城市供水管网运行的优化调度对于实现系统节能降耗至关重要。针对传统方法寻优效果差、实用性不高的问题，引入基于水塔时变控制水位的调度规则，在含多水塔的供水管网内探究最经济的多泵站联合调度机制。选用分时水泵状态、固定水塔水位和时变水塔水位为决策变量，分别构建电费最低且水压冗余度最低的多目标优化调度模型，采用第二代非支配排序遗传算法求解。结果表明：基于时变控制水位的调度规则更具经济效益，至少节约4.93%的成本；与分时调度计划相比，优化求解更高效，在非固定时段内实现运行状态的灵活切换；相较于固定控制水位，采取更低的控制水位下界，能有效降低高峰电价时段的水塔蓄存量。

As integral components of China’s national water network project, water distribution systems play a pivotal role in ensuring the safe utilization of water across various urban industries. However, the substantial energy consumption associated with operating these systems poses a significant challenge, hindering both the efficient utilization of water resources and the implementation of carbon reduction policies Consequently, there is an urgent need to address this issue and pursue avenues for improvement. Optimal operation research has been identified as a key strategy for promoting energy conservation in water distribution systems. Traditional strategies on optimal operation in water distribution systems typically adopted time-table schedules by the fixed time step as explicit decision-making for pumps. This strategy is easy-to-use, but it lacks of flexibility for pump switch when there are storage infrastructures in water distribution systems. Another issue is that the fixed time step constrains the attainment of maximal economic benefits through pump scheduling. This paper introduced a novel strategy that integrates time-variable trigger levels in storage tanks as an implicit decision-making rule for pump operation, with the aim of investigating potential energy-saving opportunities. More specifically, distinct pairs of trigger levels in tanks were assigned to regulate corresponding pumps during different electricity tariff periods. A multi-objective operational optimization model for water distribution systems was established to minimize electricity costs while minimizing the redundancy level of water pressure. This model was compared with two traditional strategies: time-table schedule and operation rules based on fixed trigger levels in tanks. These three models were then evaluated in a network case involving multiple pumps and tanks, with the objective of exploring the operational characteristics of joint pump and tank operations in water distribution systems. Results demonstrated that the strategy using time-variable trigger levels was capable of yielding superior Pareto-optimal solutions across both objectives compared with the two other strategies. Maintaining equal redundancy level of hydraulic pressure, this strategy facilitated the identification of greater economic benefits, resulting in a minimum of 4.93% reduction in electricity consumption costs. At the same computational budget, solving the optimization model using trigger levels for optimization was proved to be significantly more efficient compared to the time-table schedule. This efficiency stemmed from the smaller search space available when trigger levels were employed. Through a comprehensive comparative analysis encompassing variations in trigger levels, pump statuses, and their response to varying electricity tariff periods, it became apparent that the dynamic adjustment of trigger levels in tanks enabled flexible pump scheduling and optimized storage capacity utilization. Contrasted with fixed trigger levels, the lower trigger-off level effectively minimized stored water volumes during peak tariff periods, harnessing the storage capacity of water tanks at a lower budgetary cost while mitigating redundancy in nodal pressure. In contrast to explicit time-table schedules for pumps, the inclusion of water trajectory considerations in tanks promoted proactive pump switching to prevent tank backwater effects, indicative of reduced nodal pressure redundancy. The operational rule utilizing time-variable trigger levels allowed for pump switching at variable time steps, enhancing flexibility in pump operation scheduling. This adaptive feature enhances the possibility of identifying optimal solutions aligned with predefined objectives. In multi-pump, upstream-downstream joint water supply systems, the scheduling with time-varying water level control can achieve more significant economic benefits.