Browse > Article
http://dx.doi.org/10.3741/JKWRA.2019.52.8.565

Optimization of water intake scheduling based on linear programming  

Jeong, Gimoon (Department of Civil Engineering, Kyung Hee University)
Lee, Indoe (Department of Civil Engineering, Kyung Hee University)
Kang, Doosun (Department of Civil Engineering, Kyung Hee University)
Publication Information
Journal of Korea Water Resources Association / v.52, no.8, 2019 , pp. 565-573 More about this Journal
Abstract
An optimization model of water intake planning is developed based on a linear programming (LP) for the intelligent water purification plant operation system. The proposed optimization model minimizes the water treatment costs of raw water purification by considering a time-delay of treatment process and hourly electricity tariff, which is subject to various operation constraints, such as water intake limit, storage tank capacity, and water demand forecasts. For demonstration, the developed model is applied to H water purification center. Here, we have tested three optimization strategies and the results are compared and analyzed in economic and safety aspects. The optimization model is expected to be used as a decision support tool for optimal water intake scheduling of domestic water purification centers.
Keywords
Linear programming; Optimization; Water purification plant; Water intake planning;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Ahn, J., and Kim, J. (2016). "The comparison among prediction methods of water demand and analysis of data on water services using data mining techniques." Korea Bigdata Society, Vol. 1, No. 1, pp. 9-17.
2 Han, Y., Huang, Y., Jia, S., and Liu, J. (2013). "An interval-parameter fuzzy linear programming with stochastic vertices model for water resources management under uncertainty." Mathematical Problems in Engineering, Vol. 2013, pp. 1-12.
3 Heydari, M., ShahiriParsa, A., Noori, M., Othman, F., and Qaderi, K. (2015). "Introduction to linear programming as a popular tool in optimal reservoir operation, a review." Advances in Environmental Biology, Vol. 9, No. 3, pp. 906-917.
4 Hong, E. (2016). Water demand prediction in water treatment plant using data analysis. Masters dissertation, Hallym University, Chuncheon, Republic of Korea.
5 Jung, D., Kang, D., Kang, M., and Kim, B. (2015). "Real-time pump scheduling for water transmission systems: Case study." KSCE Journal of Civil Engineering, Vol. 19, No. 7, pp. 1987-1993.   DOI
6 Kang, D., and Lansey, K. (2009). "Real-time optimal valve operation and booster disinfection for water quality in water distribution systems." Journal of Water Resources Planning and Management, Vol. 136, No. 4, pp. 463-473.   DOI
7 Kim, K., Choi, J., Jung., D., and Kang, D. (2017). "Sensitivity analysis of pump and tank sizes on water network operation and water age." Journal of Korea Water Resources Association, Vol. 50, No. 12, pp. 803-813.   DOI
8 Korea Electric Power Corporation (KEPCO) (2015). Electricity Rate Table.
9 Lee, C., and Lee, K. (2015). "Determination of optimal hourly water intake amount for H Arisu purification." Journal of Korea Water Resources Association, Vol. 48, No. 12, pp. 1051-1064.   DOI
10 Lee, S., and Park, H. (2011). "Understanding uncertainties in projecting water demand and effects of climate change for adaptive management of water supply risk of the water resources system." Journal of Korean Society of Water and Wastewater, Vol. 25, No. 3, pp. 293-305.
11 Mathworks, C. (2019). MATLAB and Optimization ToolboxTM Release R2019a.
12 Yoo, S. (2014). Short-term water demand forecasting scheme using hybrid model. Masters dissertation, Chungbuk National University, Cheongju, Republic of Korea.
13 Zhao, T., and Zhao, J. (2014). "Optimizing operation of water supply reservoir: the role of constraints." Mathematical Problems in Engineering, Vol. 2014, pp. 1-15.