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Water 2017, 9(8), 596; https://doi.org/10.3390/w9080596

Chance-Constrained Dynamic Programming for Multiple Water Resources Allocation Management Associated with Risk-Aversion Analysis: A Case Study of Beijing, China

1
MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, S-C Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206, China
2
School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
3
School of Science, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
4
College of Electrical Engineering, Guangxi University, Nanning 530004, China
*
Author to whom correspondence should be addressed.
Received: 29 April 2017 / Revised: 8 July 2017 / Accepted: 3 August 2017 / Published: 11 August 2017
(This article belongs to the Special Issue Modeling of Water Systems)
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Abstract

Water shortage and water pollution have become major problems hindering socio-economic development. Due to the scarcity of water resources, the conflict between water supply and demand is becoming more and more prominent, especially in urban areas. In order to ensure the safety of urban water supply, many cities have begun to build reservoirs. However, few previous studies have focused on the optimal allocation of water resources considering storage reservoirs. In this study, a multi-water resources and multiple users chance-constrained dynamic programming (MMCDP) model has been developed for water resources allocation in Beijing, China, which introduces reservoir and chance-constrained programming into the dynamic programming decision-making framework. The proposed model can distribute water to different departments according to their respective demands in different periods. Specifically, under the objective of maximal benefits, the water allocation planning and the amount of water stored in a reservoir for each season under different feasibility degrees (violating constraints or available water resources situations) can be obtained. At the same time, the model can be helpful for decision-makers to identify the uncertainty of water-allocation schemes and make a desired compromise between the satisfaction degree of the economic benefits and the feasibility degree of constraints. View Full-Text
Keywords: chance-constrained programming; water supply; multi-water resources; reservoir regulation; uncertainty chance-constrained programming; water supply; multi-water resources; reservoir regulation; uncertainty
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Li, W.; Jiao, K.; Bao, Z.; Xie, Y.; Zhen, J.; Huang, G.; Fu, L. Chance-Constrained Dynamic Programming for Multiple Water Resources Allocation Management Associated with Risk-Aversion Analysis: A Case Study of Beijing, China. Water 2017, 9, 596.

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