Robust Planning Decision Model for an Integrated Water System
Publication: Journal of Water Resources Planning and Management
Volume 143, Issue 5
Abstract
A critical issue faced by the water industry is to efficiently manage limited water supplies to satisfy water demand from different sections (e.g., industrial, agricultural, energy and residential) and provide fresh and reliable sources of water for people’s everyday life. Most existing research focuses on either water consumption planning (e.g., supply–demand balance) or water postconsumption planning (e.g., wastewater planning). It is expected to be more cost-effective to integrate the water consumption and postconsumption planning into a holistic model since they are highly interdependent. In this research, a closed-loop integrated water system including sources, water plants, end users, and wastewater systems is modeled using the network theory, and a robust planning decision model is developed to minimize the total system costs including operation costs (e.g., water production and distribution costs, and wastewater treatment costs) and penalty costs associated with directly emitting untreated wastewater to the environment. Various levels of uncertainties from both water demand and pipeline efficiencies are considered. Three sets of experiments are developed to test the effectiveness of the proposed decision model. The experimental results conclude that (1) the integrated decision approach can achieve more cost savings compared to separated decision processes for both the deterministic and stochastic scenarios; (2) the authors’ proposed robust model can provide good balance between system robustness and cost; and (3) the integrated water system is more cost-effective when the water processing cost is dynamic, which highlights the benefits of the inventory and on-site third-party water plants. Analogous to the smart power-grid innovation, which employs on-site generation and storage systems to improve energy efficiency and environmental sustainability, the authors’ proposed model demonstrates the benefits of using on-site inventory and third-party water plants to renovate the existing water infrastructure for more cost savings and reduced environmental impacts.
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References
Agudelo-Vera, C., Blokker, M., Vreeburg, J., Vogelaar, H., Hillegers, S., and van der Hoek, J. (2016). “Testing the robustness of two water distribution system layouts under changing drinking water demand.” J. Water Resour. Plann. Manage., .
Alva-Argáez, A., Kokossis, A. C., and Smith, R. (1998). “Wastewater minimisation of industrial systems using an integrated approach.” Comput. Chem. Eng., 22, S741–S744.
Arandia, E., Ba, A., Eck, B., and McKenna, S. (2016). “Tailoring seasonal time series models to forecast short-term water demand.” J. Water Resour. Plann. Manage., .
Babayan, A., Kapelan, Z., Savic, D., and Walters, G. (2005). “Least-cost design of water distribution networks under demand uncertainty.” J. Water Resour. Plann. Manage., 375–382.
Basupi, I., and Kapelan, Z. (2015). “Flexible water distribution system design under future demand uncertainty.” J. Water Resour. Plann. Manage., .
Ben-Tal, A., and Nemirovski, A. (2000). “Robust solutions of linear programming problems contaminated with uncertain data.” Math. Program., 88(3), 411–424.
Berglund, E. (2015). “Using agent-based modeling for water resources planning and management.” J. Water Resour. Plann. Manage., .
Bertsimas, D., and Sim, M. (2004). “The price of robustness.” Oper. Res., 52(1), 35–53.
Bi, W., and Dandy, G. C. (2014). “Optimization of water distribution systems using online retrained metamodels.” J. Water Resour. Plann. Manage., .
Chen, F., Huang, G., and Fan, Y. (2015). “Inexact multistage fuzzy-stochastic programming model for water resources management.” J. Water Resour. Plann. Manage., .
Cohen, R., Nelson, B., and Wolff, G. (2004). “Energy down the drain: The hidden costs of California’s water supply.” Natural Resources Defense Council and Pacific Institute, CA.
Dandy, G. C., Simpson, A. R., and Murphy, L. J. (1996). “An improved genetic algorithm for pipe network optimization.” Water Resour. Res., 32(2), 449–458.
