Abstract

Abstract To sustain water quality in a water distribution system (WDS), disinfectant generally chlorine is boosted to the WDS. However, the concentration of chlorine should be limited to acceptable levels. The upper boundary of the range is set for preventing the occurrence of a disinfectant by-product, which is harmful to human health. The lower boundary of the range is set for controlling the growth of microorganisms as well as reducing the injection mass. As such, an optimization model was applied to solve the water quality issue in a WDS. However, in a WDS, chlorine decays and varies with time and space, affected by pipe material, temperature, pH value, and chlorine injection, etc. Therefore, in this paper, an improved fuzzy chance-constrained optimization model was proposed to optimize chlorine injection and location to maintain chlorine in a WDS distributed uniformly. The proposed model was applied to two WDSs to analyze the effect of reliability level and preference parameters on chlorine injection and location. The results indicated that the injection mass increased with the increase in preference parameter. The results also indicated that more booster stations can lower the injection mass, and two booster stations were suitable for WDS in Case 2. The method proposed can be applied to decide how and where to inject chlorine in a WDS under uncertainty, and can help managers determine whether an optimistic or pessimistic attitude should be taken under various reliability levels.

Highlights

  • Node 1 is the source node, and node 9 and node 25 are considered to be probable booster locations, which are in accordance with the other study on the same water distribution system (WDS) (Boccelli et al ; Köker & Altan-Sakarya )

  • The results indicated that the total injection mass increases with the preference parameter λ for λ ζU 1⁄4 ζL and λ > ζU 1⁄4 ζL as well

  • In case of two booster stations, i.e., node 1 and node 9 or node 1 and node 25 are taken as booster stations, the total injection mass needed for node 1 and 9 is higher than that for node 1 and node 25 for the same reliability level ζ and preference parameter λ, which indicated that booster chlorine at the end of WDS can significantly improve the water quality

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Summary

Introduction

The process for applying MFCCP model to solve the optimization of booster station can be summarized as follows: (1) Formulate the MFCCP model (Equations (15a)–(15d)); (2) Incorporate fuzzy parameters into the related uncertain constraints; (3) Incorporate various preference parameter and reliability level to construct scenarios for upper boundary, lower boundary, and both upper and lower boundaries, respectively, and generate the optimal solutions; (4) Analyze the optimal solutions and give the optimal number and injection mass of booster stations.

Results
Conclusion
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