A comprehensive review on energy efficiency enhancement initiatives in centrifugal pumping system

Optimisation of the operation of water distribution systems has been an active research field for almost half a century. It has focused mainly on optimal pump operation to minimise pumping costs and optimal water quality management to ensure that standards at customer nodes are met. This paper provides a systematic review by bringing together over two hundred publications from the past three decades, which are relevant to operational optimisation of water distribution systems, particularly optimal pump operation, valve control and system operation for water quality purposes of both urban drinking and regional multiquality water distribution systems. Uniquely, it also contains substantial and thorough information for over one hundred publications in a tabular form, which lists optimisation models inclusive of objectives, constraints, decision variables, solution methodologies used and other details. Research challenges in terms of simulation models, optimisation model formulation, selection of optimisation method and postprocessing needs have also been identified. A review of operational optimisation of water distribution systems is provided.Future challenges were identified, despite the large body of existing literature.Universally agreed formulation of an operational optimisation problem is needed.Algorithm performance for a particular problem requires improved understanding.A method for selecting only one solution for a real system needs to be developed.

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Lost in optimisation of water distribution systems? A literature review of system operation

Natural hazards have the potential to cause catastrophic damage and significant socioeconomic loss. The actual damage and loss observed in the recent decades has shown an increasing trend. As a result, disaster managers need to take a growing responsibility to proactively protect their communities by developing efficient management strategies. A number of research studies apply artificial intelligence (AI) techniques to process disaster-related data for supporting informed disaster management. This study provides an overview of current applications of AI in disaster management during its four phases: mitigation, preparedness, response, and recovery. It presents example applications of different AI techniques and their benefits for supporting disaster management at different phases, as well as some practical AI-based decision support tools. We find that the majority of AI applications focus on the disaster response phase. This study also identifies challenges to inspire the professional community to advance AI techniques for addressing them in future research.

Applications of artificial intelligence for disaster management

Considering water-energy nexus in optimising water supply systems not only ensures the sustainability of the water supply for increasing water demand but also diminishes water-related energy and environmental concerns. This paper presents a review highlighting knowledge gaps in optimisation models related to the water-energy nexus in water supply systems or “water supply side of the nexus”. Studies reported in the literature are categorised and systematically analysed in terms of different energy sources, centralised/ decentralised approaches and system parameters uncertainties. Several major gaps are identified. These include the lack of optimisation models capturing spatial aspects as well as environmental impacts of the nexus problems. The shortage of models considering uncertainties associated with water demand and renewable energy supply is another knowledge gap in this area. However, the main gap is the absence of models for optimising long-term planning of water supply system considering renewable energy within an urban context. Accordingly, based on this review, we have suggested pointers for future studies in the water supply side of the nexus.

The role of water-energy nexus in optimising water supply systems – Review of techniques and approaches

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Dynamic Programming Deterministic And Stochastic Models

This paper describes a transportation management system for disaster wastes to support early recovery from great the effect of earthquakes and other natural disasters. The system consists of a route selection process and a waste allocation process. For the system, the simplification map is made from arterial roads, temporally storage yards and disposal facilities. And, a directed graph with traveling times and transportation distances of adjacent nodes was generated from the simplification map. The route selection process calculates path length between all pairs of nodes by Warshall-Floyd algorithm. The allocation process decides transportation amount for each disposal facility by linear programming method. In the experiment, we confirm our method is able to manage waste transportation by using a map that simulated south Tokyo. Our system selected the shortest route from a disaster waste source to the nearest disposal facility with related to traffic conditions. The system allocated simulated disaster wastes for the facilities in proper quantities.

A route planning for disaster waste disposal based on robot technology

Many of the waterworks facilities in Japan were constructed during the rapid economic growth period. Today, the deterioration and renovation of these aged facilities have become a pressing issue. There are approximately 600,000km worth of water pipelines laid out across Japan, accounting for about 70% of the nation's water-related assets (totalling ¥40 trillion). To provide water that is safe to use, it is necessary to improve and innovate water purification technologies; not only that, it is also vital to properly maintain and manage the pipelines. The current research aims to apply reliability engineering in the waterworks field as one possible approach and to show its viability; it will also obtain vital messages revealed within pipeline incident data. In other words, we collected the information concerning water distribution pipeline incidents through questionnaire surveys and then analysed the cumulative failure distribution (unreliability) by pipeline material, the failure probability density and failure rate, among others.

Study on failure rate analysis for water distribution pipelines

This research is aimed at multiple-objective optimization of water operations in a water supply and distribution system. These objectives include reducing energy use while at the same time meeting water quality needs. The first objective is to propose water operations aimed at minimizing energy consumption. The second is to optimize water supply and distribution from the standpoint of water quality based on total organic carbon and the third is to attempt optimization that satisfies the first two objectives through multipurpose fuzzy linear programming (LP). This study mathematically formulates water operation planning issues focusing on reducing energy consumption and improving water quality in a water distribution system. Estimates show that a reduction in energy use of around 10% can be expected. Fuzzy LP is applied to achieve a balance among multiple objectives. The research demonstrates the effectiveness of the proposed multipurpose optimization when applied to trade-offs in water operation.

Optimized operation of water distribution system using multipurpose fuzzy LP model

\n The main purpose of this study was to investigate whether machine learning can be used to detect leak sounds in the field. A method for detecting water leaks was developed using a convolutional neural network (CNN), after taking recurrence plots and visualising the time series as input data. In collaboration with a pipeline restoration company, 20 acoustic datasets of leak sounds were recorded by sensors at 10 leak sites. The detection ability of the constructed CNN model was tested using the hold-out method for the 20 cases: 19 showed more than 70% accuracy, of which 15 showed more than 80%.

Water leak detection based on convolutional neural network using actual leak sounds and the hold-out method

This study proposes a method using genetic algorithms (GA) to optimize selection of appropriate pipe diameter during pipeline replacement planning for water distribution networks. Mathematical programming problems were first formulated to minimize cost of replacement while considering hydraulic constraints such as flow velocity for each pipe and water pressure at each node. In addition to the economic perspective, stability of flow velocity in pipes was considered as another objective function of the multipurpose programming problem. After this, a GA model combined with hydraulic pipe network analysis was created: the HGA model. Finally, a case study was conducted to show the validity of the proposed model. Results reveal that this multipurpose HGA model is useful for optimization of pipeline replacement planning.

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Yasuhiro Arai

Papers

A route planning for disaster waste disposal based on robot technology

Study on failure rate analysis for water distribution pipelines

Optimized operation of water distribution system using multipurpose fuzzy LP model

Water leak detection based on convolutional neural network using actual leak sounds and the hold-out method

Optimization model for water distribution network considering minimization of total replacement cost and stabilization of flow velocity in pipelines