Diao, K., Guidolin, M., Fu, G., Farmani, R., and Butler, D. (2014). “Hierarchical decomposition of water distribution systems for background leakage assessment.” Procedia Eng., 89, 53–58.
Draper, A., Jenkins, M., Kirby, K., Lund, J., and Howitt, R. (2003). “Economic-engineering optimization for California water management.” J. Water Resour. Plann. Manage., 155–164.
Eusuff, M., and Lansey, K. (2003). “Optimization of water distribution network design using the shuffled frog leaping algorithm.” J. Water Resour. Plann. Manage., 210–225.
Farmani, R., Walters, G., and Savic, D. (2005). “Trade-off between total cost and reliability for Anytown water distribution network.” J. Water Resour. Plann. Manage., 161–171.
Fu, G., Butler, D., and Khu, S.-T. (2008). “Multiple objective optimal control of integrated urban wastewater systems.” Environ. Modell. Software, 23(2), 225–234.
Giuliani, M., Castelletti, A., Amigoni, F., and Cai, X. (2015). “Multiagent systems and distributed constraint reasoning for regulatory mechanism design in water management.” J. Water Resour. Plann. Manage., .
Gleick, P. H. (1994). “Water and energy.” Annu. Rev. Energy Environ., 19, 267–299.
Goldstein, R., and Smith, W. (2002). “Water and sustainability: U.S. electricity consumption for water supply and treatment—The next half century.” Electric Power Research Institute, Inc., Palo Alto, CA.
Guo, P., and Huang, G. H. (2009). “Two-stage fuzzy chance-constrained programming: application to water resources management under dual uncertainties.” Stochastic Environ. Res. Risk Assess., 23(3), 349–359.
Guo, P., Huang, G. H., Zhu, H., and Wang, X. L. (2010). “A two-stage programming approach for water resources management under randomness and fuzziness.” Environ. Modell. Software, 25(12), 1573–1581.
Haghighi, A., and Bakhshipour, A. (2015). “Deterministic integrated optimization model for sewage collection networks using Tabu search.” J. Water Resour. Plann. Manage., .
Hassanzadeh, E., Elshorbagy, A., Wheater, H., Gober, P., and Nazemi, A. (2016). “Integrating supply uncertainties from stochastic modeling into integrated water resource management: Case study of the Saskatchewan River Basin.” J. Water Resour. Plann. Manage., .
Herman, J., Reed, P., Zeff, H., and Characklis, G. (2015). “How should robustness be defined for water systems planning under change?” J. Water Resour. Plann. Manage., .
Izquierdo, J., Montalvo, I., Pérez, R., and Fuertes, V. S. (2008). “Design optimization of wastewater collection networks by PSO.” Comput. Math. Appl., 56(3), 777–784.
Jung, D., Kang, D., Kim, J., and Lansey, K. (2014). “Robustness-based design of water distribution systems.” J. Water Resour. Plann. Manage., .
Kalogirou, S. (2005). “Seawater desalination using renewable energy sources.” Prog. Energy Combust. Sci., 31(3), 242–281.
Karagiannis, I. C., and Soldatos, P. G. (2008). “Water desalination cost literature: Review and assessment.” Desalination, 223(1–3), 448–456.
Lavric, V., Iancu, P., and Pleşu, V. (2005). “Genetic algorithm optimisation of water consumption and wastewater network topology.” J. Cleaner Prod., 13(15), 1405–1415.
Li, M., Guo, P., and Ren, C. (2015). “Water resources management models based on two-level linear fractional programming method under uncertainty.” J. Water Resour. Plann. Manage., .
Li, T., Li, P., Chen, B., Hu, M., and Zhang, X. (2014). “Simulation-based inexact two-stage chance-constraint quadratic programming for sustainable water quality management under dual uncertainties.” J. Water Resour. Plann. Manage., 298–312.
Liu, S., Konstantopoulou, F., Gikas, P., and Papageorgiou, L. G. (2011). “A mixed integer optimisation approach for integrated water resources management.” Comput. Chem. Eng., 35(5), 858–875.
