2443. https://doi.org/10.1016/j.egypro.2011.03.419
  11. Ministry of Environment, 2010, Basic plan for energy saving at public wastewater treatment plants.
  12. Ministry of Environment, 2013, Report on the manage -ment and operation of public wastewater treatment plants.
  13. Noh, H., 2005, Theory and application of multivariate statistical analysis using Excel and SPSS, Hyungsul, 244-261.
  14. Ovezea, A., 2009, Saving energy: Using fine bubble diffusers. Saving energy: Using fine bubble diffusers, Filtration & Separation, 46(1), 21-27. https://doi.org/10.1016/S0015-1882(09)70033-3
  15. Park, S. H., Cho, S. S., Kim, S. S., 2009, Understanding and application of SPSS 17.0, 261-270.
  16. Sung, T. J., 2007, Easy statistics using SPSS/AMOS, 263-265.
  17. Yoon, J. W., Kim, C. Y., Choi, C. K., 2014, Case studies of energy-saving method for renewable energy installa -tion in sewage treatment plant, Journal of Korean institute of illuminating and electrical installation engineers, 28(4), 42-48. https://doi.org/10.5207/JIEIE.2014.28.4.042