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Economic model predictive control for the operation optimization of water distribution networks with risks
Author(s) -
Zhang Yuan,
Zheng Yi,
Li Shaoyuan,
Zou Yuanyuan
Publication year - 2021
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2218
Subject(s) - water supply , function (biology) , stability (learning theory) , computer science , supply and demand , control (management) , engineering , environmental engineering , economics , microeconomics , machine learning , evolutionary biology , artificial intelligence , biology
For water distribution networks (WDNs) with risks of insufficient water supply, some users' water demand is affected. Because the operation cost is positively related to the number of users whose water demand cannot be met, making the most of the limited water sources to meet the water demand of as many users as possible is the key to reduce the related cost in the operation optimization. Considering the time‐varying of users' water demand and the dynamic characteristics of WDNs, real‐time dynamic operation optimization of WDNs is required. In this paper, an economic cost function which connects the cost incurred by the risks and the controllable pressure is proposed based on the distribution of users and the corresponding water supply method. An EMPC strategy with the ability to guarantee the closed‐loop stability is adopted for the optimization problem. Performance of the proposed methods is illustrated based on the simulation of the Newtown case at different risk levels. Simulation results show that the extra cost decreases greatly in the situation with risks by applying the proposed pressure‐related economic function and the EMPC strategy.