Lubega, W. N., and Farid, A. M. (2013). “A meta-system architecture for the energy-water nexus.” Proc., 8th Int. Conf. on System of Systems Engineering (SoSE), Maui, Hawaii, 76–81.
Mielke, E., Diaz Anadon, L., and Narayanamurti, V. (2010). “Water consumption of energy resource extraction, processing, and conversion.” Energy Technology Innovation Policy Discussion Paper Series, Belfer Center for Science and International Affairs, Harvard Univ., Cambridge, MA.
Montalvo, I., Izquierdo, J., Pérez, R., and Tung, M. M. (2008). “Particle swarm optimization applied to the design of water supply systems.” Comput. Math. Appl., 56(3), 769–776.
Ormsbee, L., and Lansey, K. (1994). “Optimal control of water supply pumping systems.” J. Water Resour. Plann. Manage., 237–252.
Ostfeld, A., Oliker, N., and Salomons, E. (2014). “Multiobjective optimization for least cost design and resiliency of water distribution systems.” J. Water Resour. Plann. Manage., .
Shiklomanov, I. A. (2000). “Appraisal and assessment of world water resources.” Water Int., 25(1), 11–32.
Shiklomanov, I. A. (1998). World water resources. A new appraisal and assessment for the 21st century, United Nations Educational, Scientific and Cultural Organization, Paris.
Siddiqi, A., and Anadon, L. D. (2011). “The water-energy nexus in Middle East and North Africa.” Energy Policy, 39(8), 4529–4540.
Soyster, A. L. (1973). “Convex programming with set-inclusive constraints and applications to inexact linear programming.” Oper. Res., 21(5), 1154–1157.
Tong, L., Han, G., and Qiao, J. (2011). “Design of water distribution network via ant colony optimization.” Proc., 2nd Int. Conf. on Intelligent Control and Information (ICICIP), Harbin, China, 366–370.
U.S. DOE (U.S. Department of Energy). (2015). “Annual energy outlook 2015.” http://www.eia.gov/outlooks/aeo/pdf/0383(2015).pdf, (Dec. 19, 2016).
Wang, B., Huang, G., Liu, L., Li, W., and Xie, Y. (2016). “Integrated planning of urban water resources and water pollution control management: Case of Urumqi, China.” J. Water Resour. Plann. Manage., .
Wang, X., and Luo, L. (2016). “District water cycle management for wastewater reuse.” Green technologies for sustainable water management, ASCE, Reston, VA, 147–186.
Winz, I., Brierley, G., and Trowsdale, S. (2009). “The use of system dynamics simulation in water resources management.” Water Resour. Manage., 23(7), 1301–1323.
Xie, Y. L., Huang, G. H., Li, W., Li, J. B., and Li, Y. F. (2013). “An inexact two-stage stochastic programming model for water resources management in Nansihu Lake Basin, China.” J. Environ. Manage., 127, 188–205.
Yates, D. F., Templeman, A. B., and Boffey, T. B. (2007). “The computational complexity of the problem of determining least capital cost designs for water supply networks.” Eng. Optim., 7(2), 143–155.
Zeferino, J. A., Antunes, A. P., and Cunha, M. D. C. (2014). “Regional wastewater-system planning under population dynamics uncertainty.” J. Water Resour. Plann. Manage., 322–331.
Zessler, U., and Shamir, U. (1989). “Optimal operation of water distribution systems.” J. Water Resour. Plann. Manage., 735–752.
Zhang, W. (2013). “Water network design and management via stochastic programming.” Univ. of Arizona, Tucson, AZ.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 143 • Issue 5 • May 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: May 10, 2016
Accepted: Nov 2, 2016
Published ahead of print: Feb 1, 2017
Published online: Feb 2, 2017
Published in print: May 1, 2017
Discussion open until: Jul 2, 2017
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