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Staged energy and water quality optimization for large water distribution systems

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Abstract

Simultaneous optimization of energy and water quality in real-time large-sized water distribution systems is a daunting task for water suppliers. The complexity of energy optimization increases with a large number of pipes, scheduling of several pumps, and adjustments of tanks’ water levels. Most of the simultaneous energy and water quality optimization approaches evaluate small (or hypothetical) networks or compromise water quality. In the proposed staged approach, Stage 1 uses a risk-based approach to optimally locate the chlorine boosters in a large distribution system based on residual chlorine failures and the associated consequences in different land uses of the service area. Integrating EPANET and CPLEX software, Stage 2 uses mixed integer goal programming for optimizing the day-ahead pump scheduling. The objective function minimizes the pumping energy cost as well as the undesirable deviations from goal constraints, such as expected water demand. Stage 3 evaluates the combined hydraulics and water quality performances at the network level. The implementation of the proposed approach on a real-time large-sized network of Al-Khobar City in Saudi Arabia, with 44 groundwater wells, 12 reservoirs, 2 storage tanks, 191 mains, 141 junctions, and 17 pumps, illustrated the practicality of the framework. Simulating the network with an optimal pumping schedule and chlorine boosters’ locations shows a 40% improvement in water quality performance, desired hydraulics performance with optimal pump scheduling, and an average 20% energy cost reduction compared to the normal (unoptimized) base case scenario.

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Provided in the “Methodology” section.

Abbreviations

CWQI:

Canadian Water Quality Index

CCME:

Canadian Council of Ministers of the Environment

CPS:

Central pumping station

DP:

Dynamic programming

NLP:

Nonlinear programming

FMEA:

Fuzzy failure modes and effects analysis

GP:

Goal programming

kWh/m3 :

Kilowatt-hour per cubic meter

GHG:

Greenhouse gasses

LP:

Linear programming

MH:

Metaheuristic algorithms

MIGP:

Mixed integer goal programming

OPS:

Optimal pump scheduling

PVC:

Polyvinyl chloride

RPN:

Risk priority number

SA:

Simulated annealing

SAR:

Saudi Riyal

TDS:

Total dissolved solids

V,C,D:

Vulnerability, consequence, detectability

WDS:

Water distribution system

WSS:

Water supply system

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Acknowledgements

This research work is part of the Ph.D. work of the first author. This research work did not receive any internal or external funding. The author would like to thank the Ministry of Water and Environment, the City of Al-Khobar WDS (local office), Saudi Arabia, for providing the network data for use in this research work. The authors would also like to thank the anonymous referees for their helpful remarks that improved the quality of our work.

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Correspondence to Muhammad Nadeem Sharif.

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Sharif, M.N., Bakhtavar, E., Haider, H. et al. Staged energy and water quality optimization for large water distribution systems. Environ Monit Assess 194, 232 (2022). https://doi.org/10.1007/s10661-022-09874-0

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  • DOI: https://doi.org/10.1007/s10661-022-09874-0

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