Water distribution networks (WDNs) connect consumers to the source of water. The primary goal of optimizing WDNs is to minimize the network costs as WDNs entail high construction costs. This paper presents a newly developed parameter-less Rao algorithm for optimization of WDNs. The methodology is based on a pressure and discharge dependent penalty. It is written in python code by linking to a hydraulic model of WDN implemented in EPANET. The algorithm is applied and tested on three benchmark networks, namely Two-loop (TL), New York Tunnel (NYT) and Goyang (GY) and a real WDN of School of Planning and Architecture (SPA), Bhopal, India. Rao algorithm employs two approaches to hydraulic modelling, demand-driven analysis (DDA) and pressure-driven analysis (PDA), as the DDA-Rao algorithm and the PDA-Rao algorithm. PDA-Rao algorithm outperforms DDA-Rao algorithm in terms of convergence. PDA-Rao algorithm saved 1.7% network cost for the NYT network, while the best-known least-cost values were obtained for TL and GY networks. It is seen that the Rao algorithms are efficient, easy to apply and do not require any parameter tuning, which reduces a large number of computational efforts.

供水网络 (WDN) 将消费者连接到水源。优化 WDN 的主要目标是将网络成本降至最低，因为 WDN 需要高昂的建设成本。本文提出了一种新开发的无参数 Rao 算法，用于优化 WDN。该方法基于压力和排放相关的惩罚。它是通过链接到在 EPANET 中实现的 WDN 水力模型用 python 代码编写的。该算法在三个基准网络上应用和测试，即双环 (TL)、纽约隧道 (NYT) 和高阳 (GY) 以及印度博帕尔规划与建筑学院 (SPA) 的真实 WDN。Rao 算法采用两种方法进行水力建模，需求驱动分析 (DDA) 和压力驱动分析 (PDA)，即 DDA-Rao 算法和 PDA-Rao 算法。PDA-Rao 算法在收敛性方面优于 DDA-Rao 算法。PDA-Rao 算法为 NYT 网络节省了 1.7% 的网络成本，而为 TL 和 GY 网络获得了最著名的最小成本值。可以看出，Rao 算法高效、易于应用且不需要任何参数调整，减少了大量的计算工作量。