The pressure-driven analysis is essential for modelling the pressure deficient condition of water distribution networks. Owing to the complexity, the development of pressure-driven analysis algorithms remains a grey area over the past few decades. As a milestone, EPANET 2.0 got upgraded to EPANET 2.2 with the inclusion of pressure-driven analysis. However, EPANET 2.2 has a shortcoming of using only a single value for the parameters, minimum pressure-head and required pressure-head of the demand nodes. Ironically, when a water distribution network serves for a wide area or during a fire-fighting period, the demand nodes have variable values for each of these parameters. To address this, a new method named Fictitious Component Free - Pressure Deficient Network Algorithm (FCF-PDNA) is proposed in this paper. The FCF-PDNA does not require any additional fictitious components. It can be used for both steady-state and extended period simulations. The proposed method is applied to water distribution networks of different sizes and types and confirmed that the FCF-PDNA could deal with variable values of minimum and required pressure-head. The suitability of this method for different scenarios that will lead to pressure deficient conditions is also analysed and verified. Moreover, the computational time taken by the FCF-PDNA and the EPANET 2.2 pressure-driven analysis is similar.

压力驱动分析对于建模供水网络的压力不足状况至关重要。由于复杂性，在过去的几十年中，压力驱动分析算法的开发仍然是一个灰色领域。作为一个里程碑，包括压力驱动的分析在内，EPANET 2.0已升级到EPANET 2.2。但是，EPANET 2.2有一个缺点，即仅对需求节点的参数，最小压力头和所需压力头使用单个值。具有讽刺意味的是，当供水网络服务于广阔区域或在灭火期间，需求节点的每个参数都有可变值。为了解决这个问题，本文提出了一种新的方法，即虚拟组件无压力缺陷网络算法（FCF-PDNA）。FCF-PDNA不需要任何其他虚拟组件。它既可以用于稳态仿真，也可以用于长时间仿真。所提出的方法应用于不同大小和类型的供水网络，并证实FCF-PDNA可以处理最小和所需压头的可变值。还分析和验证了该方法在不同情况下是否会导致压力不足的适用性。而且，FCF-PDNA和EPANET 2.2压力驱动分析所花费的计算时间是相似的。所提出的方法应用于不同大小和类型的供水网络，并证实FCF-PDNA可以处理最小和所需压头的可变值。还分析和验证了该方法在不同情况下是否会导致压力不足的适用性。而且，FCF-PDNA和EPANET 2.2压力驱动分析所花费的计算时间是相似的。所提出的方法应用于不同大小和类型的供水网络，并证实FCF-PDNA可以处理最小和所需压头的可变值。还分析和验证了该方法在不同情况下是否会导致压力不足的适用性。而且，FCF-PDNA和EPANET 2.2压力驱动分析所花费的计算时间是相似的。