JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Development of Energy Consumption Estimation Model Using Multiple Regression Analysis
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Development of Energy Consumption Estimation Model Using Multiple Regression Analysis
Shin, Won-Jae; Jung, Yong-Jun; Kim, Ye-Jin;
  PDF(new window)
 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 value in the regression analysis appeared 0.68, and performance of the electric power prediction model had less than error.
 Keywords
Multiple regression analysis;Energy estimation;Wastewater treatment plant;
 Language
Korean
 Cited by
 References
1.
Amand. L, and Carlsson, B., 2012, Optimal aeration control in a nitrifying activated sludge process, Water Research, 46, 2101-2110. crossref(new window)

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. crossref(new window)

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. crossref(new window)

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. crossref(new window)

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. crossref(new window)

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. crossref(new window)

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.

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. crossref(new window)

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. crossref(new window)

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.