School of Engineering, University of British Columbia (Okanagan Campus), 1137 Alumni Avenue, Kelowna, BC, V1V 1V7, Canada.
Prep Year Program, College of General Studies, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia.
Environ Monit Assess. 2022 Feb 28;194(3):232. doi: 10.1007/s10661-022-09874-0.
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.
实时大型供水系统的能源和水质同时优化对供水商来说是一项艰巨的任务。能源优化的复杂性随着大量管道、多台泵的调度以及水箱水位的调整而增加。大多数同时进行能源和水质优化的方法都评估小型（或假设）网络或牺牲水质。在提出的分阶段方法中，第 1 阶段使用基于风险的方法根据剩余氯故障以及服务区不同土地利用的相关后果，在大型配水系统中优化氯助推器的位置。第 2 阶段通过混合整数目标规划来优化日常泵调度，将 EPANET 和 CPLEX 软件集成在一起。目标函数最小化泵送能源成本以及与预期用水需求等目标约束的不良偏差。第 3 阶段评估网络级别的综合水力和水质性能。在沙特阿拉伯的 Al-Khobar 市的实时大型网络上实施该方法，该网络有 44 个地下水井、12 个水库、2 个储水池、191 条主管道、141 个节点和 17 个泵，说明了该框架的实用性。通过优化的泵送计划和氯助推器位置来模拟网络，水质性能提高了 40%，期望的水力性能与最优的泵调度相结合，与正常（未优化）基础案例相比，平均能源成本降低了 20%。
